Data driven Cost Estimation Optimizing Categories

How Artificial should Procurement Intelligence be ?

As the COVID-19 Pandemic changes all aspects of the business landscape, the Procurement function is taking center-stage in areas of risk mitigation, cost control, innovation, and ensuring overall business continuity. As companies around the world search for levers to gain a competitive advantage in this challenging environment, supply cost reduction is proving key to protecting and boosting operating margins.

With this in mind, companies need to adopt a more data-driven, strategic methodology to derive savings from these strategic partners. This is when Machine Learning and data driven approaches can renew the function and accelerate efficiency.

Traditional cost reduction measures are becoming less and less effective, as supplier networks become more strategic in nature. Value within the supply chain is no longer solely a function of the lowest product or service provided.

Therefore, it should not come as a surprise to see supplier leverage moving away from the purchasing organization and becoming more neutral (a zero-leverage scenario based on the give and take of vendor/supplier dynamics).  


Data empowered Procurement

Three ways Data can add to the function

1- Estimate the cost of a new product or service with near-perfect  accuracy
2- Identify savings opportunities across entire product categories
3- Provide live anonymous benchmarks on specific categories

A Fasteners' Category Case

Let’s assume we are comparing two screws within your Fasteners purchase category. 

Both screws have identical raw material, head type, and finishing, and very comparable length, width, heat tolerance, and thread length, and are purchased in similar quantities over the year, however the price of one screw is 25% more expensive than the other.  That 25% difference in price cannot be explained based on its attributes, and therefore becomes the basis for cost reduction at the SKU level. 

This simple example, which most likely exists several times over within your purchase portfolio, describes precisely what easyKost uncovers for its users.  It is a fast, accurate, easy-to-use tool that delivers serious results. 


 Mr Jason Mallory

KEPLER N-America

The present case study showed an overall savings rate of 8% year-over-year within the Fasteners purchase category vs. 2% in previous years. 

Cost reduction : based on data? A simple ask

With a data-driven approach, the ask is simple. Instead of a blind request of 10% reduction in price across the entire portfolio, you are simply asking your suppliers to deploy a consistent pricing model for the products you purchase. Kepler has found this is much more well-received by suppliers, as it is a focused ask rooted in in-depth analysis of their own pricing structure.

…And a leading U.S vehicle manufacturer

  • Over 8 billions of revenue
  • 13 000 employees
  • Spend : $5 Billions

As a leader in the production of light, medium, and heavy-duty trucks, buses, emergency and military vehicles, this client was looking for ways to optimize their purchase portfolio in accordance with their Procurement Transformation efforts. 

KEPLER and easyKost associating

EasyKost is cost modeling software utilizing machine learning and your own purchase data to identify pricing inconsistencies at the SKU/PN level. With KEPLER, they are working to help the client : 

  • establish cost savings, 
  • consolidate their supplier base 
  • reduce the number of Part Numbers in their overall portfolio.

5 step process to rapidly identify and realize savings

  1. Preparation
  2. Data Collection
  3. Data  Modeling / gap analysis
  4.  Validation of opportunities
  5. Execution

Smart Value Initiative

First savings captured after 2 months (negotiations) with a full savings scenario validated under 3 months.

Inputs required to kick off the preliminary analysis

Spend Data Collection

Preliminary Analysis Cost reduction

Category initial questionnaire

Machine Learning Costing KEPLER

Key criteria to assess addressability and opportunity of the category, general questions regarding:

  • Products
  • Data accessibility
  • Market
  • Strategy

Introducting the future of Costing

Turbo-charging cost-reduction with data

Kepler Consulting has partnered with easyKost, a leading Costing software Company that utilizes Machine Learning to identify savings opportunities within a company’s existing purchase portfolio.  

Using a Random-Forest based algorithm, the solution compares your own internal purchasing data against the attributes of the products you purchase to identify inconsistencies in your supplier’s pricing.  


The discovered inconsistencies are then used as the basis for renegotiating pricing with suppliers.  

This thoughtful, quantitative approach is helping numerous companies around the world turbo-charge their savings achievement, streamline the supplier base and create an overall more efficient supply chain.  


Possible use of cost estimating & data mining softwares

  1. Estimation of the cost of a new product/service with near-perfect  accuracy
  2. Identification of savings opportunities across your product categories
  3. Provision of real time & anonymous benchmarks on specific categories

Random forest : cost estimation based on drivers

The Software analyzes all the correlations between the actual purchase prices and the product or service “cost drivers” in order to identify inconsistencies and optimization opportunities.

Cost is estimated through a thousand decision trees in a random forest. 

The method leads to a 60%+ increased accuracy compared to traditional statistical methods.

Random Forest Cost Modeling

Identifying cost-drivers

Differentiating among the Data sources

Cost Drivers

A technical characteristic: the weight, the length, the width or diameter…

A function: E.g. the function “Screwdriver (yes/no)” of a drill…

A country or region: they inevitably influence the cost of the product.

A supplier: you will not pay the same price for the same product.

A percentage: even if it is preferable to use a value, a factor representing a percentage can be used as cost driver.

Not Cost Drivers

Indicators that vary over time or would not include at least two separate values : 

  • a time-variable factor
  • an exchange rate
  • a unique identifier
  • a material cost
  • a date, an incoterm
  • a currency

Collecting Data

By extracting attributes from Client drawings, our off-shore data team based in Chennai India, creates a database that captures all cost drivers per part number. 


  • Cost drivers are defined by family using technical expertise
  • For each family, a database is created capturing cost drivers by part
  • Cost drivers are normalized to improve the model
  • The full catalog of attributes is provided to Client to close the project
Pricing supplier Artificial Intelligence


Three savings generation strategies are used to maximize results while maintaining  the right amount of work per supplier type. 

  1. Supplier Negotiations:  Strategic Suppliers
  2. Supplier Re-allocation & Consolidation: Transactional suppliers
  3. Tail Spend Optimization & Consolidation: Tail suppliers

Focus on supplier reallocation

Machine Learning estimations predict the best price that key strategic suppliers should be able to offer on existing parts that are currently supplied by transactional suppliers.

Price inconsistency analysis

Costing Modeling Price Inconsistency

Estimate transactional with highest cost reduction opportunity. 

Screen Capture : EasyKost software

Supplier change simulation

Based on Batch Estimations run on the exhaust models, the new state of exhaust would shift heavily away from Suppliers 1 & 2 into Suppliers 3 & 5. Total savings if every part number target was achieved would be $2.04M. This would require 596 parts to be moved to new suppliers. 

Supplier Change Simulation KEPLER AI Procurement
Supplier reallocation

Testing the model and entering the validation phase

E.g. Commodity 12 - Before

Original State : $1.7M

Key supplier A ……………………32 PN

Key supplier B ……………………59 PN

22 Non-preferred suppliers .96 PN


E.g. Commodity 12 - After

Optimized State : $1.5M

Key supplier A …………………… 59 PN

  • 8% reduction of incumbent business
  • 7% reduction on $180K new awarded

Key supplier B …………………… 128 PN

  • 19% reduction of incumbent business 
  • 21% reduction on $192K new awarded 

Validating the Model

Out of a $93 million spend in scope, the analysis and modeling estimated a savings opportunity of $5M.

Supplier Optimization Reallocation
Supplyer Reallocation Optimization KEPLER

Executing the model

Focus on Supplier A

Focus Supplier Costing AI

Highlighting inconsistencies

After reviewing the entirety of our product database and comparing attributes from Supplier A, we have validated that the pricing model demonstrated the capability of achieving accurate targets: 

Price Inconsistency Costing Supplier Model

After reviewing the entirety of our product database and comparing attributes from Supplier A, we have validated that the pricing model demonstrated the capability of achieving accurate targets: 

Price Inconsistency Costing Supplier Model2

Getting the Results

The Washers Example

Category Optimization Costing KEPLER

Client was challenged to consolidate the Washers product family.  KEPLER and easyKost were able to achieve 183% of the savings target and eliminate more than 70% of vendors.

Few project’s additional numbers

  • Savings Target: $5MM / $93MM
  • Mission ROI: 7.1x
  • Current Direct Spend Addressed: $500MM  (15% total)

Going Further

Permanent Webinar Access

Downloadable Version

Webinar : Turbo-Charging Cost Savings Utilizing Machine Learning

The Easy-Kost Solution

EasyKost is a publisher of cost estimation and modeling software based on artificial intelligence algorithms. Capable of generating predictive models from random forests, EasyKost is a leading tool both for helping to develop new products and for calculating savings.

A Webinar on Artificial Intelligence applied to Costing

During a Webinar held on June 4th, 2020, KEPLER and EasyKost presented Machine Learning technology applied to modeling and cost optimization. This presentation was an opportunity to recall the main principles of AI, present the Methodology used and illustrate the point with a client case.

EasyKost Booster: the power of analysis combined with the consulting strengths

Convinced of the relevance of this new technology, KEPLER and EasyKost have developed an innovative approach exploiting the computing power of costing software to quickly identify and capture purchasing gains within the main categories (direct and indirect). Artificial intelligence algorithms applied to customer data help identify and maximize savings opportunities through supplier renegotiation, volume reallocation or technical standardization / optimization.

Useful Links

The worst Supply Chain practices must be confessed and not only by constraint

Hand turns a dice and changes the word

Responding to the ever-changing expectations of consumers in a highly competitive digital economic environment involves having a solid, agile, and cost-effective Supply Chain. After all, companies need to minimize and monitor the most harmful supply chain management practices. This can only be achieved by addressing the elimination of the worst practices in the organization, processes, and digital resources of the company.

The importance of a robust supply chain

Diagram 1

Some examples of worst practices

1/ Managing the quality of information

Non-updated product sheets in ERP (purchase price, MOQ, Incoterm,…) resulting in non-compliant supplier orders 

In the absence of good product data quality, non-compliant supplier orders systematically result in poor product availability, one solution to this problem is to set up an efficient communication system with the purchasing and supply divisions that can reduce data update times up to 90 %.

Stocks of raw materials, semi-finished products and/or unsuitable finished products that destroy exposure

The inability to provide daily updated data on inventories of raw materials, semi-finished products, and finished products presents two major concerns:

  • The decrease of the WCR for companies, the deployment of a dashboard tailored and user-friendly is essential in order to take charge of the management of a share of its WCR.
  • The improvement of CBN reliability and automation, resulting in the consolidation of production and scheduling plans, elements that can be disruptive to the supply chain.

Exhaust-data analyses (OTD, pallet volume, transport, suppliers, returns, etc.) that use unreliable data to misrepresent supply chain decisions

Uncertain data consistently generate biased analyses and therefore lead to actions that are not suited to the real issues.

2/ Order processing

Fixed orders placed with the supplier at the very early stage of the need, which generates overstocks

This approach impairs flexibility to cope with the hazards of the various downstream systems (production tool, customer demand, etc.). However, it is essential to react quickly in order to prevent harmful effects due to the overload of the operational system (Véronneau and Cimon, 2007) and also to preserve a certain agility in for the Supply Chain.

Diagram 2

Changing orders in the closed period (lead time supplier) affecting the supply chain and the supplier’s planning

A frequent worst practice that makes the supply process more difficult. In addition to the consequent extension of delays caused by these amendments, the supplier-customer relationship does not come out with less damage. The definition of clear and effective management rules contributes greatly to limiting this situation.

Diagram 3

Non-shared requirements with the supplier reducing exposure on future orders

A range of bad practices are observed on the visibility provided to suppliers:

  • Failure to share forecasts with the supplier: this bad practice causes suppliers to secure their lead time by prolonging it, which has a negative effect on the customer’s sourcing flexibility. The establishment of systemic sharing makes it possible to negotiate shorter lead times, up to 50%. Some studies (Cachon and Fischer (2000); Lee et al. (2000); Cachon and Larivière (2001); and Zhao (2002)) show that when demand and stock information is shared, this results in a significant reduction in stocks and costs
  • Absence of systematic summary sharing of fixed supplier orders: just like the previous one, the implementation of this communication makes it possible to comfort the supplier about their production and supply plan.

3/ Workflow Management

The failure to review the distribution plan in the light of logistical and commercial constaints in the stores leads to the blind disposal of warehouse stocks

The reduction of stock inventory is one of the major challenges of a sustainable Supply Chain, as long as the reduction is made under rules that take into account the logistical and commercial constraints of the company, its customers and the market, hence the need for a method to optimize this process of stock reduction that makes it possible to increase the sell-through rate.

Non-optimized storage options with the high national and low local turnover references placed in local storage

The process of choosing product storage streams must be the result of an in-depth analysis of the market, turnover, type of products, geographical locations of suppliers and customers, etc… This will make it possible to save storage space on warehouses, reduce operating costs and inventory valuation and thus optimize working capital requirements.

The lack of reliable in-line consumption preventing flow regulation

A failure to control IT consumption in production will hinder the delivery of components along the line, the waste management through the forcing of manufacturing orders and, ultimately, the calculation of the PRI.

4/ Performance Management: QCD element animation

The non-existence of KPIs and activity animation which impedes the attainment of the desired performance targets

A relevant dashboard and the ABC of a successful Supply Chain management and performance control. This allows to measure the discrepancies and therefore solve the problems related to these discrepancies within the concerned department and, if necessary, to report them to other decision-making authorities within the organization.     

Distribution between the different Supply Chain divisions is an obstacle to communication

Failure to communicate and establish roles is a major setback to supply chain performance. An in-depth integration of the Supply Chain through the exchange and coordination of information flows between all members of the supply chain, therefore makes it possible to better define their RACI (R: Director; A: Approver; C: Consulted; I: Informed) (Kempainen and Ari, 2003).

Cumbersome processes with no added value

One of the most common bottlenecks in supply chain management and burdensome processes (purchasing, procurement, preparation, etc.) with a large number of non-value-added tasks that are essential for the proper functioning of the process. One of the most efficient methods is the combination of VSM (Value Stream Mapping) to streamline the process with RPA (Robotic Process Automation) in order to automate it, which makes the error rate negligible and saves uptime. Two examples among others are the manual sourcing process or asset management to be applied on future orders from the supplier.


  • Cachon G.P. et Fischer M., “Supply chain inventory management and the value of shared information”, Management science, vol. 46,2000, p. 1032-1048.
  • Cachon G.P. et Lariviere M.A., “Contracting to assure supply : How to share demand forecasts in a supply chain”, Management science, vol. 47,2001, p. 629-646.
  • Garnier A. – 10 key trends to understand Supply Chain Management
  • Garnier A. – Supply Chain Management: is Blockchain the new RFID?
  • Lee H., So K.C. et Tang C., “The value of information sharing in a two-level supply chain”, Management science, vol. 46,2000, p. 626-43.
  • Zhao Y., The impact of information sharing on supply chain performance, Ph. D. Thesis, Northwestern University, 2002.
  • Kempainen K. et Ari P.J.V., “Trends in industrial supply chains and networks”, International journal of physical distribution & logistics management, vol. 33,2003, p. 701-719.
  • Véronneau S. et Cimon Y., “Maintaining robust decision capabilities : An integrative humansystems approach”, Decision support systems, vol. 43, p. 127-140,2007.

The decrease of air freight, an opportunity for commercial airlines?


Air freight : situation and players

It is a bad time for air freight. In June 2019, the world traffic fell by 4.8% in tonne-kilometer (TKM) compared to the same period in 2018 (1). The International Air Transport Association (IATA) attributes this decline to rising kerosene prices, Sino-American trade tensions and protests in Hong Kong – forcing world’s first cargo airport to shut down temporarily.

Contrary to public opinion, the decline in traffic affects both commercial airlines and all-cargo airlines.

Indeed, close to 70% of world air freight (in TKM) is transported in cargo decks of commercial aircrafts. Moreover, the top 10 freight carriers are occupied by 7 commercial airlines against 3 cargo specialists only.

Freight constitutes 10 to 20% of commercial airlines revenues. To compensate the freight deceleration, the latter will have to capitalize more on passenger revenues in order to ensure their growth.

Cargo decks of commercial planes are becoming an additional source of revenue to leverage.

Sans titre-ENG


The innovation offered by Airbus and Safran

In March 2018, Airbus and Zodiac Aerospace (now Safran Cabin) announced a partnership for the development and launch of passenger units located on the lower decks of A330s – space previously reserved for passenger luggage and cargo.

The partnership glimpses sleeper units, lounge, areas for children and meeting rooms. Safran Cabin which already produces rest units for on-board staff, would like to extend its services to passengers until 2020. This additional comfort feature arises with the return of ultra long-haul flights, made possible with planes capable of covering previously unattainable distances (A350-900 ULR and 777-8X).

© Airbus SAS 2017 – All rights reserved.

The passenger units will be easily interchangeable with the regular freight containers and will constitute an alternative to compensate the vacant lower cargo deck led by the decrease of cargo freight. These new services, sold as a paid option, are very timely for airlines which want to optimize each square meter on their planes.

© Airbus SAS 2017 – All rights reserved.

In addition to being a source of alternative revenues when cargo demand is low or not profitable enough on some routes, the pods allow airline companies to differentiate their offers and “upgrade” their service level at lower costs, without structural modification of the seats and the cockpit.

The concept raises a clear business interest – AirFrance-KLM is interested in equipping its A330s – however it must be validated by the European Aviation Safety Agency and the American FAA. Therefore, the units will become an additional profitability lever in an industry where average profit per passenger per year (6.12$) doesn’t exceed the price of a Big Mac in Switzerland. (3)  

Unleashing your potential: outsourcing strategic processes

Businessman in blue suit working with digital vurtual screen

Outsourcing strategic processes can bring more added value to secure performance and enable internal resources to focus on the big picture.  When it comes to new supplier identification, negotiation or strategic sourcing process, many of our clients need to increase the level of expertise and empowerment without adding headcount. By outsourcing these processes to a dedicated team, the client can also focus on what is most important to its business – whether it’s innovation, restructuring, or reassessing the market to meet their customer’s needs.

Supplier Scouting

Many procurement departments do not dedicate enough expertise and time to scope for new, qualified suppliers and insure comprehensiveness and robustness of supplier market screening. Moreover, supplier scouting could be extremely time consuming if the focus on the most promising areas is not enough defined and documented. When procurement is challenged to meet production demands, finding new suppliers as plug and play as possible is a long and painful task.

KEPLER's best practice

Utilizing a macro study methodology like KEPLER’s, regional supplier identification can be limited to the countries most likely to commercially produce the needed product or category. Through this data driven approach, an exhaustive search can be conducted and result in a shortlist of screened suppliers to conduct RFI, RFQ/RFP, or on-site qualification. By outsourcing this process to a global team, with resources where the suppliers are located, the client can focus on keeping the lines running.​

Supplier Negotiation

When it comes to managing suppliers, our clients often have too many of them to consistently maintain contact with. As a result, some negotiation opportunities are not addressed at all, such as remote suppliers, non-critical technologies, tail spend. Utilizing a third party to analyze spend, build clear vision and negotiation strategy and directly negotiate with suppliers is a great way to quickly capture untouched savings opportunities.

Figure 1

Through refined processes and tools for negotiation, it becomes possible to provide an outside perspective and identify new savings.

KEPLER's business case

For one of its clients, KEPLER reviewed over $135M spend and 154 suppliers to prepare for negotiations. Over the course of 3 months, the team prepared toolkits and engaged in negotiation with 87 suppliers, enabling the client to capture 3% in previously unidentified savings.

Procurement Outsourcing

Client initiatives are always constrained by a lack of resources but adding internal people is often not possible or non-relevant. Whether the work is time limited and there is not a need to sustain resources, or there are not available resources to staff a project, outsourcing the process at an optimized cost is a reliable and flexible solution for short or long-term staffing. 

KEPLER's best practice

KEPLER organizes mixed operational teams with local consultants and offshore / low cost consultants (India), to manage and execute on our BPO offerings. Through its deep knowledge in procurement and supply chain, KEPLER is able to effectively manage processes and adapt to the needs of its clients, regardless of the maturity of the process.

KEPLER's business case

For one of KEPLER’s clients launching a new product, the ability to outsource the end-to-end sourcing process enabled them to meet tight production deadlines without carrying additional long-term resources. Over the course of 10 months, KEPLER negotiated and placed orders for 1200+ parts and $11M spend. By outsourcing the sourcing of high mix, low complexity parts, the client team was able to focus on highly complex, system level sourcing initiatives. By utilizing flexible resources, the client was able to increase their sourcing throughput by 20% and focus their industry knowledge on strategic initiatives.

Outsourcing is not only a question of bringing additive resources, it is also and mainly a question of efficiency. Bring more value added with experienced team and robust methodologies, deploy flexible team fully aligned with the workload and planning of each initiative, optimize cost through remote low-cost professionals allow KEPLER to go further, deeper and quicker compared to internal teams.

Outsourcing is also a great method to refocus on the core business strategy and elevate above the day-to-day challenges that can block change.  

5 digital solutions serving production and maintenance at Airbus

Airliner in motion on abstract background of highrise and binary code

The world air traffic, catalyzed by the expansion of economies, in particular in India, China and Middle East, meets an unprecedented growth. Airbus plans a demand close to 37,400 aircrafts until 2037. This represents a yearly average evolution of +4.4%.

In 2018, Airbus demonstrated record throughputs on assembly chains, with an average of 66.6 A320 models produced each month. Coupled to an order book of 7,525 aircrafts or 9.38 years to the current production rate, the manufacturer aims at intensifying furthermore its cadences thanks to digital tools.


Solution 1

Each player on the aerospace market only detains a fraction of the data of his environment. Partnered with Palantir, Airbus rolled out in 2017 its new data platform called Skywise. This platform aims at increasing the value chain via crucial data sharing among players of the aerospace industry.

  • Suppliers: details and availability of components
  • Manufacturers: design, production and MRO
  • Airline companies: flight data and passenger behaviors
  • Airports: plane, passenger and luggage movements

Skywise gathers all the data of 22 airline companies, 2,500 planes, 12 million flights and 25 million maintenance files.  With digital, Airbus divided its problem resolution time by 3 for the assembly of the A350 and it respected the increase of production cadences of this program. In the future, Airbus plans to incorporate supplier data (currently hosted on a separate platform) as well as partner airport data.

Solution 2

In cooperation with a major consulting firm, Airbus developed smart glasses improving precision and reducing the complexity of cabin planning processes. The seat marking is a long process because the specificities between plane categories and planning according to airline company requirements makes standardization impossible. This “wearable” technology divides by 6 the required time for seat marking.

Solution 3

A key element of 4.0 aerospace production is the creation of IoT “digital twins”. These virtual copies replicate the characteristics of a product or a physical process. The coupling of virtual and physical worlds allows to analyze data and monitoring systems in order to prevent issues before they even occur, avoid down times and plan the future by using simulations. The Safran-GE joint venture called CFM International pairs each LEAP engine provided to Airbus with a digital avatar, providing a real-time diagnosis of engines in circulation and idle ones.


Solution 4

Airbus equips each of its aircrafts with an average of 20,000 embedded MRO sensors in order to identify defective equipment and structural parts that need to be changed. This way, this process helps to optimize the exploitation and lifespan of the plane.

The anomalies identified by the Flight Data Monitoring (FDM) lead to anticipating a change of parts or equipment rather than a repair – the Turn Around Time (TAT) of an equipment renewal being usually shorter than the repair – and limits duration of AOGs (Aircraft On Ground).

In parallel, the parts aimed at the spare part fleet are produced in an anticipated way, reducing stocks and production times. The demand for “spare parts” is then satisfied without jeopardizing the production of parts targeted to the initial aircraft assembly.

Solution 5

Partnering with Dassault Systems, Airbus announced the roll-out of the 3DEXPERIENCE platform to support its digital transformation. 3DEXPERIENCE lays the foundation of a numerical consistency, from conception to operations, in a single data model for a unified user experience throughout all product divisions and categories. With this implementation, Airbus hopes a robust production configuration coupled to an increase of its prototype development lead times.

Avec ces outils, Airbus entend booster sa capacité à produire vite et bien. De la conception, avec 3DEXPERIENCE, en passant par la production, avec les lunettes intelligentes, jusqu’à la maintenance, à l’aide de capteurs et répliques virtuelles, les solutions digitales représentent un gisement de valeur déterminant pour Airbus, dont Skywise devient progressivement la colonne vertébrale. 

Network Design: the 5 good questions to ask

A lot of our clients reflect upon the relevance of their network design and wish to challenge their flow organization in order to address the stakes of reactivity and efficiency imposed by the market. This reflection is even more necessary that most retailers (more than 80% according to recent polls) and an increasing number of industrials tackle the omnichannel battle. Being closest to the consumer, providing quick and customized service at the lowest cost… many challenges that put high pressure on logistics networks and force players to rethink their organization. How many warehouses and where to place them? What storage strategy to associate? What delivery method to choose?

Oftentimes, the evolutions of logistics networks are done under constraint, for instance to compensate deficits of storage surface. In France, more than 8 million square meters of additional storage surface have been put out on the market in 2018 by 40 logistics players. This approach is pushed by a global trend of regionalization of just-in-time production.

Yet, to be efficient, the flow master plan cannot be apprehended opportunistically, link by link, but rather in a holistic way. The network design is part of a mid/long term logic and aims at supporting the company’s business plan implementation. This requires the top management’s implication in order to have a transversal reading of the challenges and opportunities faced by the company. The evolution of supply and demand will have to be integrated upstream in the different scenario modeling, implying a reflection in the break.

In the most mature organizations, the network design will even be used to draw change management in other corporate functions because it moves the set of corporate functions.

benchmark 2018In a recent benchmark among players of the retail sector (brand with a network of at least 100 stores in France), the declared costs of their Supply Chain fluctuate between 8 and 15%. These cost gaps are partly due to specific services offered by the different brands. For instance, the fact of offering to customers and/or stores, a per unit preparation requiring an unpacking operation, increases structurally the picking costs by 2 to 3%. Without mentioning the costs implied by a customer promise to D+1, allowing a craftsman to place his/her orders at 5pm in order to be delivered the day after on his site before 7am…This creates additional costs that need to be precisely estimated on the field to let the decision maker pick the right choices in terms of service offerings.

Mind the popular misconception that outsourcing logistics is THE solution to optimize the couple cost/service. Indeed, it will increase the business expertise and bring flexibility but it can also be disappointing. The markup operated by providers represents on average between 5 to 15% of increase compared to an internal production. Furthermore, if the handled products present strong specificities for instance in terms of congestion or fragility, it is more than likely that your current logistics team have an expertise that will be very difficult or expensive to find amongst the market players.


Once you’ve had this operational understanding of your costs, you will have all elements in hand to define the right level of service that you want to offer. For instance, the linear improvement of delivery times can be very expensive and sometimes completely unnecessary compared to your customers’ or prospects’ real expectations.

In addition to an interpretation per product type, the reflection should also relate to the customer segmentation according to their attractiveness. This attractiveness can be assessed according to the margin or market growth level or to the customer’s turnover potential increase.

Example of Matrix

Product types-costing

The definition of customer promise requires a very good knowledge of the market. For example, we have been recently asked by a cosmetics subcontractor to reduce its lead time from 14 to 10 weeks on the market. Collaborative workshops allowed us to find out that the current lead time was perfectly acceptable by the contractors. However, the latter is completely uncompromising on the respect of this commitment. We have reworked the flow organization in order to secure this lead time, without applying additional constraints on the flow scheme.

In the various modelized scenarios, a robust sensitivity analysis must be realized in order to check the impact of hypotheses on the cost, quality and lead time results. A wrong anticipation of risks leads to important additional costs, whether they are indirect through dispute processing in 60% of cases or direct with the application of penalties in more than half cases. They can even result in customer loss in 30% of cases. Some risks are relatively well apprehended by industrials, like supplier risk which appears now almost systematically in the model’s evaluation grids, or country risks which lead to a world known and shared ranking, created by FM Global, an American damage insurance company.

However, other parameters are much more difficult to model because they’re often unknown.

In the first place, there is the regulatory risk. For example, the customs charge evolutions represent a confusing factor for Supply Chains in our global economic paradigm. Closer and more concrete, the taxation threat which constrains refrigerated freight is like a sword of Damocles above logistics flow schemes with per kilometer costs which could triple. The multicriteria analyses and the workshops conducted within the network design study allow to choose the scenario that will optimize benefits while limiting risks. The most resilient organizations use “what if” scenarios in order to build a continuous activity plan and secure quick backup plans’ implementation.

The transition plan generally falls within a period of 2 to 3 years to let all players of the value chain adjust their job to this new scheme. It is essential that the identified projects involve the entire organization, as the project’s success isn’t only the Supply Chain’s responsibility. The crucial role of IS in these projects is obvious and requires the right level of technical competencies (internal or external). One of the key success factors through the network design evolution lies on the good evaluation of necessary resources and an agile driving of potential threatening bottlenecks. The savings and benefits planning will systematically be linked to a resource plan in order to have a realistic understanding of P&L impacts on a short and mid-term.

The entire organization and its partners must be aligned on the target flow scheme which will let either the organization follow new dynamics, or accelerate its decline, in case of failure. Priorities and projects phasing are an integral part of the network design. All industrials agree on the fact that one of the key success factors of such a large project is to make all the impacted employees share responsibility, be it operational people in Supply Chain, marketing, procurement or finance positions. All must be convinced by the approach in order to support the project both internally and among clients. Indeed, with the digitization of the purchasing act, there is no doubt that the network design, is more than ever, a differentiating strategic element for the company.


In a nutshell…

All of these questions are necessary if one wants to define an optimal flow scheme. Numerous network design solutions exist to support this strategic reflection but beware of the shortcut that implies that the tool will answer the questions. Its utilization is, on one hand, often limited by the level and the size distribution of the available data and will not be able to replace collaborative workshops among jobs. Once defined, the network design should then be regularly challenged, as many internal and external parameters influence this equilibrium.

Quick repricing or how to generate significant savings with tail suppliers (video)

Companies have increasingly large supply bases for various reasons: acquisitions, decentralized procurement, uncontrolled supplier portfolios, or process weakness. Due to the high number of suppliers, supply processes, and resource constraints, significant productivity goes unrealized. Strategic sourcing teams focus on high-value-add suppliers and strategic projects while plant buyers address tactical suppliers when issuing orders. At a time of increased cost pressures and complex supply chains, a significant amount of spend goes unaddressed year over year. With sourcing managers pushing their supply base to drive new innovations, achieve greater productivity, and keep the plants running, companies are continuing to ignore the tail spend and leave savings unrealized. That’s why Kepler has developed a Quick Repricing offering to generate savings with…

Industry 3.X and TPM deciphered

Following our last article “Industry 4.0… well let’s talk about 3.X!, we propose to continue with a brief description of the TPM supplemented by the different types of technologies in Industry 4.0.

What is the TPM?

Machines’ defects or failures during production have negative effects on the production schedule as well as on employee morale. Total Productive Maintenance (TPM) is at the origin of the equipment reliability. It is essentially machine-centric and its productivity measured by the OEE (Overall Equipment Efficiency, also called TRS for Synthetic Efficiency Ratio). *

The focus is on reducing the 16 OEE generalized losses, classified into three groups: equipment losses, labor-related losses, and material-, tool- and energy-related losses.

The JIPM (Japan Institute for Plant Maintenance) has defined in 1989 the eight pillars of the TPM management approach :

Autonomous management and maintenance of equipment

Waste elimination / Improvements on a case-by-case basis

Scheduled maintenance

Improvement of knowledge and know-how:

Safety, working conditions and environment

Quality control or maintenance

Mastering product design and associated equipment

Efficiency of related services or “TPM at the office”

These eight pillars will remain the industry fundamental. The question is simple: “How will the 3.X consolidate and ensure ever more efficient maintenance? “.

What does Industry 3.X bring us?

The analysis of Big Data, the Internet of Things, artificial intelligence, virtual and augmented reality, and cyber-physical systems are considered the main levers of the next digital upgrade.

  • Big Data analysis

The term “big data” refers to large, technically complex data sets for typical data analysis and processing applications. Big Data analysis allows companies to “predict”. Companies can predict events using in-depth analysis of large data sets that will be actively monitored. The amount of information stored is growing four times faster than the global economy, while computing speeds are growing nine times faster. This remains very important because from the beginning of the digital data creation until 2003, there were 5 exabytes of information created and now the same amount of information is created every two days. A study with over 2,000 business participants from 9 major industry sectors and 26 countries, shows that 80% of global CEOs have recognized the importance of data mining and analytics for their organizations. Large data can extract new data from existing data, providing important technical and business information that helps make clearer and more efficient decisions.

Cloud computing and machine learning are also leading technologies in Big Data analytics, cloud computing is a scalable platform that helps to use IT resources more efficiently, helping automate and reducing system costs. isolated. Cloud manufacturing is the concept that reflects the idea of a smart factory, that is, the collaboration of advanced production models with cloud computing technology to achieve computer-based and service-oriented production. (Givehchi, Tresk and Jasperneite, 2013).

  • Internet of Things (IoT)

The idea of the Internet of Things appeared for the first time in the 1980s to meet the needs of automated teller machines (Shon, 1996). Many of these devices have been networked. The Internet of Things (IoT) is the terminology used for physical devices or components that can be connected via the network and have the ability to communicate with each other via Radio Frequency Identification (RIFD) or intelligent sensors (Gilchrist, 2016b ). According to ISO / IEC JTC1 (2015), IoT is an infrastructure of interconnected objects, people, systems and information resources as well as intelligent services to enable them to process information from the physical and virtual world and react. However, it is a concept similar to physical cyber systems (CPS). According to an estimate, around 25 billion devices / objects will be interconnected and will communicate with each other, and this will be used by 2020. The Internet of Things allows businesses to add transparency to processes and make it analytically measurable. These sensors can be worn by the operators, placed on the production lines, on the machines directly, in the warehouses …

Similarly, the new RFID type solutions make it possible to guarantee a perfect products traceability on the value chain and also to measure everyday performance through the collection of relevant data. IoT’s ability to offer enhanced intelligence helps organizations optimize decision-making capabilities, ensure efficient data collection, and generate the right reports for their specific environment. IoT helps the company gain “intelligence” by giving them the ability to analyze their physical processes that were not measurable before. All of this contributes to better strategic and operational capacity and, in some cases, to a competitive advantage (Kopetz, 2011).

  • Artificial Intelligence

AI was introduced as a field of research in the late 1950s. Artificial intelligence is a sub-domain of computer science, whose sole purpose is to give machines or robots a human intelligence as they become independent platforms and able to make intelligent decisions autonomously (McCarthy, 2007). There are two types of AI: Artificial Narrow Intelligence (ANI) which is related to single-task applications in a very specific area that we are witnessing today (ie Go game), then there is Artificial General Intelligence (AGI) which is still developing. The concept of AGI is broad, deep and contains features that surpass human intelligence in many dimensions such as analytic speed, memory, multitasking, pattern recognition and adaptability with new auto information. Learned (Muehlhauser, 2013). According to Hawking et al. (2014), the success in creating the AGI would be the biggest event in human history, but they are not sure whether it is also the last, unless one learns to avoid risk, hence the experts’ hesitant vision in relation to AI.

How many jobs will be replaced by robots and AI in the coming years? And how many new jobs and positions will there be created? The answer is not given but, as an example, Japan’s largest bank, Mitsubishi UFJ Finance, has recently installed robots for its customer service operations and IPsoft, a call center, is using an AI robot called “Amelia” able to self-learn outside preprogrammed knowledge. “Amelia” can now process more than 60% of all incoming requests.

  • Virtual and Augmented Reality

The Smart Factory will be supported by advanced human resources programs in “Virtual Reality and Augmented Reality”. Virtual Reality (VR) is a computer-simulated environment. It is presented to the user as a real environment. It can support employee training programs and business process support with compatible digital devices. On the other hand, Augmented Reality (AR) has a head start and allows the user to interfere with a simulated environment (Boud et al., 1999). According to Jason Ganz, CEO of Agora VR, “Internet has allowed us to learn anything – VR and AR will allow us to experiment everything”. Experts suggest that some of the management tasks will be held virtually as, for example, meetings and strategic conferences. In addition, the RV and RA will assist the Human Resources Department in training and the continuous coaching system for transition in a digital environment.

  • Cyber-physical systems

In order to make the smart factory operational or functional, we will need “Cyber Physical Systems (CPS)”. CPS’s are intelligent systems that bridge virtual and physical components used in production, logistics and products. It is the concept that combines with the Internet of Services (IoS) to make 3.X industry possible, opening up new possibilities for innovative applications and processes. CPS’s will facilitate the paradigm shift from business models and market models to all stakeholders in the value chain including suppliers. All these technologies combined to other technologies such as additive manufacturing, for example 3D printing, selective laser sintering, cobotic, AGV, etc., are the basis for the future factory, which brings together virtual and physical systems via physical cyber systems. Such a fusion of technical processes and business processes will be a gateway to the concept known as the “Smart Factory” (MacDougall, 2014).

All these technologies already known, how will they contribute to production sites? And especially as part of a TPM approach? In the next article, we will present the contributions of the digitized environment to the TPM and more broadly, practical solutions that we put in place within our customers’ companies.

Sources :

Boud, A. C., Haniff, D. J., Baber, C., & Steiner, S. J. (1999). Virtual reality and augmented reality as a training tool for assembly tasks. In Information Visualization, 1999. Proceedings. 1999 IEEE International Conference on (pp. 32-36). IEEE.

Gilchrist, A. (2016b). Middleware Industrial Internet of Things Platforms. In Industry 4.0 (pp. 153-160). Apress.

Givehchi, O., Trsek, H., & Jasperneite, J. (2013). Cloud computing for industrial automation systems—A comprehensive overview. In Emerging Technologies & Factory Automation (ETFA), 2013 IEEE 18th Conference on (pp. 1-4). IEEE.

Hawking, S., Russell, S., Tegmark, M., & Wilczek, F. (2014). Stephen Hawking: \’Transcendence looks at the implications of artificial intelligence-but are we taking AI seriously enough?’. The Independent, 2014(05-01), 9313474

Kopetz, H. (2011). Internet of things. In Real-time systems (pp. 307-323). Springer US.

Shon, S. W. (1996). U.S. Patent No. 5,499,238. Washington, DC: U.S. Patent and Trademark Office.

MacDougall, W. (2014). Industrie 4.0: Smart manufacturing for the future. Germany Trade & Invest.

McCarthy, J. (2007). WHAT IS ARTIFICIAL INTELLIGENCE? Retrieved March 15, 2017, from

Muehlhauser, L. (2013, September 15). What is AGI? Retrieved March 26, 2018, from

Industry 4.0… well let’s talk about 3.X!

Industry 4.0 has become obvious for everyone… but we must keep a sense of proportion!

The term Industry 4.0 was introduced for the first time during the 2011 Hanover Fair (Wahlster, 2012). It comes from an initiative launched by the German Federal Government as part of its overall High-Tech strategy. An introduction to the Industry 4.0 concepts can be found in Lasi et al. (2014).

For the record, the first industrial revolution reflects the automation of production through steam and water (Industry 1.0); for the second one, the electrification (2.0) has arrived, and finally, more recently, the third one saw the digital computer advent (3.0). All these revolutions were related to inventions based on breakthrough scientific discoveries (Watt, Tesla, von Neuman) opening up new industries.

Bear in mind that even other revolutionary inventions, such as Marconi’s (1909 Nobel Prize) wireless telecommunication, which is the basis of today’s global communication, as well as varied possibilities for supply chain control in the modern production are not considered “revolutions” for the industry.

Thus, the Industry 4.0 concept is not linked to a technical revolution following a breakthrough scientific discovery!

Indeed, main tools required for the Industry 4.0 implementation have already existed for a long time: sensors, robots, big data, Internet of Things, cloud computing, 3D printer. More than a technological revolution, Industry 4.0 represents rather a complete reorganization of the mode of production with the modern tools, giving a bigger weight to the network. 

This new generation of factories aims to boost the dynamism of European industry through several actions: modernization of production, increase of competitiveness, flexibility in demand, positioning in front of the challenges of globalization…

If it’s not a revolution, then why is it THE subject today? 

Every company today has to communicate on digital. According to recent studies, several hundreds of billions of 4.0 investments are launched each year in the world. Companies expect returns on investment in less than two years by generating several additional revenue points while reducing costs – 2 to 4% according studies. In this context, the main players are banking on this high-potential market and are making war on platforms for the factory of the future: Siemens with MindSphere, GE with Predix, Bosch with IoT Bosch Suite, ABB with ABB Ability, etc.

Today, global players such as Siemens, Bosch, SAP and Deutsche Telekom have positioned themselves, have entered into alliances and are offering Industry 4.0 offerings while developing demonstrators (Kohler C & C, 2015).

Countries do not hesitate to follow this movement because they see it as an opportunity to inspire new life into their countries, their regions, their cities. In addition, technological fertility with a large computational capacity and new generations increasingly “trendy”, are the key ingredients to promote this digital transition since the Internet bubble.

From our point of view, Industry 4.0 will initially be a catch-up factory: the “pick and place” allows Japanese machines for several decades to load and unload cycle machines automatically. The same goes for robotic handling trucks transporting semi-products, from station to station, on less and less predefined routes. Until now, they had never convinced the French manufacturers while they have been working to the satisfaction of everyone in Japan for more than 20 years. This catch-up achieved, the factory will already have a more current “look” As for what will be in the future, probably an extension of the current breakthroughs in more industrial fields and more opportunities.

Therefore, calling Industry 4.0 a “revolution” represents an inconsistency with the first three revolutions, as it is simply a natural evolution of computer-integrated manufacturing (CIM). rather it is materialized by small steps that one could possibly call V.3.1, V.3.2, etc.

The industry evolution (adapted from Schrauf and Berttram, 2016)

Industry V.3.x or “Advanced Digitization”, will target businesses moving towards the customer through e-commerce, digital marketing, social media and the customer experience. Ultimately, virtually every aspect of the business will be transformed by the vertical integration of R & D, production, marketing and sales and other internal operations, as well as new business models based on these advances. Indeed, we are moving towards the complete digital ecosystem.

But the reality is a bit more complicated

A study of the DZ Bank (sample of 1000 companies with a turnover between € 0.5 M and € 125 M) published in 2014, showed that 35% of Mittelstand companies thought that digitization was not very relevant compared to their value chain and another 14%, that it played a weak role.

How is this situation explained?

  • check

    Cultural and Psychological Barriers: below, the many sources of uncertainty for business leaders that are hindering the introduction of Industry 4.0:

Obstacles perceived by business leaders in the deployment of Industry 4.0 (Kagermann et al., 2013)

  • check

    Financial resources may be lacking for businesses to implement the digitized industry;

  • check

    From a management stand point, there is a lack of global digital vision. Leaders struggle to perceive the potential of digitized industry and the associated ROI;

  • check

    Today, the majority of companies are overwhelmed by the complexity of the “digital” theme and all the implications in the business;

  • check

    Cybersecurity: for the German Academy of Technology (Acatech), there is no security solution efficiency, only those that exist are not used systematically. Although the threats are real in the application: infection of equipment with malware via office networks, insertion of malware by USB key or external hardware, illegal access by a remote maintenance network, deliberate sabotage or misbehavior , incitement to reveal personal data including passwords by phishing (fraudulent emails, phishing) and by “social engineering” (criminals take a false identity, for example in an email where they can present themselves as tax authorities or a human resources interlocutor).

Although clean techniques of Lean production systems are not yet in place in all the workshops of production sites, the “Smart Factory” with the very promising German label “Industry 4.0” is already making the show.


While the Toyota Production System (TPS) has been shown to be the most efficient production system, Industry 4.0 is still in a framing phase with the ambitious goal of becoming a cyber-production system. Partial and sometimes limited knowledge about Lean production systems leads to distorted ideas that both approaches are incompatible.

The implementation of a ferocious digitization without a management of the “just necessary” in a logic of change management would lead to waste in today’s industry, where the machine-man continues to cohabit and will in the next decade. Certainly, the digitized industry will make the production system more flexible, but it is not certain that it will be faster, smoother, more stable and more accurate. Industry 3.X itself will materialize anyway, with or without this politico-economic initiative. In fact, digitization in the industry has been going on for a long time and is still going on.

Of course, it is the connection, the availability and the processing of the data that will make the difference in the future. Critical minds might even say that the 3.X industry is a self-fulfilling prophecy to a certain extent and will not meet the high expectations it raises.

We will see in a future publication the different types of technologies proposed by, let us be indulgent, the “4.0” and a brief definition of the TPM.

Sources :

Kagermann, H., Wahlster, W., & Helbig, J. (2013) Recommendations for implementing the strategic initiative Industrie 4.0 – Final report of the Industrie 4.0 Working Group. Frankfurt am Main: Communication Promoters Group of the Industry-Science Research Alliance, acatech.

Kohler C&C (2015). Industrie 4.0 : quelles stratégies numériques ? 1–67.

Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., and Hoffman, M. n, “Industry 4.0,” Business & Information Systems Engineering, vol. 6, no. 4, p.239, 2014.

Nelles, J., Kuz, S., Mertens, A., and Schlick, C. M., “Human-centered design of assistance systems for production planning and control: The role of the human in industry 4.0,” in Industrial Technology (ICIT), 2016 IEEE International Conference on, pp. 2099–2104, IEEE, 2016.

Schrauf, S., Berttram, P. (2016). How digitization makes the supply chain more efficient, agile, and customer-focused.

Wahlster, W., “From industry 1.0 to industry 4.0: Towards the 4th industrial revolution,” in Forum Business meets Research, 2012.

The use of machine learning to generate quick savings and gain in price consistency

The purpose of this article is to share our experience in the use of machine learning to generate quick saving opportunities and homogenize purchased pricing across business units / regions in large groups.

  Context and challenges within a multi-BU group

It could rapidly become cumbersome for a large group and its supply management team to ensure consistency of prices on a specific category.

  • check

    Why pay $5.6 dollars for an extruded tube of 10cm long and 2mm diameter and $20 for 20cm and 2.5mm diameter tube?

  • check

    Or a certain price for a red product and double for its blue version?

Those gaps can be normal but need to be controlled and understood so that suppliers or R&D can be challenged.

Even with a corporate organization and systems, Business Units are often independent or even worse, siloed. They could implicitly refuse to play it global because they need to go fast and stay independent. But, beyond organization & cultural behaviors, main barriers are technical & IT related:

  • check

    Products have different specifications & characteristics making the price comparison and alignment difficult

  • check

    There is no common repository combining technical & economical information

  • check

    History of pricing is rarely reviewed

  • check

    ERP system not alerting on pricing gaps

  • check

    Tail pricing is not properly controlled

  • check

    Pricing revision routines can be different across the group

  • check

    Multi contract with similar suppliers

  • check

    Suppliers apply a different cost of doing business per BU / Region

For sure, the traditional should cost approach and solutions can help solve these issues.

However, they are often complex to implement on a large scale, because they require a lot of manufacturing process related information, strong technical expertise and deep & time-consuming cooperation with suppliers (open book policy is mandatory).

 Refer to our article “Supply Chain optimization: a total cost approach

  Value proposition

Many firms have developed an innovative & effective approach combining advanced analytics and predictive algorithms (derived from Artificial Intelligence) to generate quick savings opportunities, only by processing your existing data.

The methodology is based on 5 pillars:

  • check

    Create a cost model based on shared cost drivers considering BU/Region specifics

  • check

    Utilize benchmarking to identify gaps across BU/Regions and optimized sourcing strategies

  • check

    Identify overpriced products and quantify savings opportunities

  • check

    Utilize data mining to determine optimization levers and prepare arguments for supplier negotiations

  • check

    Specify the management systems & required needs to sustain the process 

The following benefits have been observed:

  • check

    Identify savings opportunities (negotiation, VAVE, resourcing)

  • check

    Generate quick wins through “analytics based” negotiations with suppliers

  • check

    Control supplier quotes on new projects

  • check

    Improve Sourcing Strategies through optimized supplier allocation per cluster

  • check

    Drive continuous improvement through a robust cost model, increased skills, and improved cross-functional collaboration

  Machine learning based costing solutions

Machine learning based costing solution which estimates the price of a new product or service by processing current/historical data through a sophisticated algorithm, such as “Random Forrest”. Random Forrest is a nonparametric statistical method that performs learning on multiple decision trees driven on slightly different subsets of data generated by Bootstrap techniques (Ref. Breiman, L., Random Forests. Machine Learning. 45, 5-32 (2001)).

This type of methods allows to estimate the price of a product/service based on pre-identified parameters called “cost-drivers”. The estimation is very quick and accurate (30% of increased accuracy in comparison to traditional statistical methods).

The main advantages of machine learning based costing compared to traditional methods are:

  • check

    The user does not need to be an expert of the manufacturing process of the product. The estimate is based exclusively on the product characteristics (“cost drivers”) which are information you have access to internally (vs. asking to your supplier)

  • check

    It can mix an infinite number of cost drivers, those cost drivers can be continuous or discrete, technical (weight, function, color, raw material type, …) or commercial (country, volumes, supplier…)

  • check

    Ability to process databases for which the number of variables largely exceeds the number of observations

  • check

    Ability to identify and weight automatically the most important parameters, and therefore the cost drivers that impact the most

  • check

    Ability to interpret results

  • check

    Ability to manage missing values / incomplete database

For all these reasons machine learning based software helps create a very robust and ready-to-use costing model.

Beyond the above, machine learning based costing solution is processing all current purchasing prices and identifying inconsistencies / gaps versus estimates, which makes it easy to identify savings opportunities, including negotiations with suppliers.

Finally, some solutions have integrated benchmark functionalities which allow to compare each BU/Region for a specific category (even through products that have different design & characteristics).

They are increasingly utilized in industry and therefore is, every day, adding external benchmark knowledge for each commodity (IP and confidentialities being respected).

This allows to create benchmarking communities and share further (life sciences, automotive…)..




Examples of software

Analytical Model

  • Explanatory and operations- centered model
  • “Best Landed Cost” Estimation and Target Price Definition
  • Allows to optimize the prices in production and to control the plans of progresses suppliers
  • Difficulty accessing process references and maintaining them over time
  • Intrusive approach towards suppliers
  • Expert model with little diffuse
  • Timeout for setting and performing encryption
  • Precision ?
  • Siemens PLM
  • A Priori
  • Facton
  • Statistical Parametric Model

    • Easy and quick to use
    • Estimated price coherence, and accuracy (conditional)
    • Non-intrusive approach to suppliers
    • Product and service applications
    • Very relevant in the upstream phases of the life cycle and for the analyses of coherence
    • Requires minimal data and quality history
    • Model that is not very “explanatory” to moderate supplier progress plans
    • Less relevant model for setting target prices and “Best Landed Cost”
    • Difficulty in modeling qualitative parameters
  • Seer
  • EstimFEC
  • Non-Parametric Statistical Model

    « Random Forests »

    • Easy and quick to use
    • Consistency of the estimated price, and precision increased by 30% compared to parametric models (conditional)
    • Non-intrusive approach to suppliers
    • Product and service applications
    • Very relevant in the upstream phases of the life cycle
    • Relevant also in the downstream phases for the analysis of price coherences and the identification of opportunities thanks to the explanatory properties of the forests
    • Integrates a lot of cost drivers, including qualitative ones
    • Detects technological breakthroughs
    • Prioritizes cost drivers
    • Manages missing values and can work with a limited sample
  • Model less relevant for setting target prices and “Best Landed Cost”
  • easyKost
  • 5 tips to make your IT purchasing performance sustainable

    The rapid emergence of new technologies, the price opacity of major market players, the experts shortage in I.T procurement are all elements justifying an urging need to bring performance and professionalism to I.T Purchasing.

    Here are 5 tips to make your I.T purchasing last:


    In big companies, with multiple geographic locations, I.T purchasing is often managed directly by countries or business lines, without any real coordination. Each country, in connection with its own development, has been able to set up an IT Department that implicitly manages its expenses and many of them are therefore out of the Purchasing Department radar screens and are not covered by any coordinated policy.

    In collaboration with the IT Department, I.T purchasing must therefore (1) define the policy to adopt on each segment in relation to the structure of each supplier market, – centralization (global or regional), coordination, 100% local, (2) stall a RACI matrix on each phase of the purchasing process (budget forecasting, purchasing, supply, expenditure control, SRM), (3) make this policy work through transversal animation of the different entities of the company (country and / or business lines).


    The term “I.T spending” hides actually a real jungle: nothing in common between hardware, cloud, software or service expenses. It is in this jungle again that we meet unavoidable big names (Google, Oracle, Microsoft, and Salesforce, etc). It is also in this jungle that we face unscrupulous salespeople who leverage their expertise and the apparent complexity / uniqueness of their solutions to sell more and more.

    It is therefore vital to put, in front of them, buyers who are experts in their field. This way, they can develop a peer-to-peer exchange by best piercing the sellers’ interests, sales cycles and emerging alternative evolutions. The I.T expert purchasing profile is a rare resource, with long training. It is illusory to rely on internal mobility to quickly acquire such skill. Only looking for external profiles in mature I.T purchasing organizations can meet the need.


    The current period is more to budget restraint on indirect spending, of which I.T is mostly part, while the complexity of technologies is constantly changing. Salvation resides more in an adaptation of the offering to the real company needs than in the negotiation of a particular material or support. The principle is to switch from a purchasing model in silos (equipment, service…) to a full cost model based on usage (I.T as a service), thus limiting the expenditure to the necessary and especially putting it under condition of activity.

    This approach makes it possible, on the one hand, to directly connect the cost of I.T to the actual use and, on the other hand, to make the cost distribution between the different internal customers, objective. This distribution is most often in the classical model carried out by means of more or less arbitrary keys.


    In a context of constant increase in I.T spending (+ 4% per year on average, + 4.5% forecast for 2018) – especially due to digitalization -, many of these expenses are not managed by the purchasing department and being directly in the hands of internal customers (IT Department for an important part, but also trades which can have specific needs), the follow-up, that it is budgetary, contractual or functional is a real headache. In particular, having a consolidated overview of I.T costs is often a challenge.

    Two points are particularly lacking: the budget monitoring itself – the vision of the adequacy between actual incurred expenses and the budget provided – and the control of billing before payment. The first point is to put in place a consistent and accurate expenditure classification so that allocations are clear, easy to achieve and aligned across entities. The second point may require the implementation of dedicated tools, which will never completely replace human control, as providers often show ingenuity (not always voluntary) in billing. In addition, the establishment of a contract library and a SAM (Software Asset Management) are two examples of control tools particularly relevant for I.T expenses.


    The I.T ecosystem is made of a multitude of actors of a heterogeneous nature. Many purchasing procedures, processes, rules especially in risk management, evaluation criteria, are not adapted to this diversity.

    For example, supplier qualification rules are often incompatible with working with start-ups: ability to present 3 years of balance sheets, potential level of dependency quickly important as the targeted company’s activity is fledgling, lack of certification… Capturing innovation is then seen as a risky exercise that mature organizations may not be ready to take.

    Agility goes through the definition of specific processes in order to be able to collaborate in a different way with companies with “exotic” configurations, even if it reinforces certain aspects to secure collaboration (co-development model, exclusivity, incubation, intellectual property…). Often, the effectiveness of this type of measure is increased tenfold by the establishment of a dedicated organization within the purchasing department, with specific skills, not only on new technologies, but also in the legal or financial field to better support these fragile start-ups.

    10 key trends to understand Supply Chain Management

    In few years only, Supply Chain Management became one of the trendiest topics for organizations facing globalized markets. But in parallel, it also remained one of the foggiest topics for managers at every level. Sticking to logistics origins, we could stand our ground on initial Supply Chain Management definition (a system reaching all processes, flows and resources needed to deliver the right product/service at the right place, in the right timing, with the right quality, quantity and cost). But I think the best way for Managers to keep an up to date vision is to have a clear understanding of the main trends shaping business environment. Through this exercise, we clearly see how the essence of Supply Chain Management (systemic approach, vision sharing, animation principles…) is essential to face all challenges emerging.


    #1 Value chain schemes involve a growing complexity for business Management

    #2 Needs for Flexibility, Reactivity and Coordination make older models obsolete

    #3 Technological revolution acts as a trend amplifier


    #4 Operational Excellence forms a powerful approach for transformation plan set up

    #5 Fully aligned business models are on top of best practices

    #6 Refocus on green supply chain should/ may occur soon


    #7 Control of information/ data is vital

    #8 Manager behaviors drive team understanding and involvement

    #9 Misalignment of skill market and business needs is impacting organization design

    #10 Today’s Supply Chain truth will not be applicable tomorrow

    Supply Chain: Logistics Masterplans

    The industrial footprint of major international companies has continued to grow over the last thirty years without however leading to a streamlined logistical organization. The topics currently dominating the Supply Chain represent as much a takeover of the logistics organizations as a very strong expected potential in terms of expected gains.

    ​By developing industrial sites around the world to meet the strategic imperatives, companies are obliged to implement a consistent set of processes to shape their value stream… If an applied implementation of the value stream is essential for meeting performance targets, it is indeed a significant position due to the implied needs (transportation, storage, support functions …).

    This is the price of increasing complexity. The internationalization of major organizations and the dispersion of industrial assets must now be combined with the growing need for flexibility and responsiveness required in the whole value stream without however restraining competitiveness.

    What about flexibility? How to adapt one’s organization to be able to respond to shifts in demand (shifts in volumes, shifts in the nature of the requested products, modulation of the demand frequency)?

    And about responsiveness? How to position yourself to make these adjustments in the least possible space-time? 

    Industrial groups are not less demanding than the end-customer regarding flexibility and responsiveness: series’ sizes are reduced, effective time optimized and buffer stocks are reduced to the lowest possible level. In turn, they all require, from the logistics sector, a very high level of performance and regardless of the degree of internationalization of the latter.

    ​What are the levers currently being used?

    • Towards upstream logistics

    After working on the downstream perimeter and leaving the upstream optimization to the purchasing (optimization of the purchase price) and supply (securing service levels) teams, supply chain managers ask us more and more about existing potential for reducing upstream logistic costs.

    For a multinational, such costs can represent, over a year, up to 15% of the purchasing budget. They relate to the “door-to-door” transportation operations, including some players focused on warehousing operations and handling.

    of the purchasing budget

    The levers are not fundamentally different from what we know about the downstream:

    • General optimization of the Logistics framework

    • Generalization of the pick-up routing principles and sharing of resources used (trucks or containers) 

    • Tightened management of resources utilization (e.g. containers fill rate)

    • Alignment of internal schedules on standard logistics times (e.g. orders distributions)

    • Streamlining the panel of third parties, competitive bidding and optimization of contract terms (advanced price negotiations by route and channel, securing the provider’s quality of service, backup solutions …).

    Using these levers on the upstream supply chain, large industrial groups such as Fiat or Valeo succeeded for example to generate in 2012 savings equal to € 7,8m and € 20m respectively. These initiatives are widely promoted in corporate communications as they contribute directly to the improvement in operating margin.

    • Regaining control of the flow

    This approach was also at the heart of the study we conducted in early 2013 for one of the major market players in consumer goods, with a large presence in Asia Pacific emerging countries (5 local plants). The analysis of upstream logistics flows and costs incurred helped to highlight existing opportunities especially in terms of rationalization of domestic transportation from local suppliers.

    The challenge in this case was first to question the relevance of the incoterms used in contracts. By delegating the organization of transportation to the suppliers, our client did not put himself in a position to control the cost and launch supply chain optimization initiatives. By taking over the organization of logistics flows, all levers mentioned above could therefore be activated. 

    total transportation cost

    On a domestic scope, regarding road transportation, switching to a touring system and using if necessary consolidation/deconsolidation nodes in the upstream flow enabled a 50% reduction in the total transportation cost. 

    • Adapting the organization

    In addition to streamlining the process it is also good to question the Supply Chain organization to ensure that it is in line with the needs of flexibility and responsiveness mentioned above.

    When a large industrial group sets up operations in a new country, it initially needs to manage the new plants centrally to ensure continuity in regard of the internal performance standards. According to the culture of the company, the progressive relocation of support activities follows with varying responsibilities, giving varying degrees of autonomy as appropriate.

    A major English automotive supplier recently asked us to streamline its Supply Chain & Purchasing process in China and review the division of roles and responsibilities between central and local teams. We could then measure how the resurgence of historically centralized organizations could cripple the team’s daily life. The complexity of the decision making process (creates constant communication and various validation requirements) can lead to a severe lack of responsiveness and penalizes customer satisfaction.

    Supply Chain is, in this sense, often trapped between two worlds; particularly regarding the issues of the upstream portion mentioned above, who could offer supplies on time touring transports without having the operational view of the factory? With the same reasoning, who can achieve economies of scale in purchasing or in service providers’ costs without having the data on the aggregated demand of the group?

    We always recommend our clients to clearly separate strategic processes and business processes and then assign the former to global functions (which have a general vision of the group needs) and the latter to local or regional functions (which are directly aware of the field requirements). Timing is therefore essential between the local and the global, but the company makes sure that each one addresses the appropriate level of issue. 

    If large international groups sometimes struggle to accelerate the transition to an efficient supply chain management in terms of process organization, confronting emerging market players make them directly face the need to change their way of thinking. Established in China and India and working with Western companies on issues concerning operational efficiency, we are regularly witnessing the extreme mobility and adaptability of local players. Supply chain managers will be more than ever in the forefront to support the strategic goals of the company: international development, “end-to-end” competitiveness, securing flexibility.

    Supply Chain optimization: a total cost approach

    Industrial Europe is currently going through a period marked both by strong competitive pressure from low-cost countries and a narrowing, a direct consequence of a consumption crisis in local markets. On the front line since 2008, the automotive sector was quickly forced to adapt and work on the flexibility of its model in order to maintain a robust economic performance

    To reduce Supply Chain costs, once the traditional levers have been activated (supplier negotiations, transport schemes optimization, inventory reduction, etc.), manufacturers have decided to go further by progressing on the notion of total cost. 

    The following summarizes some best practices for deploying such an approach that extends beyond the automotive industry.

    The primary purpose of the total cost approach is to direct decision-making processes towards solutions that achieve a global optimum in the supply chain. Because of this systemic nature (opposed to function-based approaches), total cost is a fundamental concept of Supply Chain Management.

    It is calculated by realizing the sum of assumed costs directly or indirectly by each function and this, until the service of the final customer:

    SCHEMA 1: Simplified representation of the Supply Chain + cost/ function source

    The objective is to have the most exhaustive possible cost vision during its construction in order to measure the impacts (including those usually hidden) of a decision on all the functions of the chain.

    In sectors where the value chain is shaped by large, long-term programs (vehicle programs in the case of the automobile), this approach is used in particular to optimize the current models during the serial lifespan. The total cost must be able to overcome breakthrough ideas by neglecting impacts on a function cost if the overall result is beneficial.

    In the shorter cycle sectors (Consumer Product Goods, various industries), the approach is mainly used to: (i) build the right model at the start of production by supporting Make or Buy trade-offs, (ii) facilitate and optimize allocation decisions between logistics flow schema for each new product launch.

    Recurring examples

    By constructing the cost structure of the automotive supply chain, it quickly becomes clear that the weight of the upstream part, which consists mainly of transport from suppliers to factories, is substantial (around 40% of total logistics costs). The main driver of cost reduction, the improvement of the trucks/containers filling rate requires the implementation of transverse reflections such as total cost, in order to achieve solutions that are disruptive compared to the current models:

    Supply-Transport arbitration:

    Car manufacturers have all gone very far in terms of batch size in their various applications of Toyota’s precepts (see the concept of One Piece flow). However small lots have a double negative effect. On the one hand they no longer allow to optimize loadings (cost/m³ penalized accordingly).

    On the other hand, they contribute to the frequencies increase and thus to the multiplication of journeys. The positive impact on the stock levels of the production units is, in this case, erased by the additional costs assumed by the transport function.

    In this case, the use of the total cost makes it possible to dissociate (i) the high-value parts that have to be delivered on a daily basis in order to minimize their weight in the inventory (this gain covers the additional cost of transport induced) (ii).
    The others parts that will be massified in transport at reduced frequencies (weekly if possible) to optimize loading rates (the gains largely covering here the differential on the storage cost).

    Piece – transport manufacturing arbitration (design to logistics):

    Still too little measured concretely in the industrial world but clearly identified at the operational level, the impact of the design phase on the logistics processes is an important subject to sift through total cost. Steering columns or exhaust lines are striking automotive examples. For pieces combining size and design complexity, the question of sub-component cutting (inducing an internal pre-assembly) must be systematically laid down on the basis of the different costs to be assumed.

    It enables to dissociate (i) Pieces that make a relatively short journey in terms of km and / or that require a very complex assembly process or not mastered internally, these parts to be supplied by finished sets (ii) Pieces costly in transport (according to kms traveled and packaged volumes) and whose cost of internal pre-assembly is competitive, these pieces needed to be conversely decomposed into sub-assemblies during the design.

    The idea of such a division is to be able to densify items within the same packaging and therefore to improve the cost/m³ ratio of transported goods; up to 30% in the case of steering columns or exhaust systems.

    In other sectors, the exercise can be done around trade-offs between Marketing and Logistics functions, for example. In distribution, the total cost analysis of the ready-to-sell packaging on low cost ranges is not yet widespread while it poses interesting conclusions. These packaging, originally designed to reduce racking time, are very unstable to handle during all upstream stages and suffer from a markdown rate 4 to 5 times higher than warehouses level, thus penalizing the final cost customer rendering. On the other hand, on premium ranges for which the packaging is designed to be resistant, the loans to be sold can generate real savings and improve the customer experience.

    Implementation keys

    The transversality of the approach and the need to decide on a global optimum in break with the established scheme necessarily induces friction between trades still operating too much in a silos logic.

    Here are main principles adopted by the builders to complete the process:

    #1 Make the dashboards consistent

    Creating a total cost global objective that is common to the different functions and aligning each one’s objectives limit the blockages associated to diverging indicators and reduces the tension subjects.

    #2 Adapt the organization 

    The establishment of a steering unit of the topic of total cost at the general management level and the appointment of referents in each profession is a prerequisite to ensure effective project management. This one must promote the identification and implementation of concrete opportunities in the supply chain.

    #3 Define an arbitration body 

    The appointment of a top manager with the final decision-making power in case of blockage avoids having to recourse to the management committee continuously to decide. This decision-making power can even be given to the factory manager who is not only in charge of his productivity but also of the complete value chain of his vehicle.

    #4 Develop the actors supply chain maturity

    The work basis, the training and the communication allow the operational ones to understand the direction that one gives to the use of the total cost tool.

    Good reflexes

    Moving forward with the total cost issues requires the ability to compile a large amount of data in a structured way and then use it to trigger arbitration.

    For this, it is necessary to:

    #1 Structure cost models

    If a good knowledge of all the applicable costs for each process is a good starting point, the goal must be to structure quickly generic cost models reproducing the different existing options and the total cost associated.

    This point has already been developed by manufacturers but is also found in sectors such as large retailers under the name of rating grids. These ones enable to make a choice of logistic diagrams by comparing different possible scenarios. The first step in this case is to frame the potential channels (import, domestic stored, domestic cross dock, domestic direct for example) and the processes that they involve. The Supply Chain function saves the costs of each stage in parallel in the grid, with a particular focus on the processes known in advance for criticality and/or recurrence (typical example: what is the real cost of non-palletising the goods on import flows?).

    The purpose of such a grid is to be able to automate and optimize the allocation of each new product in this or that sector according to the cost of the customer.

    #2 Facilitate Arbitration

    Extracting key data and presenting it in a synthetic form is the best way to create buy-in around a change scenario. On the batch size issues in the automotive sector, a summary vision of the stocks by supplier and the delivery frequencies used is a good example of an inventory comparing the production and transport trades:

    SCHEMA 2 : Inventory vs frequency graph

    ​Behind the arbitration process, the use of decision matrices makes it possible to clearly share and validate main rules to be used to revise the management methods:

    SCHEMA 3 : Volume delivery matrix vs pieces value

    ​In the automotive sector, the introduction of this approach has already been proven to significantly reduce upstream logistics costs and thus improve the operating margin. It makes it possible to put on the table innovative scenarios of cost reduction by basing the final arbitration on the gain generated globally for the manufacturer.

    This approach is starting to be deployed in other industrial and distribution sectors with real opportunities into the bargain. It requires setting up robust tools, adopting new management systems, and finally driving change within the company through targeted training and communication actions. For this, it must be the subject of a business project conducted by a dedicated team supported by the General Management.

    Sourcing Offices: a shift of paradigm

    Over last decade, sourcing offices became a major piece within globalized footprint of western retailers. Asian countries and China in particular have been privileged destinations for those entities due to cost attractiveness of the area.

    After a first era of development and opportunity catch up particularly positive and characterized by consistent purchasing gains, most of these Sourcing Offices are now searching for their second breath.

    Being caught between suppliers raising progressively their prices to follow cost pace (labor, utilities, quality costs…) and internal counterparts expecting more value (purchasing gains, flexibility, services…) they need to redefine and strengthen their model.

    A growing demand for added value

    Back to the origins, the Sourcing Offices have been developed by retailers for two main reasons:

    #1 Gather demands coming from various entities within a same group

    Retail groups are by nature associations of small entities (stores / country grouping / store brands) that in isolation are facing difficulties to reach economies of scale in purchasing task. Once pooled through a Sourcing Office, they can get a higher power of negotiation.

    #2 Set up localized resources

    Dealing on a daily basis with distant and unknown sourcing markets is a real challenge from supplier identification and qualification to order processing and shipment arrangement. A localized Sourcing Office helps tackle the cultural differences and handle process with knowledge of local constraints.

    Consequence of this position, Sourcing Offices have always been at the crossroad of two worlds presenting different expectations, timelines and constraints. They need to match the need of volume / visibility / stability of suppliers with the need of pricing / flexibility / reactivity of internal counterparts. And current trend shows that each of these needs even tends to be reinforced.

    In parallel, Sourcing Offices progressively became a center of services and they integrate functions not directly related to sourcing operations such as Supply Chain, Design or Packaging. Buyer’s product selection is going toward less item picking (what supplier already has in his catalog) and more product development allowing to better customize products in function of the destination markets. It makes Sourcing Office job a more complex job within a more complex environment.

    Process set up: streamline tasks

    Three kinds of actions are necessary to rework processes

    #1 Streamline the processes

    A quick process mapping exercise shows that support functions can carry until one third of Non Value Added Operation and one other third of “Waste” operations. Sourcing offices are not an exception and existing waitings, overlaps, reworks are damaging the performance. It artificially grows workload of teams that tend to sacrifice the Value Added tasks as Supplier and Product sourcing.

    On this axis everything starts with Value Added definition by teams, what do the clients expect? What are they ready to pay for? Once this defined, the streamlining exercise will aim to map and progressively improve / eliminate all tasks not contributing to create value added for clients. It’s the occasion to redefine for each process the operating standards and expected outputs.

    #2 Structure advanced toolsets

    As demand for high value added service raised, Sourcing Offices frequently demonstrate a cruel lack of methodologies for key structuring activities. Job Description as defined today in Sourcing Offices are limited to daily commercial execution (supplier integration, product development and qualification, order processing…). Strategic actions like Purchasing Strategy definition or Negotiation preparation are not correctly documented.

    It requires, while working on operating standards, to create standard approaches and templates for strategic processes.

    As an exemple on Purchasing Strategy axis, it means provide an analysis structure / template that will be used by each category to set up a mid term vision and an action plan aiming to reach this vision. On Negotiation preparation, best practices show that having a standard blusheet per supplier centralizing key figures (turnover, rebates, item price evolution vs cost index evolution…) helps buyers to be better prepared for negotiation rounds.

    #3 Link processes & tools to organization

    Last point in the inventory, the tools are most of the time not adapted to the needs of teams and are not giving the right vision for people to monitor their activity. Information Sytems are not covering the entire value chain, standard KPIs and dashboards are missing, and sometimes several Information Systems co exist without being connected to share information.

    No mystery on that point, solution is coming from Information System itself, several solutions are already proposing a End to End Management of information and physical flow. On top of a transversal cover, capacity of the system to deliver tailored and visual dashboards is also part of ideal solution.

    Organization set up: develop the 360° vision

    Organization is a key component of sourcing office performance, it requires to put the right level of skill and experience in front of each task and each interlocutor.

    A lack of maturity in organization will end in a general disorder where Commercial team (merchandiser, product manager, department manager…) tend to monopolize conversations with each side of the business for each topic assessed (Quality, Supply Chain…). It’s also frequent to see overlaps between commercial team members.

    There are three kinds of actions to carry in order to work on this axis

    #1 Refine the Commercial team Roles & Responsibilities

    Commercial team (merchandiser, product managers…) is central for a sourcing office, it’s the team in charge of settling and rolling out the sourcing strategy (suppliers / products) by matching internal client expectations with market offer.

    Within the commercial hierarchy itself, it’s important to separate strategic tasks and operational tasks to ensure that higher level of hierarchy will dedicate time to strategic topics and stop overlapping other levels on operational topics.

    #2 Position operational functions as key actors of performance

    Operational teams (Quality and Supply Chain firstly) are essential to carry on the business and deliver value added services to internal clients.

    Position them as key interlocutors on each of their topic will secure the output per topic (product qualified, delivery on time…) and avoid overlaps with commercial team.

    #3 Structure transversal relationships

    To guarantee the good execution
    of processes and secure the delivery of expected performance, communication within organization is vital. To give a framework and force teams with various objectives to work together toward a common goal, matrix management can be relevant.

    One referent is nominated per function in order to monitor on daily/weekly basis with referents of other teams the achievement of key milestones (product selected, product qualified, order validated, production launched…).

    Working on organization through these 3 axis will push the need for standardized R&R. This is where RACI definition exercise (Responsible, Accountable, Contributor, Informed) becomes important, it will clarify Roles and Responsibilities newly define through waste hunting workshops.

    In terms of management, we can’t let rooms for interpretation. Management routines, animation principles are often viewed as well-known topics but there execution suffers from a lack of definition and of discipline from Managers. They need to be part of new standard definition, with pre defined owners, frequency and expected outputs.

    Upstream set up: Educate the suppliers

    Process streamlining and organizational alignment is not only reserved for inner Supply Chains. The development of counterparts’ maturity is a natural and essential step along retailer’s Supply Chain reinforcement. Tier one suppliers are one of first focus to have in this approach.

    Maintain an accurate knowledge on supplier’s strengths and capacities, align his processes with internal requirements, face the right interlocutors for each function (Commercial / Quality / Supply chain), here are the basics to put under control upstream channel.

    Obviously it also involves having regular check points around pre-defined dashboards and KPIs in order to get a live vision of execution advancement.

    To secure sustainable purchasing gains and sustainable quality level with the biggest and most strategic suppliers it also becomes common to launch supplier development programs. It involves for Sourcing offices the nomination of dedicated resources specialized in Operational Excellence that spend time on supplier‘s site and help him to improve its overall productivity through Lean workshops.

    Downstream set up: Educate the internal customers

    Today, there is no standard sourcing organization, each retailer has developed his own approach with various level of centralization leading to various degrees of penetration of Sourcing Offices within everyday business (penetration represents the ratio of business handled by Sourcing Office among total purchasing amount for a group).

    Fully aligned organizations position Sourcing Offices at the heart of their strategic plan, working on product development and costing, being responsible of quality delivered, acting as an unavoidable service center to deal with upstream actors. They are not necessarily covering the entire portfolio but on a set of pre-defined strategic categories (best sellers, non-food categories, commodities…) they have the prerogative.


       In Europe Ikea, Decathlon or Zara are well known examples of fully aligned organization. Business Model is reflected in       the entire value chain that is oriented toward cost optimization and ability to focus on value expected by clients. We talk    about bridging operation cost constraints and client experience through design approach for Ikea, developing a strong         internal alignment around development and merchandising of own brands for Decathlon, working on time to market           reduction with each function to propose faster collections for Zara.

    Aside of these word class organizations, other retailers are mixing approaches allowing entities (or grouping of entities) to deal directly with suppliers while developing their own resources in a structured Sourcing Office.

    The more aligned you are at group level, the less bias you open for daily execution of sourcing tasks by the internal customers. It leads to a systematic volume pooling and the more volume you give to your Sourcing Office, the more value they will be able to bring back to you. It’s Key Success Factor to strengthen Sourcing Offices and give them the best condition to develop their potential.

    In few bullets points we saw the preconized focuses for Sourcing Offices in 2017, if industrial purchasing is still fare considering the BtoC market constraints, it’s still a good ideal to chase, several best practices are easily reachable. The existing gaps in management mindset, in organization maturity and in tools & processes alignment can be closed and need to be closed in order to keep positioning Sourcing Offices as performance contributors.

    Lead suppliers to win with you – The importance of supplier development

    Every company’s business model should be to win by delivering valued, quality products, services and solutions to customers that provide the lowest total owning and operating life cycle costs. This business model begins and ends with the customer. To execute this business model, it is important to develop and sustain a supply base that is an integral part of the extended supply chain, and that can provide the right part, to the right place, at the right time, at the right quantity, at the right quality every single time.

    Today’s business environment is characterized by:

    • Increased supply chain complexity
    • Need for integrated supplier relationships
    • Limited internal resources, need for flexibility
    • Increasing competition and need for innovation
    • KPI driven and siloed working environment
    • Ever more demanding market

    For businesses to reinvigorate their customer focus and transition from a finite business player mindset to an infinite business player mindset they need to embrace integrally their supplier base. The suppliers-customer relationships constitute a system that will optimize its performance when all involved work for maximizing the performance of it, sharing resources, trusting one another, and truly collaborating to always be there for the end customer.

    All is much easier said than done, and never happens over night!

    Businesses have been deploying supplier development programs for decades, as well as deploying lean initiatives, trying hard to truly embrace continuous improvement, but have constantly been failing. The reason is that all these initiatives were developed in a silo either within the four walls of the business itself, or just within one of its function/departments, involving only marginally at any given point the supplier base. Another reason for failure is that such initiatives would all be centered around selected KPIs, driven by one symbol “$”, causing conflicts when definition of such KPIs or their targets is not in alignment with other business performance indicators in the business or at any supplier.

    Without truly addressing the cultural implication of creating real partnerships, without having visionary leadership that grasps the long-term implications, without formulating a strategy that targets a true change in the way supplier-customer relationships are thought, developed, and measured anyone of the initiatives will continue to fail.

    Supplier price concession contribution (shortest bar) is only a fraction of the total supplier contribution to OEM profits. When added to the supplier non-price contribution (third bar from left) the total exceeds the OEM’s managerial contribution (fourth bar) to OEM profits. (PRNewsFoto/Planning Perspectives, Inc.)

    Supplier Monozukuri is a new way to approach supplier development, converting it to a supplier integration and cross functional effort that extends the benefits captured optimizing the supply chain end to end.

    ​Supplier Monozukuri is created by using 3 pillars:

    Nine Monozukuri Levers

    A Robust Process

    Change Management

    The above Monozukuri Pillars do not sustain themselves, and require 3 Supplier Monozukuri enabling factors:

    1. ​Validated tools & techniques
    2. Aligned KPIs, targets, and objectives
    3. Company Culture

    Communicating properly the Supplier Monozukuri vision across the supply chain creates the momentum required to establish the Supplier Monozukuri enabling factors, and deploy the three pillars across the supply chain. Businesses should not underestimate the time and effort required to define and communicate the Supplier Monozukuri vision statement, this with in all effect trigger the transition from finite to infinite business mindset.

    To then sustain Supplier Monozukuri a business does not require as many resources as those needed to establish it. Once the Supplier Monozukuri engine is oiled and running a perpetual collection of benefits is captured by the system, truly accomplishing continuous improvement within the end to end supply chain, and extending ultimately to the end customer.

    ​The outcomes of Supplier Monozukuri are not to be measured by the success or shortfalls of this or that KPI at any given time, but by the way the system reacts to any shortfall, understanding the true long-term impact to the end customer, and working as true partners.

    Whichever challenge you may be facing, facing it together with your business partners (strategic suppliers) will give the competitive advantage you need, and will provide a role model for change management that each element of the system will look up to, driving a deeper cultural change, and perpetuating benefits for each company involved!

    Algorithms and Artificial Intelligence: New Horizons for Cost Estimation and Modeling?

    The progress made in the last 20 years in the field of statistics have made it possible to develop predictive algorithms that are much more efficient, especially in terms of precision. What are the possible applications in the field of cost estimation and modeling? While traditional analytical models based on the manufacturing processes of the product or service are still widely used in our Cartesian society, statistical models are gradually imposing themselves to their formidable efficiency. But rather than an opposition, these two methods are enriched and complement each other.

    Traditional costing models

    As a reminder, there are now 3 main methods used to estimate the cost of a product:


    The analogical method

    This method estimates the cost of a new product compared to similar products produced or purchased in the past. This method is unreliable, but can be used in extremely upstream phases (study of opportunity) when the characteristics of the project or the service are not yet known. We will not detail this type of basic estimate in this article.


    The analytical method

    It estimates the cost of a product by modeling the industrial production process. This method is based on the cost structure of the product of which it estimates each intermediate element, based on the materials & components involved, process costs (machine and labor), and related structural costs. This method has several advantages:

    • It allows to estimate an optimized and theoretical cost of production by modeling a virtual factory on the basis of the best ratio (labor cost, TRS, Scraps, …).
    • It allows to give an ambitious cost target and to identify the “Best Landed Cost” for a given product.
    • It also makes it possible to identify in a concrete way the sources of non-performance of the suppliers (on which process step, which cost item, which indicator …) and to engage with them a continuous improvement process to capture productivity.
    • This method is therefore particularly useful in the downstream phases of the life cycle (production, continuous improvement, product redesign, etc.).

    However, the analytical method has some disadvantages or constraints to its implementation:

    • It requires a good understanding of the manufacturing processes involved as well as key parameters (TRS, Scraps, cycle time …). So much information is not always easy to collect and capitalize with suppliers.
    • The determination of the “Best Landed Cost” requires feeding these tools with benchmark data on production parameters, and keeping these benchmarks up to date.
    • If the standard processes can be modeled more or less quickly (injection, extrusion, casting, cutting, striking, surface treatment …), the encryption of a complex product is often tedious. It requires a specialized expertise that only a few people master in the company…
    • As a result, encryption cells quickly experience bottlenecks, with processing delays incompatible with agile development and time-to-market constraints.
    • Finally, if these models have a real relevance to give cost targets, they often lack precision, because they do not take into account the hazards or certain external factors (balance of power, market effects, …) especially since many suppliers have a very low level of maturity on the control of their industrial cost price (PRI).

    Existing software solutions on the market address some of these problems by offering in particular integrated benchmarks on several manufacturing processes with benchmark data per country. Some editors have also developed interfaces that provide CAD file reading, which allows automating the proposal of manufacturing processes (virtual factory). However, these kinds of software remain heavy and long to set up and are used only by a few experts.


    The parametric method

    This method estimates the cost of a product or service by statistical modeling. This method uses similar product or service histories to define equations or statistical laws that allow to model the evolution of the cost according to certain parameters known as “cost drivers”. These models are mostly based on linear, multilinear, polynomial or logarithmic regressions. These estimation methods have several advantages:

    • They make it possible to estimate the cost of a new product / service based on simple and known characteristics of the company (weight, size, volumes, country of production, key elements of the specification …) without necessarily knowing the details of the manufacturing process or external benchmarks. It is therefore a very quick and simple method to implement.
    • On the other hand, based on the observation of products / services actually manufactured or purchased in the past, the estimated cost is potentially more consistent and precise than a “theoretical” analytical model, provided that there is sufficient quality history.
    • These statistical methods are particularly useful in the early phases of life cycle (opportunity, feasibility, detailed design …) because they make it possible to make the right decisions quickly for an optimized design and thus to secure the margin while accelerating the “time to market “.
    • Further downstream, they also make it possible to quickly analyze the consistency or the inconsistencies in the current prices, thanks to the dispersion analyses with respect to the predictive model. Thus, they reveal aberrant products or services, at an abnormally high cost, for example, with regard to the predictive model. This gives optimization leads for buyers (renegotiation, change of supplier) or for R & D (redesign).

    On the other hand, these methods have several limitations:

    • Traditional statistical models (based on regressions) hardly take into account the qualitative parameters (except to reduce the size of the database).
    • They do not manage properly the missing data and therefore, require very clean databases.
    • They mismanage “breaks” or threshold effects. For example, the price can have a linear behavior over a certain range, then a radically different behavior from a certain threshold (size, weight, volume …) because the manufacturing process can change.
    • All these elements directly affect the accuracy of traditional parametric models and therefore their use.

    Artificial Intelligence paves the way for a fourth model of cost modeling

    The advances made in algorithmic and machine learning in recent years largely solve the disadvantages of traditional parametric methods and improve their performance and their field of application.

    Among the recent statistical methods, the random forest algorithm, formally proposed in 2001 by Leo Breiman and Adèle Cutler (Breiman, L., Random Forests, Machine Learning, 45, 5-32 (2001) is a non-parametric approach that performs learning on multiple decision trees driven on slightly different subsets of data generated by Bootstrap techniques.

    1/ What are the advantages?

    The main advantages of this artificial intelligence algorithm are:

    • Ability to model a very large number of parameters (“cost drivers”) and particularly qualitative or “symbolic” parameters
    • Ability to process databases where the number of variables largely exceeds the number of observations
    • Ability to identify and weight automatically the most important parameters, and thus the “cost drivers” that impact most the cost of the product
    • Ability to manage missing values / incomplete databases
    • Robustness to outliers
    • Ability to identify behavioral breaks in variables
    • Interpretation of the tree
    • Precision increased by 30 to 40% compared to traditional methods

    2/ What are the applications?

    The applications of these algorithms are numerous, especially in the medical, insurance, marketing targeting (with uplift methods).

    The application of random forests in the field of cost estimation solves many of the disadvantages of traditional parametric approaches and opens to new opportunities for companies interested in efficiency and competitiveness.

    A precise estimate of costs is now possible, even with a limited number of observations (a few dozen), limiting the resources used to collect and capitalize the data. On the other hand, the price of complex systems can be modeled from easily accessible functional cost drivers, making encryption particularly simple and fast. Thus, for an equipment manufacturer, we were able to model the cost of an air conditioning system almost exclusively from functional or environmental parameters such as the volume to be air-conditioned, the number of openings, the time required to reach the target temperature, etc.

    For this reason, random forests have begun to be used by some companies in the early phases of the product life cycle, including:

    • Gain productivity on their encryption activities (saving time and resources that they can focus on technological innovation figures)
    • Respond more quickly to their clients’ tenders and especially use this time saving to better optimize their proposal
    • Secure and optimize their margin on new business

    It is not surprising that the first users were sectors with strong encryption and product development activities (automotive, capital goods, consumer goods, etc.).

    The second step was to use these algorithms to perform consistency or price inconsistency analyzes by identifying products with large discrepancies between the actual price and the estimated price. The explanatory properties of random forests (classification with similar products) make it possible to argue with suppliers during negotiations and thus to generate savings in purchases.

    Finally, once the model is perfectly calibrated, it becomes a cost control tool to validate the fair price offered by the supplier. This reduces the bargaining process.

    3/ What are the opportunities?

    The opportunities offered by random forests in the field of cost estimation and optimization are therefore enormous and far from being fully exploited. Beyond cost optimization, the self-learning of the algorithm on the data of companies and their suppliers makes it possible to consider intelligent contributions such as the automatic preparation of negotiations (objectives, levers arguments …), the proposing optimized designs or redesigns, recommending the most adapted purchasing strategies anticipating supplier behavior …

    In conclusion, the 2 approaches are complementary in their use:




    of software

    Analytical Model

    • Explanatory and operations- centered model
    • “Best Landed Cost” Estimation and Target Price Definition
    • Allows to optimize the prices in production and to control the plans of progresses suppliers
    • Difficulty accessing process references and maintaining them over time
    • Intrusive approach towards suppliers
    • Expert model with little diffuse
    • Timeout for setting and performing encryption
    • Precision ?
    • Siemens PLM
    • A Priori
    • Facton

    Statistical Parametric Model

    • Easy and quick to use
    • Estimated price coherence, and accuracy (conditional)
    • Non-intrusive approach to suppliers
    • Product and service applications
    • Very relevant in the upstream phases of the life cycle and for the analyses of coherence
    • Requires minimal data and quality history
    • Model that is not very “explanatory” to moderate supplier progress plans
    • Less relevant model for setting target prices and “Best Landed Cost”
    • Difficulty in modeling qualitative parameters
    •  Seer
    • EstimFEC

    Non-Parametric Statistical Model

    « Random Forests »

    • Easy and quick to use
    • Consistency of the estimated price, and precision increased by 30% compared to parametric models (conditional)
    • Non-intrusive approach to suppliers
    • Product and service applications
    • Very relevant in the upstream phases of the life cycle
    • Relevant also in the downstream phases for the analysis of price coherences and the identification of opportunities thanks to the explanatory properties of the forests
    • Integrates a lot of cost drivers, including qualitative ones
    • Detects technological breakthroughs
    • Prioritizes cost drivers
    • Manages missing values and can work with a limited sample
    • Model less relevant for setting target prices and “Best Landed Cost”
    • easyKost


    In conclusion, it would be futile to oppose the analytical and statistical methods of cost estimation. They complement each other in their use and purpose. The statistical method, which is more consistent because it is based on the observation of the actual data, makes it possible to obtain a rapid and precise evaluation to make the right decisions in the product design or redesign processes. Simple to implement, it allows to model many families of products and services in a non-intrusive way and without needing to acquire an advanced technological expertise. The analytical method allows to obtain an encryption precisely reflecting the reality (or the simulation) of a manufacturing process. More tedious to implement, on the other hand it allows to define targets of cost to be reached with explanatory factors based on the observed industrial parameters and benchmarks. In this sense, it is more appropriate to quantify technological breakthroughs and to lead industrial suppliers’ progress plans to bring them to the target. It is also more relevant to quantify technological innovations on which the company does not have a history.

    Nevertheless, self-learning algorithms and deep learning open new horizons and fields of application for the use of statistical models, notably through the sharing of information between companies or between them and their suppliers.

    Do’s and Don’ts of International Operations Development













    In conclusion, integrate the operations early in your decision!

    Supply Chain in retail: prioritizing the shelf

    For fifteen years, information systems have taken a leading role in the management of flows: ERP communication and collaborative approaches between manufacturers and retailers (SSM and now GPFR) have become the industry standard. Even better, stocks are now controlled on the basis of actual consumption (VMI), completely relieving the sales areas of responsibility of supplies. Yet despite all these developments and associated investments, the Out Of Stock (OOS) rate recorded on shelf stock barely drop below 8%. Are we facing a structural OOS rate? Can we go further to improve the product availability? Traditional retailers are asking the question more than ever at a time when, to deal with increased competition from online distribution, the answers are to provide a wide range of products with immediate availability.

    In 2011, a study by the ECR concluded that the average rate of actual product availability in large retailers was less than 90%. This figure surprised many France no exception. Studies conducted in the United States have come to similar conclusions, averaging 8% OOS on shelf (Corsten and Gruen 2003). Even more astonishing, this figure varies very little when you factor is investments for tools and technology. In 2008, a report commissioned by the Coca-Cola Company reported an OOS of 8 to 9% … the same rate that had been recorded 12 years earlier.

    Remobilizing Store Teams on Supply Chain Issues

    We are very far from the service rate known in the industry, in the warehouses of the same retailers that show an average 99% of product availability. How do we explain and reduce this gap?

    The first challenge is to align Supply Chain and Sales with this finding. Indeed, when we ask store managers about their product availability level, they typically announce figures that are far removed from the reality on the shelves. The OOS rate is usually underestimated, and even more the loss of associated revenue because store managers are assuming sales will almost systematically be captured by other products. A survey conducted by Danone showed that in nearly half of cases, the client preferred to do without the product or buy it via a competing brand. In defense of store managers, few Supply Chain reporting guidelines incorporate this concept of “On-Shelf Availability”. Indicators often only cover the platform availability and delivery lead time in store. But what about the actual customer service? If one agrees that the role of Supply Chain is to deliver the right product, at the right time, in the right place, the performance indicators should focus on the one place where the goods are really needed — the shelf. Yet OSA (“On-Shelf Availability”) is an indicator rarely included in the Supply Chain vocabulary for retail.

    Failing to be measured by the Central Supply Chain, OOS products in stores are often relegated to (anecdotal) field surveys performed by the sales teams. This process, which has the merit to exist, however, has two major limitations:


    It is not possible to calculate the real OOS rate of the store, for the following reasons:

    • These relatively time-consuming surveys cannot be conducted on 100% of the store’s inventory.
    • Made at a predefined frequency, it gives only a static view of OSS but does not allow you to understand the duration (or circumstances) between each review.
    • Finally, usually performed in the morning, at off-peak time rush and often just after replenishment, they cannot be considered reliable. Client traffic usually follows a “camel hump” curve (see illustration below), with increased traffic in the late afternoon. Thus, OOS products in the afternoon potentially represent a higher loss of turnover figures for distributors than those identified (and corrected) during the morning.

    The second major limitation we see is that these OOS surveys are undermanaged and underutilized.

    During this operation, the store employee will strive to optimize the presentation of the shelves, and potentially to verify the presence of the product in the storage area. With our clients, we work with operational teams on the development of a simple diagnosis & resolution tool to help them utilize the information system to localize the goods. From there, we can easily understand and deal with the root cause of OOS products. This analyses often concludes that the central supply-chain is responsible for many of the failures.

    Build a Field Action Plan

    Empirically, it is found that 50 to 60% of OOS on-shelf depend directly on store operations, the remaining portion being connected to the upstream supply chain (suppliers / platform failures).

    Among the errors attributable to the stores, listed are those which occur most frequently and which must be better managed:

    • The theoretical stock is wrong, thereby preventing replenishment triggers
    • The quantity on shelf is not properly aligned / set-up (facing and depth)
    • And finally, a well-worn subject but that still represents a potential improvement for retailers, the product is in the storage area but it did not make it to the shelf.

    This year we worked with a chain of hypermarkets where stores complained of a malfunction in their automatic ordering system. The conclusions of the on the ground analysis confirmed this rule (see below the summary of the causes of observed failures):

    It’s a fact: products often travel thousands of kilometers without any problem, to then get lost in the last meters in-store. The goods and information flows are under control until they enter the storage area – which is where store organization needs to take over.

    • What Operational Solutions can be Undertook to Avoid these Problems in Stores?

    Some retailers, with the support of manufacturers, develop tools to encompass the shelf in their global vision of supply flows. RFID is the most acclaimed. A survey conducted in October 2015 with professional retailers confirmed that 63% of interviewed companies were investigating RFID as a solution or already deploying it as a solution. However today, the solution is deployed in only 6% of organizations … So from here to have an RFID chip on every product, what we do?

    It would be unrealistic to base the improvement of customer service only on the technology. For example, electronic tags that incorporate logistical information (available stock, work in progress…) have not had a significant impact on product availability. While access to information is faster, it’s utilization is still necessary in order to know how to use it more effectively.

    It is therefore necessary to work with operational teams to develop an efficient information processing system.

    Two main areas need to be analyzed:

    • Review the Process
    • Strengthen the Managerial Control

    Goods receiving, shelves replenishment and more generally operations planning in stores

    The storage area often resembles a ‘black box’, which generates either overstock or out of stock products. It is essential to redesign how this area is organized into a transit area instead of a storage area. The reconfiguration of the storage area is often a prerequisite to optimize the replenishment process and the activity management. Whether the store has dedicated replenishment teams or mobilize their sales staff during off-peak hours, the challenge remains the same — ensure that the information and goods efficiently circulate between the storage and the sales area.

    Change Competencies in the Retail Sector

    In terms of optimizing the supply chain, we can only welcome the development of technologies that allow a transversal and centralized management of supply flows. However, these tools should not limit the responsibilities of the section manager but instead, allow him to position himself on higher value added activities. The release time on order placement (what, how, when?) must be reallocated to stock calibration and the global flow management during the last meters of flow.

    Any technological change, as it enters the supply chain of retail companies, must be accompanied by a change of roles & competencies. In the retail sector, the explosion of the offer (range width multiplied by an average of 2 of the last 15 years) and the pressure on costs create many challenges for an organization. The shelf is not only a place to showcase products for sales, but is also a storage space. The roles and competencies of sales teams must evolve accordingly and retailers must adapt their organization to this transformation.

    Supply Chain Management: is Blockchain the new RFID ?

    It has been hard lately to work on Supply Chain Management topics without hearing a word about Blockchain technology and all the potential progresses it carries. For people involved in our field it can sometimes sounds as an echo of what happened with RFID technology.

    Back in the days, around 2006, Supply Chain world was shivering with the booming of RFID application (Radio Frequency IDentification). From a technology appeared at mid-20th century, the actors of technological appliance development started to create a universal tracking system able to make Supply Chains walk fully into the world 2.0.

    RFID: from hot topic approach to pragmatism

    Every sector of the market, every actor in the chain, every function in the company would use RFID to improve the logistics performance (right product, right price, right quantity, right quality, right place and right time). And due to an obvious need for product traceability and information chain mastering, it has reached the interest of most of the actors.

    Professional fairs and professional press were heavily passing the information around through conferences, round tables and articles. The limit of these exercises was the clear fact that tangible examples of technology application (I mean with revolutionary changes in terms of performance) could be counted on the finger of the hands. Later on, we would also discover that RFID usage touches its limits when the technology is entering the private sphere, enabling to track more than just marmalade pot until the door of the shop.

    With hindsight, we can say that no revolution occurred, printed barcode is still the top 1 mean to track and trace products in the Supply Chain; the announced wave has been localized. Facing a more mature technology, we can say that it has been a huge added value for some sectors having identified needs and constraints. Garment retail, high value sub components in industry, handling means tracking (pallets, reusable trays…), these are a few models of successful application.

    Blockchain: you don’t master Supply Chain 1.0, try Supply Chain 4.0!

    10 years later, RFID is not anymore a hot topic and new concepts appeared that feed the expert debates. On technological axis, the main one is related to Block Chain late development and it sticks with the major stakes existing around Big Data mastering. Started from a need for money transaction the Blockchain protocol is opening a large window for other application areas.

    The two main advantages already identifiable are: 1/ the high level of security offered and 2/ the ability to spread data processing between many devices (instead of using one huge, costy and sensible server). Each device involved in the chain is requested to store a small portion of information and counter check the authenticity of data stored by its peers. This kind of protocol is essential to secure financial transaction and this was the starting point for Bitcoin that developed the protocol.

    Time passing, we are hearing more and more experts saying that there is no border to this technology and that it can be used everywhere. I was recently attending the Supply Chain Event in Paris and Blockchain was a key concern with one entire morning of conferences dedicated.

    As Supply Chain Management is entering in the 4.0 era, the Blockchain is an ideal topic to be launched in the air. But as for RFID sooner, no example of concrete roll out is available today for our jobs (warehousing, transportation, order processing…).

    It wouldn’t be a problem if Supply Chains were already mature on 2.0 and 3.0 axis (do you know the difference between these two ?). 90% of Supply Chain Managers are currently fighting in their daily operations to apply basics of organizational efficiency. As far as the concept creation can go, and as much as it feeds experts’ lives, companies are still struggling to structure and make work together key logistics processes for tomorrow.

    We can easily guess that Blockchain will be a concrete progress for some particular operations, basically each time a Supply Chain deals with external counter parts (not only for financial transaction). But it’s not at the heart of problematics as long as basic Supply Chain Management remains a myth (a statement that I’ll develop in another article).

    8 tips for a successful supplier development program in China

    For the last 5 years the labor cost has kept increasing in China at a huge pace as the manufacturing labor cost has more than doubled from 1.15 EUR/hour in 2009 to 2.6 EUR/hour in 2014. Moreover, the exchange rate dropped from 9.59 to 8.18 CNY/EUR for the same period and today reaching 7.30, that is to say an increase of 24% for “made in China” products. Most of the cost driving factors have the same trends leading to the overall impact of decreasing gradually China’s cost advantage.

    Most of the local but also foreign suppliers have no other choice than to increase pressure on their production and supply chain organizations to maintain a competitive cost and retain customers. However, shortcoming savings of Chinese suppliers equals frequently to a proportional increase of the risk of business discontinuity. As an example, it affects manpower retention, competencies, or even worst it leads to strikes. The number of strikes has doubled in China in 2014 according to the China Labor Bulletin NGO.

    Many manufacturers tend to solve those issues by investing in expensive equipment and robots, whereas the capital invested can be largely saved with a proper and structured approach. Another well-known problem in China is to sustain quality and delivery in a very fast growth period; we see that the traditional way is to install more equipment to increase capacity instead of working on productivity and developing continuous improvement. This is rarely framed into a long term industrial plan.

    Why a supplier development program?

    A supplier development program is a collaborative project involving both client and supplier aiming to developing supplier performance in terms of quality, cost, delivery, time-to-market, management and environment, as well as innovation and financial performance.

    The establishment of a durable cooperation with suppliers is crucial in China as we observe a change of mindset. The development of Lean initiatives is expanding in China, even for small companies, as the increase of productivity moves from 40% to 60% in average in the 5 past years. But the lack of know-how and old believes, such as that supplier development is costly and time consuming, remain the main hurdles to switch from a firefighting mode to a win-win sustainable development.

    On another hand, the companies willing to develop their suppliers often think that the improvement will benefit to their competitors too and that the impact will be therefore diluted. The involvement of the team to understand their suppliers and to build up deep relationships, as described by Jeffrey Liker and Thomas Y. Choi in the Harvard Business Review, shows how essential this tactic for a long term business development and building the foundations of innovation is.

    Based on our experience, the implementation of a supplier development strategy can achieve significant performance improvement. We generally observe:

    • -5% to -50% of product defect
    • +6 to +90% of on-time delivery
    • +30 to +50% of order fulfillment cycle time
    • +5 to +10% of labor productivity
    • 4 to 8% of cost reduction

    These figures are based on our own observations but can vary widely depending on the industry and the maturity of the supplier and the product types.

    Our 8 tips to succeed in supplier development

    During the past 8 years of our presence in China, we have identified 8 key factors to lead successfully supplier development programs. They are not all specific to China but cultural specificities have to be addressed for a smooth and successful deployment.

    1) Define internally clear “development” initiatives which will support business strategy

    2) Dedicate time to select the right suppliers

    3) Inform suppliers in general and selected suppliers in particular

    4) Lead the project with the Supplier Quality Team

    5) Run on-field diagnosis to assess savings opportunities and confirm selection

    6) Put in place and suggest financial incentives at supplier’s

    7) Sign development contract with selected supplier

    8) Organize REX and strengthen communication


    A supplier development program is a long journey for both client and supplier teams to reach a common goal. It must be carefully prepared and planned to fit in supplier’s culture and maturity, and meet business expectations.

    The Supply Chain myth

    The Supply Chain topic has risen progressively from early 2000s to become an essential part of business approach today. Surprisingly it remained in parallel one of the foggiest topic for people within companies whatever the function they hold.

    Birth and story of a myth

    The development of Supply Chain theory started with the idea that each process in the value chain should be considered as a contributor of the performance delivered to the final client. The approach aims at digging into logistics processes (procurement, warehousing, transportation, kitting, reverse…), understanding their efficiency factors and adopting a systemic approach to establish strategic and operational links between them.

    The revolution around Information and Communication Technologies has supported the development of these interactions by facilitating the information brewing. Data mastering became strategic to drive the business and win competitive advantages, turning Information Systems into vital tools. Progressively they’ve been able to cover every Supply Chain process; we gave them acronym names (ERP, WMS, TMS…) and we stepped into the Supply Chain 2.0.

    Few years after, more technologies were developed (RFID, SaaS, APS, automatization, Drones, Block Chain…), more theories were defined (DDMRP, flowcasting, shared inventory management, omni channel distribution…); Supply Chain Management is for good a strategic component of companies’ performance.

    L'impact de la révolution technologique sur la Supply Chain

    Listening to experts, we should even be by now in the 4.0 era.

    The widening gap

    Looking at examples coming lately from western / historical retailers and OEMs, let’s have a doubt and let’s say that pragmatism is essential in front of the various level of maturity we can face in terms of Supply Chain Management.

    ​Retailers and OEMs cases are interesting as they both show the reality of problematics that Managers are facing, far from theorizing theories. First ones spent the last years searching for the good solution to address the needs of online market in front of pure players that still handle 99% of this limitless business. The second ones are facing more and more issues with delivery delays and capacity to align rank 1 (even rank 2) suppliers on expected deliverables (Quality / Cost / Lead Time).

    ​Everyday life is focused on very basic questions:

    • How to maintain competitiveness across all channels handled?
    • How to secure supplies while more and more items are coming from far shore countries?
    • How to handle high variations in demand?
    • How to stick to initial planning? 
    • How to drive the upstream chain and eradicate risks of shortage (even sometimes in link with financial issues at supplier side)?
    • How to deal with extreme customizations needed?

    As a consequence, having a conversation with a Supply Chain Manager these days is pretty interesting as they generally try to peck here and there for revolutionary solutions while revamping regularly the organization searching for the right formula. Drown in the profusion of concepts and tools, Managers tend to lose the essence of Supply Chain Management while everything starts with their ability to build and share a vision.

    The DNA shortage

    Standing out of the crowd, a couple of economic actors are showing a great ability to meet customer demand and create value based on the way they fit their organization. No mystery on that, every world class actor has bet on a Supply Chain entirely designed to make processes flexible and efficient, to speed up the flows and optimize resources needed.

    Apple, Decathlon, Dell, Ikea or Amazon, Intel, Mac Donald’s and Unilever (if we want 4 names sticking to the Gartner 2016 top 25 Supply Chain organizations), these are concrete examples of successful application of SCM.

    If you run opinion surveys, you’ll find that each of these companies have a strong and easily recognizable identity. They rely on identifiable models: Apple and its pioneer technologies, Ikea and its shopping environment, Dell and its customization offer, Decathlon and its positioning with reinforced own brands.

    Do you think it’s only Marketing? Have a second thought and you’ll see that all of these companies are relying on a strong and highly flexible logistic organization. Marketing model pull/align Supply Chain models, Apple and its inventory focus, Ikea and its design to cost approach, Dell and its online BtoB platform, Decathlon and its vertically integrated strategy.

    Supply Chain Management remains a myth as most of the companies are not even able to do this exercise of definition of their identity. They are not able to characterize a DNA, to create a vision around this DNA and to align every people within organization with this DNA.

    Best of breed entities are on top, thanks to their ability to run this exercise, to align operational processes on strategic vision, and we can see all the positive effects it has on their Supply Chain Management approach.

    L'importance de l'ADN pour créer sa vision autour

    Managers: Light! Camera! Action!

    Then converting a corporate identity into operational application is THE job of Supply Chain Manager. He has to define, to size and to implement the Processes, Flows and Resources needed to secure the feasibility and profitability of the strategy defined by top management. As a result, it requires a set of behaviors and skills pretty unique, bridging strategical and operational approaches.

    Strategy ownership, ability to share a vision with teams, self-confidence and self-discipline are key elements giving form to behavior axis. It’s a complex cocktail needed to bring flexibility, reactivity and coordination within the organization.

    Operational experience, knowledge of Management toolkit, and ability to define and roll out logistics Master Strategies are the basic skills needed for SC Managers. They are essential to structure the Supply Chain and focus operations on expected delivery (Quality / Cost / Lead Time).

    Supply Chain Management remains a myth as most of the Managers acting are vision-less and stress-full for their team (stress resulting from a lack of confidence and discipline). They don’t have time to do their homework, logistics Master Strategies are rarely correctly defined. And their lack of vision is generating a lot of short term decisions based on local constraints and local results expected. Managers are firemen, constantly pulled in operational topics and unable to step back in order to find how to reach strategic targets through operational means put in place.

    No one to blame here, Managers are suffering from two distinct problems:

    1. ​Incompatibility of initial formations with job market needs (regarding Supply Chain profiles);
    2. Lack of support developed by companies when they integrate/promote managers. Management has never been so theorized but, in parallel, Management components have never been so ignored.

    ​What is the consequence?

    Say that you work in a warehouse or in transportation, say you handle order processing or inventory Management, everybody will have a rough idea about what you’re doing.

    Say you are a Supply Chain Manager you’ll lose 80% of the audience including in your own company.

    Nothing complex, it’s just time to go back to basics, time to work on the shared vision and time to align the organization, this is how Supply Chain will earn its stripes.