Do You Have a Handle on Demand?

In a recent Harvard Business Review blog, Eddie Yoon points out an important distinction — demand and sales data are not the same. Yes, retail teams — for the most part — have realized the value of business intelligence (which is often called demand intelligence). But Yoon makes an interesting and important distinction. “Sales is what you buy. Demand is what you want. Growth comes from bringing the two together.”

Today, the real opportunity for sales growth is in analyzing historical POS data in context, using a business intelligence (BI) solution, and pairing that with demand data from other sources. As critical as it is to use your BI solution, as Yoon notes, “If you’re simply measuring sales, it's hard to tell who in my family represents demand for each of these products... sales don't equal demand because consumers settle for less far more often than most realize.” And it’s a valid point. While a consumer may purchase regular orange juice, it just may be the purchase was made because their favored no-pulp version was out of stock. In cases such as this, a past sale does not predict a future sale; and there really was no demand for the regular orange juice in the first place. But how is a retail team to know this?  

What is “demand”? And how do you identify it? Yoon identifies demand as something “primal” — a decision made by a consumer because of who they are or what they’re feeling. As he notes, “Demand is primal. I've seen consumers cry when given just the right stapler because being neat and organized is part of their identity.” He continues, “It's easy to overlook the profound, Pandora's Box of human emotions that even the most commodity of products can unlock…”

While consumers often state they “love” a particular product — such as a Coach purse — they may never, ever purchase one simply because it is beyond their means to do so. Another example is the “Made in America” ethos. Consumers may say they want and will buy things that are made in America, but if the cost of these items is higher than a similar item manufactured outside our borders, they often will opt for the less expensive (and not-made-in-America) item. As Yoon notes, “ “Demand is also paradoxical. Consumers frequently say and do very different things.” This, of course, makes predicting demand a challenging task for retail teams.

Does this mean POS data is useless? Certainly not. The idea here is to use POS and demand data in tandem in order to get the whole picture. Where can you get demand data? Market research, social media, demographic and behavioral databases are good places to start. As consumers increasingly use multiple channels to research and shop, retail teams need to realize that “…demand needs to be measured in profits, by quantifying the economic value of a Facebook Like, a Google search, or a top two box score on a survey.”

 The key to understanding your business is to integrate and analyze all types of data (demand, sales and also media), because people who buy your items contribute to all three areas. So the question we pose is this — if you’re already analyzing your POS data using a BI solution, what are you doing to assess the demand portion of your targeted consumer business?