supply chain design Archives

Active Supply Chain Design: A Key Imperative for De Risking Supply Chains

Supply Chain Network Design | By Nari Viswanathan • 09/19/2023

Supply chain resiliency and sustainability are top priorities for CEOs today. To achieve these goals, corporate leadership must focus on two key areas: shift from internally focused supply chains to collaborative supply networks and actively design their supply chains.

Resiliency, which is the ability to withstand supply chain shocks and bounce back quickly, has become the most important requirement for supply chains. Supply chain executives must evolve from cost and service as the key objectives for optimal demand-supply balancing towards the “quadfecta” of cost, service, resiliency, and sustainability. Management practices such as lean manufacturing and just-in-time inventory management, along with globalization, have made tremendous impact on cost and service, but have accentuated risk. Risk events that happen in one part of the supply chain can cause a disruptive effect that is amplified multi-fold given the complex connectivity of labor, raw materials, and capacity. The bullwhip effect is one example of this disruptive effect, when small changes in demand cause huge demand spikes downstream.

Globalization, nearshoring and friendshoring trends are amplifying the supply chain risks. No single company is vertically integrated or isolated enough to be able to withstand the barrage of macro-economic challenges that are happening today. Inflation, pandemics, railway strikes, adverse weather events – the supply chain disruptions keep on coming. With expansion of supply chains into supply networks globally, there is an increased chance of disruptions caused by various kinds of risks.

Operational vs. disruptive risks

One of the keys to becoming more resilient is to minimize risks in your supply chain, while another is having the agility to quickly respond to disruptions caused by these risks. A good way to think about risk is anything that causes a supply chain to be impacted in terms of its performance. Risks can be further divided into internal risks or third-party risks. Each of these types of risks can be further subdivided into operational and disruptive risks. Table 1 describes a few examples of these types of risks.

Table 1. Categorization of risks

Types of risks based on where within the supply chain these risks occur	Impact of risks	Example
Internal Risks	Operational	Minor quality defect in internal manufacturing process that was caught during inspection
Internal Risks	Disruptive	Major quality defect that was unaddressed and caused consumer health issues (pharmaceutical recalls)
External Risks	Operational	Third-party supplier not shipping on time
External Risks	Disruptive	Supplier’s supplier going out of business due to lack of business compliance (for instance, the German Supply Chain Act is an example of regulatory compliance that suppliers have to adhere to)

Operational risks are mainly driven by variability and uncertainty. Balancing supply and demand by orchestrating the flow of materials and information is a key requirement for managing operational risks. Metrics such as lead-times, forecast accuracy, inventory levels, and service are used to measure operational risks. Design and planning software has been utilized for the last several decades to manage these operational risks. Lean manufacturing also focused on managing these operational risks, especially within the four walls of the enterprise.

Disruptive risks on the other hand are harder to predict and manage. These risks are low probability and high impact. Examples of disruptive risks are suppliers going out of business or shipwrecks that result in the loss of cargo containers. Natural risks such as weather, fires, pandemics, etc., fall under this category as well.

Using technology to de-risk supply chains

From a technology perspective, supply chain design tools have been developed from the ground up to handle uncertainty and risks, generate scenarios that identify risks proactively, and provide solutions to mitigate these risks. It is critical that supply chain design tools model real world complexity to effectively model the risks. Lack of adequate risk data and the non-strategic positioning of supply chain design within the organization has been a key inhibitor to success. Another part of the solution that has been missing until recently is the tight integration with upstream processes, such as strategic sourcing and supplier risk management, which have been siloed and operating in their own domains. AI Assistants can also help make managing the process of supply chain design easier.

AI assistants uncover hidden opportunities to reduce costs and risks in the supply chain

The sheer quantity of data and possible combinations of those data points might obscure cost-saving and risk reduction opportunities from the sight of supply chain modelers. There might be millions of possible combinations for adding lanes, changing modes, or consolidating volume, making it difficult for modelers to identify which scenarios will provide the highest cost savings. There may be several nodes that are critical and single sourced thus elevating the risk profile of the supply chain. This is where AI can make all the difference. A combination of modeling and machine learning capabilities can provide insights into cost drivers and proactively identify potential cost saving and risk reduction opportunities.

Here is a sample framework of this process might work:

Identify the risky elements
1. What sites (distribution centers, suppliers, manufacturing plants, etc.) are most exposed to risk?
2. Which products would be most impacted?
3. What is the Cost to Serve for all the flows to the customer?
Quantify the costs and risk to the business
1. What revenue is at risk?
2. What’s your risk tolerance?
3. What’s the cost of doing nothing?
4. What is the cost impact of making changes?
Produce recommendations for action
1. Models that can show how flow shifts will reduce or increase risk
2. Increasing robustness of network design
3. Recovery strategy
Analyze the trade-offs
1. Risk tolerance
2. Impacts of doing nothing
3. Cost of implementing changes
4. How it all aligns with business goals

The best AI acts as a partner, handling the more mundane, routine work that can often bog modelers down. The best AI frees humans up to embrace their own creativity and focus on solving more complex problems. Supply chain professionals have been at the forefront of adopting advanced technologies associated with Operations Research, machine learning and statistical analysis. Now they have the opportunity to leverage generative AI combined with machine learning to drive resiliency and cost savings to their organizations.

Nari Viswanathan is currently Sr. Director of Product Segment Marketing at Coupa Software, where he brings products to markets in the areas of Direct Material Procurement and Supply Chain Design and Planning. Over the past 20 years, Nari has held VP and Director of Product Management, Research and Marketing roles at Aberdeen Group, River Logic, Steelwedge and E2open. He has significant experience building products from the ground up and managing the P&L for a product suite. He is a proven B2B marketer with expertise in content marketing, competitive intelligence, and positioning. He has published numerous thought leadership articles, whitepapers, blogs and delivered dozens of webinars during his career. Nari Viswanathan is a six times SDCExec Supply Chain Pro to Know award winner. Nari holds a master’s degree in Manufacturing Systems Engineering at the University of Wisconsin-Madison and a bachelor’s degree in Mechanical Engineering at the Indian Institute of Technology, Chennai.

Editor’s Choice: Why Supply Chain Design Is Not a “One-and-Done” Exercise

Supply Chain Network Design | By Chris Cunnane • 09/22/2022

Note: Today’s post is part of our “Editor’s Choice” series where we highlight recent posts published by our sponsors that provide supply chain insights and advice. Today’s article is from Ahmad Jiwani at Coupa and looks at supply chain design.

How often do you revisit and update your supply chain designs? Once a year? Once every two years?

If you’re like many organizations, you probably have made changes to your supply chain network in the past two years. But those changes may still not be enough if you don’t revisit them as conditions warrant. Even if you’ve implemented the most sophisticated process and technology for your S&OP process, there’s a hard truth you need to hear: a supply chain not designed to be in tune with the rapid market shifts will leave your best-laid plans exposed and make them unreliable.

Traditional supply chain design and planning relied on the idea that, “governments were rational, variability would be low, and logistics would always be available,” as Lora Cecere of Supply Chain Insights has said. But by now, we all know those ideas no longer hold true.

Designing every once in a while — or designing episodically — is already limiting your organization’s supply chain resiliency, sustainability, and profitability. Here’s why, and what your organization should be thinking about instead.

But first, let’s get on the same page:

Supply chain design solutions and definitions

Supply Chain Design: A process where nodes, modes, flows, and policies driving a supply chain are defined, reviewed, optimized, and aligned to business objectives.
Episodic Design: An approach to supply chain design that is often project-based and conducted on an ad-hoc or periodic basis, and may or may not be loosely connected to other business objectives.
Continuous Design: Continuous design is the development and ongoing refinement of optimal supply chain structures, policies, and flows. This is achieved through analysis, scenario planning, and simulation with end-to-end models, fueled by AI and powerful algorithmic engines. In leading organizations, such effort is supported by a Center of Excellence (COE).

Why episodic supply chain design falls short

A global food and beverage company used to run a handful of models annually across their European operations. But as their supply chains and business grew more complex, they realized it wasn’t enough. They couldn’t adapt quickly to changing situations on the ground and their designs weren’t able to take into account local and regional contexts. The realities of their business and the world required them to run more scenarios and to run them more frequently.

To read the full article, click HERE

Is Saint-Gobain Serious About Reducing Their Carbon Footprint?

Sustainability | By Steve Banker • 01/31/2022

It is not uncommon for companies to tout their commitment to sustainability, but on closer examination the company’s commitment is far less than advertised. The phrase being used for this is “greenwashing.” Here are a few questions that can be asked to really get at a company’s commitment to sustainability:

Are the goals significant?
Is real progress being made?
Do green projects have a lower hurdle for approval?
If there is a tradeoff between cost and a sustainable project, is the higher cost/less sustainable project ever selected?

Let’s put a major multinational – Saint-Gobain – under the microscope to illustrate how this kind of analysis

Who is Saint-Gobain?

Compagnie de Saint-Gobain S.A. is a French multinational corporation, founded in 1665 in Paris and headquartered on the outskirts of Paris, at La Défense. The company had sales of more than 38 billion Euros in the last financial year ($43 billion

A worldwide leader in light and sustainable construction, Saint-Gobain is present in 72 countries with more than 167,000 employees. Saint-Gobain designs, manufactures, and distributes materials and solutions for the construction, mobility, healthcare and other industrial application markets.

The company has a continuous innovation process. In 2021, for the tenth consecutive year, Saint-Gobain was named one of the world’s 100 most innovative companies, according to the Clarivate Top 100 Global Innovator™ ranking. Saint-Gobain is also considered one of the leading companies in terms of environmental ambition and transparency; They are listed as being on the CDP’s “Climate Change A List.” CDP is a global non-profit organization whose benchmarks on environmental performance by industry are widely recognized.

Are Saint- Gobain’s Goals Significant?

The company has committed to carbon net neutrality by 2050. The company will attain this goal by having operations that are significantly less carbon intensive and by producing products that are significantly better for the environment. A press release from October of 2021 stated that solutions sold by the Group over the course of one year result in the avoidance of around 1,300 million tons of CO2 emissions over those product’s lifespan. These avoided CO2 emissions from their products, they argue, are around 40 times the Group’s own total carbon footprint.

A new goal, targeted for achievement in the next five years, is to be the world leader in providing light and sustainable construction products. Buildings and building construction is the primary cause of CO2 emissions, accounting for 40% of emissions around the globe. Saint-Gobain’s ambition is to provide solutions that can decrease in at least two thirds these emissions. Light construction – when the only support is a wooden, concrete or metal structure – requires the use of light materials, such as plasterboard. This contributes to the decarbonization of buildings. The use of light construction solutions – which already account for 40% of the company´s sales – has several advantages according to the company. It increases site productivity, reduces the usage of raw materials by up to 50%, but also leads to a more comfortable building.

If a company is serious about achieving their goals, they can’t allow slippage or have a moving target. Saint-Gobain also has a goal for organic growth of 3 – 5% through 2025. However, their carbon reduction goals for their value chain operations for 2030 will not be changed. The 2030 roadmap is targeting a reduction in CO2 emissions of 33% for scopes 1 and 2, and of 16% for scope 3, versus 2017 (definition for scopes 1, 2, and 3). In other words, they aim to reduce carbon by this target by 2030 regardless of company growth. New acquisitions, for example, won’t lead to a prorated calculation that factors out emissions from the acquired company from the carbon target.

Is Saint-Gobain Making Progress on Sustainability?

If you examine the Saint-Gobain website, you will find much material on future goals, but little content on the recent progress they have made in reducing their CO2 emissions. However, progress clearly is being made. Particularly in reducing the carbon footprint associated with getting their goods to market.

Fabricio Saraiva Moreira, Operational Excellence Director for Latin America, was willing to discuss their success in reducing carbon emissions in Latin America. Mr. Moreira is in Brazil where he is also in charge of a Center of Excellence (CoE) for Latin America for supply chain and manufacturing, sustainability, EHS, Industry 4.0, and Data Science.

To support supply chain operations, Saint-Gobain has a Transport Control Tower. This control tower includes a supply chain design solution from Coupa that helps them reduce both freight costs and C02 emissions. To help evaluate opportunities, Mr. Moreira’s team develops projects and presents them to business unit directors with different scenarios for them to evaluate. The business directors pick the option that is best suited to their needs. The scenarios target achieving a specified customer service level in a manner that improves profitability while reducing CO2 emissions.

Brazil, the single largest country in which the company operates in Latin America, has experienced significant benefits by optimizing its transport routes. In Brazil, across 16 business units, they operate 56 factories and 126 distribution centers and outlets. To connect these supply chain sites to each other and customers there are 3,900 transportation lanes covering more than 1.7 million kilometers of highway. Saint-Gobain primarily uses truck transport, but sea shipments are also used.

In short, this is a complex network. In fact, there are 13,000+ potential network configurations. The Coupa tool provides a much more efficient way to conduct cost saving/sustainability studies. And the results are more credible when presented to business leaders. Saint-Gobain began working with LLamasoft, now Coupa, in 2019.

The company typically does 25 to 50 studies per year. These efforts led to transport emissions reductions of 40-60% for several Saint-Gobain brands, and a 13% reduction in CO2 across all the transport control tower studies they conducted across Latin America.

There were also freight savings. Over the past five years, the transport control tower projects have led to savings of over $10 million. In short, the gains in sustainability have been much more impressive than the freight savings. “We are only at the beginning of the journey of decarbonization of logistics. There is still much more to be done”, explains Mr. Moreira.

There are three primary ways cost savings and carbon reductions are achieved. Through green field studies, through better transport optimization, and through better collaboration with outside entities or customers.

In a green field study, a company looks for an optimal placement a new factory or warehouse. An optimal placement is one that achieves service level goals while reducing the total number of miles that trucks will need to drive to deliver goods to customers. Fewer miles traveled means less emissions.

Transport optimization is done in several ways. Saint-Gobain looks to see if trucks delivering goods for one brand, and returning empty, can get backloads from other divisions and reduce those empty miles. Saint-Gobain can also look outside their network to work other businesses for opportunities to reduce empty miles on return legs —a collaboration with Heineken led to emissions reductions of 40% for those collaborative routes.

Another way miles can be reduced is by looking at existing routes across the network. It might be that distribution centers (DCs) are delivering goods to customers in a 50-mile radius. Would a 30-mile radius for one DC, and 70-mile radius for a different DC, lead to fewer total miles? Similarly, on what routes should Saint-Gobain use their own trucks versus using outside carriers?

Can service levels still be attained if there is a modal shift? Shipping by sea is less expensive, and has fewer emissions, but takes longer. What routes can be moved from truck to sea without adversely affecting customer service?

Can trucks be filled more fully? A truck has a limit of how much weight it can carry. In one study, it was determined that a truck carrying heavy products, big bags of grain, could also carry insulation, a very light product. This resulted in better utilization of the fleet.

Finally, Saint-Gobain is exploring the use of electric and natural gas trucks in a partnership with its suppliers. However, Mr. Moreira explained, the infrastructure for electric and natural gas trucks is much more limited in Brazil than in Western Europe or North America. The opportunities are limited to metropolitan areas that have charging and refueling stations, but he believes that for the next few years the situation is going to improve.

Do green projects have a lower hurdle for approval?

Companies have a variety of projects they can invest in. If only the projects that create the best financial returns are selected, sustainability will take a back seat. One way to know that a company is serious about sustainability is that sustainability projects have lower hurdles they must clear to get approved.

At Saint-Gobain this is the case. In calculating the payback of a project, a company figures out both the costs and the savings that occur over time. If you do not put a price tag on carbon emissions, you run into the free rider problem. A company can be free rider in terms of the environment in the same way that someone who jumps over the turnstile at a subway without paying is. In the Group’s investment decisions, the internal carbon price has been increased to €75 per ton for capital investment decision (versus €50 previously), and it is €150 per ton for R&D projects.

Saint-Gobain has other measures in place to encourage progress on sustainability as well. Environmental, social, and governance (ESG) policies are embedded into management processes. ESG is taken into account in short-term incentive plans (at 10%) and long-term incentive plans (at 20%, up from 15% previously). The company has established committees focused on corporate social responsibility themes operating at the Executive Committee and Board of Directors level.

If there are tradeoffs between costs and emissions, is the higher cost, lower emission option ever selected?

Most companies are early in their journey and have so much low hanging fruit, that they can select projects that reduce carbon and reduce costs. Saint-Gobain may be further up the maturity curve. In one case, there was a green field site selection project aimed at deciding where a distribution center should be located in the Buenos Aires metro area. They looked at four sites that had the same distribution costs. The site they selected, while not a lower cost network solution, did have the best carbon footprint.

Over a span of years, as Saint-Gobain marches towards carbon net neutrality, the choices will get harder. Mr. Moreira does believe that when Saint-Gobain gets to the stage of their development where there is no more low hanging fruit, they will make the harder choices. The company, he believes, has the right kind of support from the executive suite and the right kind of governance to insure it.

Supply Chain Design Crosses the Chasm

Supply Chain Network Design | By Dr. Madhav Durbha • 10/21/2021

Recent supply chain disruptions are forcing organizations to challenge the prevailing wisdom and look for newer approaches to decision making. The simultaneous shocks to demand and supply, and the magnitude of these shocks are not something the world ever experienced. The demand patterns significantly shifted in terms of the product and channel mix. On the supply side, material shortages, staffing challenges, and shipping capacity constraints are all happening at the same time. The supply chain nodes which were once deemed to be relatively static have become far more dynamic in the recent past. The rapid shifts to eCommerce during the pandemic caused retailers and brand owners alike to flex their network nodes (where goods are made and inventories are stocked) significantly. Pop up warehouses, micro fulfillment centers, and warehousing-on-demand are all examples of how the nodes are becoming increasingly dynamic. The product flow paths and modes of transportation altered radically as well even without accounting for any network node changes, owing to port closures or shortages in various transportation lanes. Some companies have taken extreme measures such as chartering private cargo ships to sail around port delays.

For the longest time modeling and designing such nodes, modes, and flows has been the realm of Supply Chain Design. While Supply Chain Planning and Execution garnered much attention over the years, Design remained very episodic and project-based. Just a handful of optimization and operations research experts ran models of the network and made recommendations. Organizations did not see much of a need to relook at their supply chain design unless pressed for. Barring significant changes such as mergers and acquisitions, organizations looked at their supply chain design once every year or two. Planning and Execution systems in turn consider the rules, policies, and flow path assumptions recommended by Supply Chain Design as key inputs and assumptions guiding the S&OP and S&OE decisions. Decisions such as what should be the order minimums and multiples, what should be the replenishment frequency to my downstream locations, what should be the splits between different sources available, and how they should be prioritized, are all the types of policies that need increasingly frequent revision.

Several organizations are now realizing that such inputs and assumptions, if not tested regularly, become stale and lead to erroneous planning and execution decisions. Amongst the companies we engage with, there is an increasing acknowledgement that the clock speeds of the design and planning processes will need to be more tightly aligned, i.e., the testing of the policies and product flow paths along with implementation of any changes that become increasingly closer to the S&OP cadence. This is leading these organizations to move from Design being an episodic activity to a continuous process. For example, if a retailer stands up a number of micro fulfillment centers to support a spike in eComm demand, this translates into changes to the flows and possibly modes of transportation, and accordingly master data changes. Design can help test such ideas before implementing changes to the master data.

From a technological perspective, Design remained the realm of desktop modeling techniques for close to two decades since its advent, leveraged by individuals trained in advanced analytics and optimization techniques. However, with the new generation technologies, it now is practical to keep the data feeds fresh to make the modeling exercises a continuous, ongoing discipline. Thanks to cloud computing – solve speeds, scale, and granularity at which the algorithms can be applied have also grown tremendously. Taking advantage of these advances provides much sharper and refined inputs into planning and execution processes. New generation no-code platforms allow for the ability to deploy this algorithmic intelligence to planners and business users through apps. This is making the process of matching the Design and Planning clock speeds feasible.

No longer does one need to be confined by static and stale rules and assumptions guiding the planning and execution processes but can test these more dynamically. In fact, with the advances in AI, one no longer needs to test different Design parameters manually thinking through them. Instead, AI powered prescriptive analytics can proactively start recommending scenarios for users to consider. The technology is reaching such an inflection point. This capability will be game changing. Considering the number of permutations and combinations involved in decisions such as network node skips or transportation mode switches or volume consolidation opportunities, AI scales well to find those value creation opportunities and surface them to the users to act on.

As organizations prioritize resiliency initiatives, Design helps them be deliberate about where to build optionality in their supply chains. Sustainability initiatives can benefit through optimizing the carbon footprint. Taxes and tariffs can be modeled, and tax efficient supply chains can be designed. These are all capabilities that are typically beyond the reach of planning systems and fall in the realm of advanced analytics. Once supply chains are designed for these capabilities, planning and execution systems accept such design as input.

Leading organizations are recognizing the need for Design to be continuous and process driven as opposed to episodic and project-based. They are establishing Design Centers of Excellence and aligning these functions closely to Planning and / or data science, analytics practices. They are designing career paths to retain and grow such talent.

As Winston Churchill said, “Never let a good crisis go to waste”. For those who are building their careers in the discipline of Supply Chain Design and Modeling, the current disruptions present an opportunity to showcase the difference they can make and rise to the occasion. However, for this to happen, one has to lay the technology foundation to ensure Design exercises can be performed in a repeatable and timely manner.

Supply Chain Design has crossed the chasm after all!

Dr. Madhav Durbha is the Vice President of Supply Chain Strategy Coupa Software, where his team helps customers and prospects solve various supply chain challenges. Prior to Coupa, Dr. Durbha held positions at LLamasoft, Kinaxis, JDA Software and i2 Technologies, Inc. With more than 20 years in the supply chain industry, Dr. Durbha has broad experience in strategy & process consulting, supply chain software, program management, software application development & deployment, machine learning and data science. He received his Ph.D. in chemical engineering from the University of Florida and his bachelor’s degree in chemical engineering from the Indian Institute of Technology at Madras.

One of the World’s Best Supply Chains

Chemical Industry | By Steve Banker • 09/24/2018

When lists of the best supply chains in the world come out, one multinational is too rarely discussed. That company is BASF. BASF, the world’s largest chemical company, has a cleverly constructed supply chain where the byproducts of one operation get converted into starting materials of another product. BASF, a company headquartered in Germany with 2017 revenues of $65 billion, calls this “Verbund.” In English this means to “combine” or to “cooperate.” I call it excellence in supply chain design.

Verbund at BASF

Verbund is defined as the intelligent interlinking of production plants, energy flows and infrastructure. BASF has six Verbund sites that create efficient value chains that extend from basic chemicals basic chemicals to high-value-added products such as coatings and crop protection agents. When by-products of one plant can be used as the starting materials for another, chemical processes consume less energy, produce higher product yields and conserve resources.

Verbund is core to have one of the best supply chains — Verbund Sites at BASF

The Ludwigshafen site, encompassing ten square kilometers, is the largest chemical complex in the world. At this site, 110 production facilities and 200 production plants are interconnected. Byproducts and products flow through 2850 kilometers of pipes, 230 kilometers of rail, and over 100 kilometers of road. An astounding 39,000 employees work at this site. Talk about a company town!

The Verbund Concept Largely Explains How BASF Created One of the World’s Best Supply Chains

Verbund saves the company money. The company believes they save over one billion euros annually through this concept.

But Verbund is also a sustainability play. BASF saves on raw materials and energy, lowers emissions and cuts logistics costs because the synergistic production operations are near each other. In logistics, having plants near each other allows for 280,000 fewer truckloads per year.

In energy, waste heat from production processes is captured to be used as energy in other production plants. In 2016 this allowed the company to save around 19.0 million megawatts per year. That reduces CO2 emissions by 3.8 million metric tons annually.

BASF Embraces Digitalization

This highly integrated value chain generates unbelievable quantities of data. BASF seeks to better capitalize on this data by investing in digital technologies. The company’s smart manufacturing initiative is working on predictive maintenance, the use of augmented reality, and even greater savings in electricity and steam generation.

Improved savings in electricity is particularly interesting. Ludwigshafen needs about 20 million metric tons of steam per year. This is generated by the production plants and the site’s three power plants. The power plants produce the majority of electricity needed at the site. But they sometimes generate more power than is required. That electricity can be fed into the public grid.

On the BASF digitalization website, they describe their digitization effort in this area this way:

However, electricity is a complex business as market prices fluctuate every 15 minutes. Computer programs help to buy and sell at the best times. For this, however, a precise forecast is required as to how much steam and waste heat the production plants supply at the site, how much steam the power plants have to contribute and how much electricity is needed. This also fluctuates depending on the time of year, the weather and the economic conditions.

To date, the total requirements have been determined manually combined individual forecasts of the plants. A new statistical model, based on large amounts of data, now provides even more precise calculations: The software takes into account, among other things, historical and up-to-date information on production shutdowns, weather data and economic indices. The program searches for relationships and establishes connections with the energy demand.

This has been very successful: The forecast for steam demand has already improved by up to 60 percent. The former procedure will now be gradually replaced and applied to other areas. The new program supports us also in electricity trading to make better price forecasts.

BASF also has a smart supply chain program that has created some of the world’s largest automatic guided vehicles (AGVs). These AGVs allow the company to supply their production plants faster and at lower cost. They project that it will soon take one hour from order to delivery of raw materials in huge tanks. Historically, this took twenty-four hours.

When you look at lists of companies with the best supply chains, you rarely see chemical companies mentioned. BASF shows there is a lot more going on in this sector than most supply chain executives understand.

Three Ways to Design Your Supply Chain for Successful Mergers and Acquisitions

Guest Commentary | By Jeff Metersky • 01/11/2018

As the global economic outlook improves, worldwide mergers and acquisitions (M&A) activity is predicted to pick up. M&A deal volume and deal value remains strong. According to recent surveys, 56 percent of responding companies expect to actively pursue acquisitions in the next 12 months[1], with global M&A value projected to top $3.2 trillion, up 23 percent from this year[2].

Despite the increasing numbers, failure rates for M&A initiatives are extremely high. Depending on which report you consult, M&A initiatives have a failure rate of anywhere between 50 and 90 percent. Failure to consider the synergies and redundancies of the end-to-end supply chain of both companies is arguably a top contributor to the shortfall. How can businesses improve their chances for M&A success and reduce the inherent risk?

Apply Supply Chain Design Across M&A Activities for a Better Future State

Supply chain design technology enables companies to model their supply chains, evaluate alternatives, optimize the network structure, and simulate multiple scenarios in order to predict the resulting operational performance of the merged organizations. Let’s look at opportunities to leverage modeling across all stages and types of M&A activity, including:

Pre-Merger
Post-Merger
Divestiture/Spin-Off

1. Pre-Merger Analysis
The pre-merger phase is uniquely challenging in that access to data for potential markets and acquisition/merger targets is often difficult to access. Strategy building and decision making relies heavily on assumptions rooted in available data. Companies can use supply chain network models to visualize and analyze M&A strategies and perform critical sensitivity analysis on key assumptions.

Using modeling and supply chain design during this critical phase gives companies the insight and decision support needed to:

Avoid costly mistakes such as over-estimation of potential synergies
Compare alternative M&A targets
Analyze the most effective strategy for entering a new market

2. Post-Merger Analysis
Once an acquisition has closed, it is often up to the supply chain executives and their teams to help realize the operational efficiencies promised in the board room.

With two unique, complex operations often including overlapping assets, products, customers and suppliers, this is not an easy task. Supply chain modeling and design is essential to help identify and evaluate the array of possibilities.

The benefits of modeling and supply chain design at this phase include:

Finding short-term improvements with limited disruption
Simultaneously analyzing big-win but potentially more disruptive changes
Creating a more accurate projection of cost savings and operational efficiencies that can be reported to executives, the board and the investors

3. Divestiture/Spin-off Analysis
In a divestiture or spin-off situation, previously shared resources need to be separated, manufacturing and distribution capacity is reduced and shared customers and suppliers may need to be allocated to one or the other entity. Supply chain modeling can be employed in these situations to enable data driven decisions on which sites, products, customers and suppliers to keep and which to eliminate, as well as for costing of supply chain operations with new facility and lane volumes and capacities.

The benefits of using detailed supply chain modeling during a divestiture or spin-off include:

Identification of the capacity requirements and product flow volumes for the resulting businesses
Data to drive the negotiation of new business terms with transportation service providers and suppliers
Implementation timeline for the transition from shared assets and resources to independent status

Customer Example: Planning Adequate Production Capacity for Merged Supply Chains

Challenge: A well-known global food and beverage producer had acquired a new line of snack foods. Given these additional products, the company wanted to understand how their current production and distribution network was positioned to meet the increased volume, and when and where capacity problems could occur.

Solution: A multi-period network optimization model was built incorporating all existing production locations and work centers, and showing customer, capacity, product and demand data forecast for the next six years. Optimization would recommend when and where to open new production lines to ensure all the demand for the product would be met while keeping total cost at a minimum.

Results: By considering total landed costs, the model showed a potential savings of $7 million in labor and transport costs by opening facilities earlier than the company had originally planned.

Points to Remember

Mergers and acquisitions introduce an immense number of options for the design of the new organization’s future supply chain. Redundant facilities, assets, suppliers, customers, and products set many M&A efforts up for failure. Using modeling technology to visualize, analyze, and optimize the current and future supply chains can help significantly reduce risk and provide a data-driven roadmap for success.

As vice president of solutions strategy, Jeff Metersky has global responsibility for designing comprehensive supply chain design solutions comprised of technology, services, support, education and training for future and existing LLamasoft customers. Throughout his career he has consulted in over 100 supply chain design and inventory optimization engagements across a variety of industries and geographies. Prior to joining LLamasoft, Jeff co-founded CHAINalytics and was part of the team that brought i2 Supply Chain Strategist to market. Jeff holds a BS degree in industrial engineering from The University of Illinois and an MBA in materials and logistics management from Michigan State University.

[1] EY Global Capital Confidence Barometer October 2017

[2] “Global Deal Activity to Accelerate in 2018,” Baker McKenzie, November 2017

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