In the retail and consumer package goods market, data management has been at the heart of inventory and forecasting improvements for more than a decade. In the aftermarket, however, many companies are only now coming around to the idea that the massive amounts of data generated at the point of sale should be leveraged to manage what inventory goes where, from the point of manufacture to the shelf.
At the Aftermarket eForum conference May 22-23 in Chicago, four experts from every level of the supply chain converged for a panel discussion to talk about the way the industry can embrace better data management. Increasingly, the aftermarket will need to leverage Big Data to get a better handle on forecasting and inventory management to reduce returns, reduce inventory costs, and to make sure that inventory is positioned properly at the store/installer level. In an industry trying to adapt to both an exploding SKU count and increasing number of low-volume parts, a data-based approached to inventory is critical.
That requires increased visibility, says Rod Bayless, product director at Epicor. "If you can't see what's going on in the channel, you can’t measure it, and you can't do anything about it," Bayless says.
"If we can't provide correct data, we can't make a sale," adds Mike Buzzard, director of marketing at Uni-Select. "When you tie this to revenue, people start to pay attention to it."
The problem with current forecasting models, though, is that the aftermarket channel is full of low-volume products that don't generate enough sales data to provide an accurate picture of demand. Bayless characterizes this as a business intelligence gap. "The forecasts are starving for data," Bayless says. "Traditional analytics don't work at the end of the channel. You don't know enough to compete, and you need help."
Program groups are investing in inventory visibility and forecasting technology, layering a variety of data into proprietary forecasting tools to help distributors and jobbers better match their inventories to actual demand. That includes vehicle registration data and replacement rates, but for the data to be truly useful, regional knowledge has to be integrated. That could, conceivably, even include search engine data related to specific repair problems.
"We're starting to get where we can forecast for specific regions more accurately," Bayless says. Better visibility could even help manufacturers know when they have over-produced certain parts.
Another problem is the lack of consistency when it comes to data quality. While adherence to the industry data standards has improved, suppliers and distributors are still finding hundreds or even thousands of mismatched SKUs in their databases. That poor data can lead to a "bullwhip" effect in the supply chain, causing wild swings in demand and increases in safety stock. "If you have bad data, it can cause a lot of unnatural acts to occur related to inventory," says Steve Sigg, e-business manager at AC Delco.
AC Delco has been engaged in a master data management (MDM) project, leveraging the PIES and ACES standards, to clean up its own product data. Internal testing showed that the company had thousands of mismatched part numbers moving between the company and its distributors, and the problems were split evenly down the middle; some of the bad numbers came from AC Delco, others from the its distributors themselves.
"Our focus has been on getting our own data in sync internally," Sigg says. He added that segmenting data by type of customer is also important; otherwise it's difficult to leverage the data in meaningful ways when it comes to re-allocating inventory.
While more companies now use the PIES and ACES standards, synchronization issues still plague the aftermarket. "I don't think data synchronization has improved much, but we are seeing a bigger focus on MDM, and building the PIES database," Bayless says. "There's been an attempt at many companies to build better practices."
Cleaning up that data is a huge undertaking. "The biggest barrier to entry is doing the tagging and normalization of the data," Buzzard says. "But that's critical, because if you don't take those steps up front, everything coming out the other end is garbage."
Data guides inventory decisions
Accurate data, and more of it, will help fuel forecasting engines and the internal inventory process. Many companies have also turned to category management. "That means not just figuring out what the assortment is, but determining whether you have the demand to support that assortment," Bayless says.
The companies on the panel have taken a variety of approaches to improving visibility and leveraging data. Uni-Select, for instance, has established its e-Modeling tool for jobbers to help manage inventories, and it combines data on local demand, customer sales and other information. "All the transactional data goes into e-Modeling," Buzzard says. "That makes it easier to use the tool to get he right parts on the shelf."
Tenneco leveraged highly specific market data to help launch a new product line. According to Joe Pase, director of category management and strategic planning, the company wanted to identify installers that were likely to buy the new product using a variety of data inputs. Eventually, they were able to identify 82 specific installers, and the sales team contacted them in advance of the launch.
"We had great results," Pase says. "It was our best sub-line launch ever. We made better decisions about where to place that inventory."
Tenneco is something of an exception among suppliers. As Bayless notes, "There is not a manufacturer that isn't getting POS data, but few of them are doing anything with it." One problem seems to be lack of resources to manage the data, an activity that requires a dedicated staff – sometimes a fairly large staff, at that.
Even at Tenneco, the data wasn't leveraged in any real way until recently. "There was a three- or four-year period where we had data coming from anybody who wanted to supply it to us, but we never opened the hood," Pase says. "Once we really took a lot at what was happening, it really opened our eyes. Now, we know that if we are best in class in managing this data and our inventory, that gives us an advantage."
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