As companies seek that critical edge in logistics and supply chain management, you might think they'd be intensely focused on what the competition is doing. But that's not necessarily the case. Instead of looking outward, many are looking inward, scrutinizing their own operations for waste, areas of weakness, and so forth. And in many cases, that means they're making supply chain analytics—the process of examining and optimizing internal operations—a part of the routine, like freight bill audits or inventory cycle counting.
That's a marked change from past practice. It used to be that when companies employed analytical software, it was on a project basis to address a specific problem. "For a long time, firms have done one-off analytical studies," says Mike Watson of IBM. "Now, these firms realize that there are big benefits to using analytics and optimization on an ongoing basis."
Also known as "business intelligence" solutions, supply chain analytics programs basically monitor and measure supply chain activities from shipping to storage, from production to inventory. The applications use special algorithms to spot problems and then look for the underlying cause. By scrutinizing millions of pieces of data, the software can quickly decipher what's going on throughout the supply chain and detect minute changes that could portend trouble later on.
Leading companies are employing this type of software to gain sharper insight into their logistics operations. "Companies are increasingly looking at operational analytics—supply chain analytics, in particular—as a way to understand how their supply chains are really operating, what they cost, and how effective they are," says John Hagerty, a Gartner Inc. analyst who follows this market.
As for how companies are using these solutions, Hagerty says first and foremost, they're employing analytical software to get a better understanding of the factors driving their supply chain costs. In addition, they're using analytics to measure supply chain effectiveness, such as customer satisfaction with delivery performance. Once they see the results, they can zero in on the areas most in need of improvement.
Analytics are also being applied to get a better handle on demand—what a company needs to manufacture and what it needs to have in stock in the distribution center. "Analytics is being used much more aggressively to take external data, like customer demand, and translate it into a profitable response," says Hagerty.
But supply chain analytical software has the potential to do more than just prescribe a course of action. In the future, software experts say, these applications will be able to predict future developments so that companies can start making advance preparations. For example, Watson says, an auto parts store might use analytical software to look at the age of cars in its service territory to give it a better idea of what parts it will need to have in stock.
Companies could also use this type of software in their contingency planning. So-called "predictive" analytics can help managers assess future risks—like a product shortage or a jump in oil prices—and evaluate alternative responses. The advantages are obvious: Instead of being captive to events in times of crisis, a company would be ready with a detailed action plan to keep its operations running smoothly. For instance, if the price of diesel fuel were to soar, the company might start shifting shipments from truck to intermodal once prices hit a certain threshold or trigger point.
Given today's volatile environment, where an earthquake in Japan can lead to parts shortages in Southern California, companies have found there's a lot to be gained by regularly analyzing their operations and making data-driven decisions. "By running optimization once a month to create better supply chain plans," Watson says, "firms can continually drive down costs and make better decisions."
