Inventory Optimization -- It's All About Uncertainty
A multi-echelon inventory optimization solution can drive global supply chains to peak efficiency by recommending precise inventory levels, lot sizes, replenishment plans and locations from end to end.
Every large enterprise today has an Enterprise Resource Planning (ERP) system as part of its core technology infrastructure. A common characteristic of ERP systems is that they manage lots and lots of static details that, once recorded, do not change. When supply chain operations fall under the ERP umbrella, the ERP systems can come up woefully short due to volatility and uncertainty for which they have no solution. ERP systems can only help companies have the right products at the right locations at the right time if supply and demand conditions cooperate by not changing.
In realty, of course, almost everything in the supply chain environment changes all the time. For instance, a transportation problem may trigger the need to find a different supplier or transportation mode, having much the same impact as a sudden labor strike. In fact, supply chains are already stretched to their limits, with factors such as fuel costs, working capital, credit scarcity, global labor rates, raw materials, exchange rates, customer demand, and many others in a perpetual state of flux. The only way to give the supply chain a competitive edge is to augment the capabilities of the ERP system: to monitor and respond quickly to changes in critical supply chain factors.
That's not easy in today's fast-changing economic, regulatory and globalized world. Volatility and uncertainty pummel the network of suppliers, producers, wholesalers, distributors, and retailers that convert raw material to finished products for our homes and offices. That supplier in China may ship you 100,000 units this week, but only 20,000 units next week. That shipment may take 10 days to arrive or 20. Demand can be steady for weeks, then spike or drop unexpectedly, confounding the forecasts and causing excess inventories or product shortages. Businesses are struggling with these issues, and losing the battle precisely because their ERP systems were designed to manage constants but are faced instead with volatility, uncertainty and change.
With Necessity Comes Invention
Technologies such as inventory optimization have emerged that augment and complement ERP systems to bridge the 'volatility-uncertainty gap.' Inventory optimization technology uses sophisticated mathematics to model crucial aspects of supply chain behavior and analyze how different parts of the chain depend on each other. Inventory optimization intelligently quantifies and 'dollarizes' the effects of volatile shipment lead times, fluctuating demand, imperfect forecasts and many other factors. The result is a set of recommendations for inventory levels and policies that minimizes the amount of working capital tied up in inventories while guaranteeing that customer service levels are met.
Managing inventory can be a daunting task for an enterprise with tens of thousands of products that are spread across hundreds of locations. The challenge is even greater when the locations are situated in different tiers or echelons of the enterprise's distribution network. In such multi-echelon networks, new product shipments are stored at a central facility, and then sent to local distribution centers prior to being shipped directly to the customer or store. All locations may be under the internal control of an ERP system that lacks visibility up and down the supply chain and across multiple levels. This system cannot create successful replenishment strategies for multiple echelons.
In this case, inventory optimization complements the ERP system by taking available (and often incomplete or flawed) supply, demand, forecast and production data from the ERP and related transactional systems, and returning optimal inventory targets back, right down to the individual product level. Inventory optimization tools formulate optimal policy decisions and can feed them into the ERP system for execution. To the ERP system it looks just like business-as-usual -- more detailed facts to handle -- because the optimization "magic" was done outside the system, where the factors of change and volatility were transformed into fact-like data the ERP system knows how to process.
With a multi-echelon approach to inventory optimization, demand forecasting and inventory replenishment decisions can be made at the enterprise level. Each echelon has visibility into the other echelon's inventory. The primary customer demand signal and other information at the distribution centers drive the forecasts in all echelons. In each echelon, order cycles are synchronized and replenishment decisions account for lead times and lead-time variations of all suppliers.
The only way to thwart the problems caused by volatility and uncertainty is to gain visibility into all the factors needed to improve inventory decisions across the supply chain. A multi-echelon inventory optimization solution can drive global supply chains to peak efficiency by recommending precise inventory levels, lot sizes, replenishment plans, and locations from end to end -- and help inventory planners decide where and how much stock to maintain to buffer against uncertainties.
For several years supply chain managers at industry-leading companies have been implementing inventory optimization programs to complement their ERP systems. The results are compelling: many have reduced inventory by 20-30%, dramatically improved service levels, and reduced cycle times by 15-20%. At a time of unprecedented uncertainty, it's one fact that has been reassuringly reliable.
Fred Lizza is CEO of Optiant. Optiant provides a robust multi-echelon inventory optimization solution called PowerChain. www.optiant.com
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