Supply Chain Agility — When Design Meets Planning
While supply chain planning and execution get talked about quite a bit as the two pillars of supply chain management, the third pillar, design, is often thought about as something that is done once a year or so, if at all.
However, a rapidly evolving business climate as a result of rising consumerism, economic nationalism, channel and SKU complexity, dynamic pricing and promotions, and arguably the most disruptive event in modern times — COVID-19 — is necessitating organizations to adapt with speed and agility. The business process changes needed are stymied by the rigidity of supply chains and limitations of technology in most organizations. However, some companies who are leading their markets are intertwining design principles into planning and execution, making design a part of their operational fabric. Design as a discipline is being recognized as a competitive differentiator.
Thanks to the geometric progress in storage and computational power due to cloud computing and the speed of computing due to in-memory technology, it is now a reality to plan in near real-time across an end-to-end supply chain, thus breaking down the traditional silos. This is helping organizations conduct business at an unprecedented speed. However, one of the limitations of these planning systems is that they don’t question the fundamental assumptions around the supply chain design. They simply accept these assumptions as if they are set in stone. Because of this, even as the speed of planning has increased, the gains in agility are not proportionate. Moreover, the quality of the plan degrades over time as the underlying assumptions, if left untested, become stale and irrelevant.
Speed without agility can be quite detrimental, as it limits the ability to course-correct and makes the mistakes propagate faster. However, this changes when design meets planning to unlock best of speed and agility. Supply chain design supports two types of decisions. The first type is structural, i.e. where to locate a new distribution center or a manufacturing facility. The second type of decisions are flow- and policy-related, wherein the physical flows of inventory and assets, source-destination mapping, transportation mode selection, and policies around sourcing, production, inventory, and distribution can all be fair game for assessment and change. Even some of the more advanced thinkers in SCM, tend to associate design with the first type, i.e., structural decisions. They make an implicit assumption that flow- and policy-related matters are in the realm of planning. However, such simplistic thinking is a mistake. Therein arises the need for bringing design principles into planning and intertwining the two decision types.
One may assume that structural decisions have a large capital outlay associated with them and hence can be less frequent. However, with uberization of warehousing and transportation, organizations can flex the number of nodes in the network on a more dynamic basis, collapsing or expanding them on demand, turning fixed capital costs associated with structures into variable, operating costs. Think of the many peaks experienced by consumer goods companies wherein seasonality associated with the holidays or back-to-school necessitates pre-building inventory and positioning it in leased facilities. More dynamic patterns of demand wherein external causals play an increasingly important role are turning once very predictable-turn businesses into quite choppy ones. This is turning structural design decisions into much more frequent decisions working in tandem with planning.
Coming to flow-related decisions, design principles help challenge ‘always done this way’ assumptions and make them open for dynamic adjustments. A major retailer located in the eastern United States has five distribution centers. Each of these DCs was buying product independently from the same supplier. Due to the bracket pricing, i.e., price breaks offered by the supplier based on volume, each DC manager used to wait to pool up orders and place them in one go, causing the replenishment to be lumpy and infrequent. This resulted in a feast or famine situation for the stores serviced by these DCs, resulting in overstocking or out of stocks. Through visualizing these flows using their design software, the retailer decided to optimize the flows, resulting in turning one of the five DCs into a cross-dock hub catering to the remaining DCs. While the structure hasn’t changed, the flows have become more dynamic. This resulted in increased replenishment frequency, reduced stockouts and overstocks, reducing the working capital requirements, delivering US$25 million in annualized savings. The retailer now made the process to arrive at such flow decisions a recurring discipline, embedding this into their operational planning.
In another example of questioning the underlying supply chain planning assumptions through design principles, a major chemical company performed a design analysis over their entire network segmenting their cost-to-serve (CTS) and the volume of the flows by country. The analysis showed that while the Philippines was ranked 4th along the cost-to-serve dimension, it was ranked 65th along the volume contribution dimension. Needless to say, the company was losing money in serving the Philippines market. Upon further investigation, they realized that a major customer in the Philippines was receiving shipments by air for the past two years. When the customer was first signed on, their initial order was rushed by air. However, a change in the transportation mode selection was never made after that. The planning system simply took for granted that air was the only allowed mode of transportation and did its best to match the demand with supply based on this flawed assumption. While the planning system helped hit the volumetric targets, the profitability suffered. This CTS and volumetric analysis based on design principles uncovered several such anomalies leading this company to make appropriate course corrections. Frequently testing assumptions and optimizing them made their supply and demand planning far more dynamic and profitable beyond a simple supply-demand balancing act.
There are many more interesting use cases emerging where design technology and associated algorithms are being used to augment weekly production and warehouse capacity planning, making design principles part of the operational fabric of a company’s design-plan-execute loop. However, there are many more organizations that just plan and execute based on supply chain policies and assumptions that never get updated. Such companies can hugely benefit from embracing these emerging practices, including building a digital supply chain twin, implementing robust supply chain analytics, and engaging in granular scenario planning. In my experience, it will be quite easy to spot several low hanging fruits wherein significant value can be unlocked in a matter of weeks.
In a world that can be very unpredictable, design can no longer be a one and done exercise. It has to work in lockstep with planning and in a far more dynamic manner to drive supply chain agility. I will repeat an analogy I used in the past to make this point. Planning tries to play the best hand it can with the cards that are dealt, whereas design can reshuffle the deck, picking the best cards to play out of the deck. Being the dealer and player at the same time can be a wonderful winning strategy! This is the power that can be unleashed when design meets planning!