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How to Make Supply Chain Complexity Work to Your Advantage

By Joe Shamir12 Apr 2019

With supply chain complexity increasing at an unprecedented rate, perhaps the biggest challenge for businesses is figuring out how to navigate this uncertainty to deliver service profitably.

Amazon sells more than 3 billion products through 11 different country marketplaces globally. In the U.S. alone, Amazon introduced 208 million new products in 2018 — most of which are slow movers, or ‘long-tail’ items. Despite its extreme complexity and scale, Amazon’s July, 2018 earnings doubled shareholder expectations, turning a quarterly profit of a whopping $2.5bn.

When you break it down, Jeff Bezos figured out how to do three seemingly contradictory things at once: deliver exceptional service levels, at the lowest cost possible, and manage complexity. I argue that achieving all three with true success is difficult for any company to obtain without advanced technology capabilities.

So what’s the secret of making supply chain uncertainty work for you? First, take a different approach. Too many companies get locked into traditional processes and a familiar vicious cycle: unable to reliably forecast an increasing number of SKU combinations, they load up on inventory to accommodate long-tail, erratic demand. This invariably leads to extra freight costs and excess and obsolete inventory that either needs to be written off or sold at a heavy discount. Planners are continuously in reactive mode, spending most of their time changing suggested replenishments and manipulating service levels instead of driving performance.

The way out is to break through the forecast accuracy barrier: Instead of seeing forecast as the end game, see it as the starting point to a better stock plan and better service. It all starts with probability forecasting. Using this approach, you still get one number that’s associated with the most probable outcome. However, banded around this number you get a range of other possible outcomes, each with a different probability attached.

Probability forecasting is ideal for supply chains that include a high number of long-tail items and face demand variability and uncertainty due to the huge number of factors they are unable to model adequately. It’s been 25 years since we first began to champion this approach as an alternative to traditional forecasting. Today, faced with overwhelming supply-chain complexity, there’s a strong and increasing number of businesses turning to probability forecasting.

With an accurate probability forecast, use stock mix optimization to enable what we call “service-driven planning.” Instead of assigning the same service level for every SKU in a group, each SKU location across the supply chain is assigned its own service level that is optimized to achieve the business goals. For instance, instead of assigning all SKUs in a class a 98-percent service level, a global 98-percent target is achieved by optimally setting individual SKU location service levels at 99 percent, 97 percent, 99.5 percent, etc., achieving the same overall customer service level objective with far less inventory expense.

Global prescription lens manufacturer Shamir Optical applied probability-based forecasting to become more service-driven. Rather than use a one-size-fits-all inventory policy, Shamir analyzed demand patterns to create a blend of different service level targets for each individual SKU in each location. The firm reduced inventory levels by more than 25 percent overall, while consistently achieving service levels exceeding 99 percent.

To make probability forecasting work, you need to automate the planning process with a self-adaptive system that uses machine learning technology — a form of artificial intelligence. Because a supply chain model is a “living” system, machine learning continuously learns and tunes the results over time, allowing you to introduce new data sources as needed. Applying A.I. provides deep insight into the behavior of demand and inventory to improve the outcomes. For planners this is great news: probability forecasts are, by design, a starting point — not an end game. They are designed to give planners the data they need in time to make informed judgement calls on service policies and corresponding optimal inventory levels across their supply chains. This frees up planners to focus on service, work on strategic projects and add their business insights to the system.

Your business can thrive on complexity, too. Our service-driven planning customers consistently see service levels go up, and costs, waste and inefficiency go down. Hundreds of companies have gained a wide range of benefits, from freeing up working capital to reducing obsolescence, transportation and expediting costs and markdowns. Many companies report becoming more responsive to market changes and being able to make better strategic decisions.

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