By D. Douglas Graham
“If you’re a distributor, content is king,” declared Joseph Bennett, senior director, wholesale distribution services for Infor (www.infor.com).”Good clean data must be the foundation of any information ecosystem; a product information file being just one component of many. But the management of the massive amount of data required for file building is a journey not a destination. A product information archive is a work in progress for which constant maintenance is required. The file never stops growing, and he or she who maintains it, never stops working.”
Information is the lifeblood of an enterprise, but how does one identify data as business intelligence, and then harvest and manage it properly? This may prove a challenge for a small to midsized business, where all too typically employees go about their duties with heads full of highly specialized data about which they have a proprietary attitude. If one such employee has a bad day involving, say, a fatal traffic accident, his archive of knowledge will relocate with him to the next world. Here on Earth all intelligence is lost because it was not shared.
“Product information, no different than any form of business intelligence, is deployed to best effect when made available to everyone who needs it at the time it is most needed,” said Dominic Telaro, director of industry solutions, I.B.I.S. (www.ibisinc.com). “Since data lost to employee departures is potentially damaging to business, damage control should be preemptive. Find out and document what your most senior warehouse employee knows about widget B. If the computer shows you’re out but your employee knows where six cartons of B are tucked away, you’ll avoid double ordering an item for which six cartons are enough. That’s a small example, but it makes the point that product data inaccuracy can be expensive. On a larger scale it can cost enormously.”
Data should be collected and documented department-wide because it is via the lack of it that bad decisions are made. Mine the minds of your employees for minutia that will enhance the quality of the data base you’ve already compiled on individual products, vendors, costs, locations, quantities, etc. On a macro level, decisions misinformed by bad product data hit hard—a China deal gone wrong because it was transacted based on incorrect lines of cost. Product information inaccuracy exacts a painful penalty. Lacking an accurate data repository problems related to excess inventory, transport costs and other functions of business dysfunction may go unaddressed, ulcerating a company for years.
Across the Spectrum
Grab product data from across the entire spectrum of the enterprise, Telaro advised. Any effort falling short of that will give you a partial capture, which in some cases may turn out worse than capturing no data at all. Enterprise resource planning—which has the main job of integration of disparate data across the breadth of an organization—will collect such data, aided by tools that consolidate it and make it accessible to parties inside and outside the organization. What constituents relevant product information? Everything relating to individual SKUs, their cost and availability, the purchasing habits of customers that buy them…and so forth, so on, etc.
“When you talk about distributor data, an element critical to managing business intelligence is the ability to consolidate islands of information in a normalized fashion typically segregated in disparate systems,” added Matt Hartman, president/CEO of Tour de Force CRM (www.tourdeforcecrm.com). “Salespeople on the road typically have no choice but to consult multiple sources for crucial information. When data is consolidated to a single point of access he can get all the product information he needs via his iPad, not only on individual products, but on every company communication relating to them and his customer with potential to impact the sale.”
Selling in the age of the iPad sometimes calls for a pre-visit prognosis of a customer’s buying habits. This feature of product data management is known as “white space” or “gap” analysis. Say, for example, a salesperson wants to bring up all accounts within his database with a history of purchasing florescent lamps, with the object of identifying non-buyers. Should the salesperson convert a non-buyer to a customer, he need only consult his mobile device to determine whether or not he has sufficient stock on hand to satisfy the client’s immediate need.
“Product data management has many applications, one of the most practical the ability to quickly access information in order to better serve customers on a real-time basis,” Hartman noted. “Should a customer need 10,000 feet of conduit, the salesman can check stock with his mobile device and cut the order then and there. Product data management enhances distribution with accuracy and efficiency, and makes decision-making easier for everyone inside and outside the organization with a stake in the process.”
Doug Graham is a St. Louis-based freelance writer. Reach him at 314-394-0371.Tagged with tED