Inventory optimization is rocket science, but the market is growing fast

Jan. 17, 2006
The worldwide market for inventory optimization solutions is expected to grow at a compound annual growth rate (CAGR) of 12.6 percent over the next five

The worldwide market for inventory optimization solutions is expected to grow at a compound annual growth rate (CAGR) of 12.6 percent over the next five years. The market was $99.2 million in 2005 and is forecasted to reach $ 179.6 million in 2010, according to analyst firm ARC Advisory Group.

“Traditional software markets sell software licenses,” according to Steve Banker, service director for supply chain management at ARC Advisory Group. “However, in this market, knowledge-based outsourcing and software as a service will be key growth drivers.”


This is still a young, small market that requires educating potential customers of the significant benefits advanced inventory optimization offers over competing types of solutions and processes for setting inventory targets. Inventory optimization delivers targeted customer service levels with the minimum amount of network inventory.

Inventory optimization solutions are a type of supply chain planning solution. However, the optimization is different from that found in traditional planning systems that contain a single stage inventory calculator which is designed to determine inventory targets for only a single node in the supply chain at a time. Single echelon solutions are suboptimal because they do not take a holistic approach to network inventory optimization. Rather than calculating safety stocks for a single supply chain node, inventory optimization solutions simultaneously calculate where and how much inventory should be held across the network of locations at which inventories could be held.


Inventory optimization is a complex solution. The math is almost impossible to understand, Banker notes, even for those who have a good understanding of statistics. This makes the solution difficult to sell. Once sold, it can be difficult for users to drive value from solutions on an ongoing basis. According to Banker, “This type of solution is not well served by a traditional software license and service model.” Consequently, for the inventory optimization market, ARC is projecting much faster growth from the knowledge-based outsourcing and software as a service sales models.

Knowledge-based outsourcing involves outsourcing all or some portion of a planner’s function to an outside party. As opposed to traditional business process outsourcing, such as outsourcing repetitive tasks to a call center to India, knowledge-based outsourcing involves outsourcing a function that requires knowledgeable and skilled workers. The software itself is designed to be used by planners that are analytical, have the pertinent product and company domain expertise, and “have a passion for the business.” The software does not, however, require users to have a Ph.D. in operations research or statistics. Nevertheless, many companies will find that they can benefit from knowledge-based outsourcing partners to regularly search for outliers and data anomalies, keep the software properly parameterized, and engage in strategic planning perhaps in conjunction with other complex tools such as network design.

In the software as a service model, the software is leased rather than purchased outright by the user. Software as a service can be a potent sales tool for applications with high ROI such as advanced inventory optimization. According to Banker, “When I asked one company how long their payback period was following implementation, they said they had received full payback prior to the implementation.” When asked how that could be, they explained that the inventory optimization supplier came in and entered their data into the software to do an analysis of potential savings. Once the “bake off” was done, the supplier hosted the solution and provided inventory targets while the implementation began. Twelve weeks later the implementation was complete, but the solution was already paid for prior to the company’s version of the software going live.

www.arcweb.com/Research/ent/aio.asp

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