JC Penney’s Data-driven Mistake and What We Can Learn From It

Don’t be blinded by big data.

That is the warning in a recent InformationWeek (gated) article and online discussion, pointing out that just because you have flashy, powerful, big data metrics, they are not the only valid or pertinent metrics. Recently ousted CEO Ron Johnson of JC Penney cited all kinds of detailed data to justify major reorganization for the company in 2012, and then made fundamental alterations based on it. Deep discounting ended, private labels would no longer be as emphasized, and online product lineups were slashed.

As we now know, the changes upset the company’s core market while failing to attract much new interest from other demographics or clientele, resulting in a sharp drop in sales overall: $12.9 billion in 2012, down from $17 billion in 2011.


JC Penney store

Johnson left the company, but the larger warning here is not that bold moves are bad; it’s that considering many factors is still the best way to make big decisions for growth and reorganization. Says InformationWeek: “Even in the age of big data analytics, getting the right answers is tough. In some cases, in fact, big data makes decision-making more difficult, and not for the reason you may think.”

In most organizations, big data mining prioritizes activities such as social media monitoring and macro trend analysis — the shiny stuff that can dazzle even experienced executives — while sidelining routine “little” data, which includes detailed financials, customer and vendor records, product quality information, customer service data, and supporting sales stats such as store traffic, website visits and CRM information.

We’ve said it before: it’s about balancing big and little data, considering many factors and trends to make the most effective business decisions. Flashy macro trend analysis did not serve JC Penney well. (On a related note, some major retailers are doing things right, expanding their business beyond traditional consumers.)

And right now, it’s up to many companies, large and small, to ensure they have some kind of data governance in place, beyond the care and management provided by IT departments. Data governance is about more than technical and security measures. It’s at the core of business decisions for sound growth, and the sooner you’re on board, the more effective you will be at grasping the whole picture for your organization.

What are some examples of great or terrible business decisions you’ve seen that were based on the wrong data?