Maybe you already know the story of Ron Johnson and J.C. Penney. Johnson, the retail superstar behind the Apple store and Target’s turnaround, was hired to bring Penney back to profitability.
Maybe you already know the story of Ron Johnson and J.C. Penney. Johnson, the retail superstar behind the Apple store and Target’s turnaround, was hired to bring Penney back to profitability.
But retail isn’t a one-size-fits-all proposition, even if you bring in a CEO with gold stars on his report card. By slashing prices and bringing in hipster apparel, the new CEO lost the retailer almost $1 billion. Despite his former success, he failed to address Penney’s core market of budget shoppers who prefer form-forgiving clothing.
The Wisdom of Data
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Think of how the situation would have been different if, rather than relying on intuition and dismissing data to the contrary, the Penney team looked at data to guide their plans. Knowing that their core audience prefers conservative clothing, Penney could have found appropriate new brands for shoppers. By reading the numbers of which types of pricing work best, Penney could have been more strategic about its discounting approach.
It should be a lesson for us all. Company leaders—CEOs and boards—should hold decision-makers accountable for making data driven decisions. Otherwise, the risk of a gut-based disaster like Penney’s becomes very real.
C-Suite Data Insights
It is not enough to simply say that decisions should be data driven. A CEO should hold each of her direct reports accountable for providing visibility into their piece of the data pie. No one should be making decisions based solely on intuition or gut. The CEO has to demand visibility into all aspects of the business, so she can make the best strategic decisions for the entire company.
The VP of Sales should provide visibility into the sales funnel for the quarter. In addition, he should be showing how this quarter is performing against the historical ramp, so problem with funnel can be identified early and action can be taken.
It is the CMO’s job to use data analysis to innovate new solutions for branding, company reputation, customer targeting and product pricing. Car insurance companies, for example, are delivering different rates to people who drive to the same destination, but use different routes to get there, according to Forbes.
The COO should be optimizing the company’s resources, from equipment to carbon-neutrality. Analytics make it possible to ensure that every moving part of the business is performing at benchmark levels and is in line with company budgets.
Using analytics, the CFO should discover new financial efficiencies across departments. He can trim the fat in an organization, reduce financial risk and use data to drive budget decisions.
Analytics provide a high level of detail about customers, and the systems driving this visibility are powerful and sometimes complex on the back-end. The CIO must ensure the health of all the IT systems behind the company’s big data analytics. If they’re in-house, the CIO should have a solid maintenance and tuning regimen; if analytics are SaaS-based, the CIO is in charge of setting them up and collaborating with service providers to ensure seamless execution.
The CEO Has the Final Word
By analyzing massive quantities of data from diverse sources, analytics can be used to pinpoint trends and new opportunities that otherwise would never be discovered. It is up to the CEO to gather information from each team member and decide how data results should best be used to increase the company’s competitive edge. Armed with data insights, she can use the collective experience to make the best decision. But for this to happen, the CEO is on the hook to make data and data visibility an integral part of the company’s culture.
Author: Chanu Damarla, Senior Director of Product Management at GoodData (@cd2k)
(image: CEO / shutterstock)
