Wednesday, October 2, 2013
Sharing Analytical Capacity
Most of us would be unsurprised to find out that Giant Eagle and Walmart use customer-level data to discover and exploit variations in shoppers’ tastes and habits. Many, however, may be surprised to learn that organizations further up the supply chain have partnered with their retail counterparts to analyze their customer-level data. An article in the Omaha World-Herald discusses how ConAgra uses retailers data to better source and price its products.*
The article cites one example of ConAgra’s number-crunching. A retailer asked ConAgra to evaluate customer habits pertaining to frozen foods. ConAgra found that people tend to buy single-serving frozen foods or family-sized frozen foods; they do not typically buy both. This led the retailer to redesign its frozen foods aisle, grouping single-serving products together.
Interestingly enough, ConAgra has thus far done this for free. The company nonetheless expects to extract some value from its analytics. First, given the size of ConAgra’s portfolio, its products will account for some share of any improvement in sales its retailers realize. Second, the more closely and more often ConAgra works with (or for) its retailers, the more ingrained it becomes in their processes and the more critical their relationship becomes for the retailers’ operations.
One of the themes of this week’s articles is that, while businesses are swimming in data, few companies have the technological or human capacity to put Big Data to work. The Ohama World-Herald quotes one author as saying that “two-thirds of consumer products companies don’t have enough [capacity for Big Data analytics].” It should come as no surprise that this particular article focuses on ConAgra, a behemoth food conglomerate. While that seems to corroborate the notion that only giant companies have the resources for handling Big Data, I think that it actually implies a novel solution for smaller companies’ limited analytic capacity. ConAgra and its retailers are united by their supply chain; the vitality of each member of that supply chain depends in part on the vitality of every other member. The insights derived from one member’s analytics can benefit the entire supply chain, just as we saw with ConAgra and its retailers. Perhaps members of a supply chain could band-together and scale out their analytical needs.
Question: ConAgra obviously benefits from the success of its retailers. After all, ConAgra is not so far removed from the grocery stores to which it sells. The farms and producers from which ConAgra buys are much further down the supply chain. How might one tie the analytical needs of those further up the supply chain with the front-end retailers?