Nov 20 2014
It’s been said that when art is truly great, it’s no longer available to be judged. Rather, great art judges us. In other words, if you hate Picasso, the problem is yours, not Picasso’s.
It’s a bit pretentious, as far as theories go, but the point is worth generalizing: real excellence isn’t measured by any standards but its own.
We’ve all heard a lot about the power of disruptive innovation. Even if the disruption is at times over-hyped, there’s no denying that upstart outliers can eventually rewrite the rulebook for even the biggest legacy companies. A great idea may look small at first, but eventually it could define a whole new set of expectations.
Examples are everywhere: sites like Buzzfeed and Huffington Post have changed the nature of publishing. Now Vice Media, once a localized magazine about music and fashion, is one of the world’s most successful and influential news outlets.
Plastic disrupted manufacturing. Email disrupted the post office. MP3’s disrupted the record companies. Smartphones have disrupted personal computing. And now Big Data is disrupting the retail industry.
Creating Opportunities, Not Just Finding Solutions
There comes a time in the lifecycle of a game-changing technology when people realize that the implications extend beyond what they originally calculated. Usually, the tools of the trade — devices, programs, software — solve a problem or improve efficiency in some way. Decision-makers can simply insert the technology into the relevant process and begin tabulating the ROI.
But when a technology comes along that suddenly delivers unanticipated potential, business leaders need to stop looking at fixes and solutions, and start looking for new opportunities.
Retailers and their product suppliers have been absorbing the impact of retail analytics and Big Data in various ways over the last decade. Some have used it to improve supply chain efficiency, or sell-through, or product forecasting, or marketing intelligence.
However, as companies start taking next steps and using Big Data-powered retail analytics more ambitiously, such as to create new products, they will also need to look at what structural components are in place to not only generate valuable insights, but also to bring them to fruition once they’ve been created.
Consumer Packaged Goods Companies Lead the Big Data Revolution
A recent report by the Economist Intelligence Unit, entitled Big data and consumer products companies: People, processes, and culture barriers, describes how Consumer Packaged Goods (CPG) companies can actually generate just as much data as headline-grabbing online companies like Amazon and Facebook, whether from POS data, supply chain tracking, or any of the multitude of consumer touch points.
According to the report, “Unilever alone claims that 2 billion people use one of its products every single day, while Procter & Gamble (P&G) handles over 4 billion daily transactions.”
Thus, through their rich and diverse data streams, even small and mid-size CPG companies carry the potential to lead the Big Data revolution. The challenge is to create a management culture that focuses on using data operationally to make real-time decisions.
The Courage to Share: Company-Wide Retail Analytics
Considering the potential benefits of an integrated approach to Big Data, both in CPG and across all retail industries, the issue of meeting the opportunities with suitable structures is an important one. But it also raises some bracing questions, as the EIU’s report suggests:
“What if the data suggest that sales of one product line is set to collapse, while another one is set to boom? Or what if they suggest that a new business model is more likely to succeed than the old one? Assuming the forecast is shown to be robust, are organizations brave enough to overcome their internal silos and fiefdoms to realign investment between different lines accordingly?”
While those questions are daunting, they also point in the direction that Big Data is going, where decision-makers no longer simply apply retail analytics to specific niches or product lines, but horizontally across the company, in order to draw the maximum benefit.
By letting those data streams flow together, companies can generate much more momentum and create a bigger impact. To see how your company’s POS data sets can be integrated to achieve companywide collaboration, try a demo of Askuity’s retail intelligence platform.