Steve Carlotti, CEO of the company where I work, likes to say: "Sales is what you buy. Demand is what you want. Growth comes from bringing the two together." As companies try to exploit the opportunities presented by Big Data, the difference between those two things is an essential insight.
Most executives assume that sales equal demand. Very often, this couldn't be further from the truth. The challenge with sales data is that it is too superficial. First, shopping occurs at the household level, but demand is at the individual level.
Take the last grocery bill for beverages for my family of five. There are no beverages that our entire household all consumes. Four out of five of us drink milk, three out of five drink juice, two out of five drink coffee, and just one-fifth of us prefer enhanced water.
No sales database can tease apart these nuances, and if you're simply measuring sales, it's hard to tell who in my family represents demand for each of these products. Also, the past does not predict the future. For nearly all the categories above, we were buying different variations (e.g., soy milk, almond milk, organic milk) and brands of each six months ago.
Finally, sales don't equal demand because consumers settle for less far more often than most realize. Consumers are forced to buy hot dogs and hot dog buns in different pack sizes. Socks come in a handful of sizes when shoe sizes range in 20+ lengths with 7+ widths, for a total of 140+ permutations. Twenty-nine percent of beer drinkers don't like the taste of beer! Between out of stocks, suboptimal assortment, pricing inefficiencies, difficult POS experiences, misaligned brands, and redundant innovation, I'd be surprised if consumers were happy with more than half their purchases.
If the challenge of analyzing sales data is breadth, the challenge of profiting from demand data is the inverse: It requires such depth that purpose, practicality and profit get lost. Demand data comes in the form of market research, demographic/behavioral databases, and more recently in social media and search, all of which require you to wallow in the primordial soup of unmet needs to figure it out. Demand is primal. I've seen consumers cry when given just the right stapler because being neat and organized is part of their identity. I've seen people wax poetic about how a basic bar of soap can be a passport to paradise, if even for just 10 minutes. It's easy to overlook the profound, Pandora's Box of human emotions that even the most commodity of products can unlock, because each of us has profoundly complex and uniquely rich stories. Demand is also paradoxical. Consumers frequently say and do very different things. The 29% of beer drinkers who don't really like beer are reluctant to say that out loud. Finally, 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. That enables research to be linked to resource allocation and ROI and ensures purpose and practicality won't be lost along the way.
While sales and demand data have their own challenges, the biggest upside will come from better integration across both, as well as a third area of data we have yet to talk about...what people watch. I am a consumer (demand data), shopper (sales data) and watcher (media data). Yet most companies are focused on going deeper in one area, instead of integrating across all three. The challenge is that the keys to each of the three datasets are held by different companies: consumer (manufacturers), shopper (retailers) and watcher (media). Even the digital area is still fairly fragmented across consumers (Facebook/Twitter), shoppers (Amazon) and watchers (YouTube/Netflix), though some are trying hard to get to all three like Google (Google +, search, YouTube) and Amazon (reviews/ratings, retail and Prime videos).
This is why big demand data will require renaissance executives who are both right and left brained, schooled in anthropology and accounting, who are equally skilled in using a microscope and telescope to solve problems and find growth.
Source: http://blogs.hbr.org/cs/2012/10/demand_and_sales_arent_equivalent.html
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