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.

15%
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. 

50%
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.

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:

1

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.

2

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.

3

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:

Advantages

Limitations

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
Conclusions

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

DO'S

RATIONALIZE ALL DECISIONS ON THE BASIS OF A DETAILED STUDY, BASED ON FINE AND DEMONSTRATED DATA

DEPLOY, FROM THE START, THE BEST PRACTICES WITH ALL STAKEHOLDERS, NO MINIMAL DRIVING

SYSTEMATICALLY LEVERAGE THE LOCAL ECOSYSTEM, DO NOT COME UP WITH AN ARMY OF EXPERTS, BUT MIX THE EXPERTISES

LOCALIZE AS MUCH AS POSSIBLE TO OPTIMIZE COSTS, REDUCE RISKS ... AND LOOK LOCAL

Reflexion

Sustainability

DON'TS

BET ON A SERIES OF REMOTELY DRIVEN INITIATIVES WITHOUT A STRONG INVOLVEMENT OF LOCAL TEAMS

OVERESTIMATE THE IMPACT OF "LOW COST" TO AMORTIZE, JUSTIFY ANY IMPLANTATION

STARTING ON AN EXPORT-BASED MODEL, ALWAYS VERY EXPENSIVE AND RISKY AND EVENTUALLY RARELY SUSTAINABLE

UNDERESTIMATE THE ENERGY REQUIRED TO SUPPORT LOCAL ACTORS

In conclusion, integrate the operations early in your decision!

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

 Conclusion

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.