More Data Means Better Insights & Greater Revenue – Right?

Everyone is telling you that you must have more data.  You have to know EVERYTHING about your fans, your salespeople, your building, and your business process.  If you don’t have access to every single data point related to your business you are going to be left behind.  This is the era of the Big Data Revolution after all.  That is why you are spending thousands of dollars appending your data, building your data management platform, and adding resources to your BI team.  Since more data means better insights and greater revenue, obviously, this is money well spent.

Or is it?

What is the value of data?

The conventional wisdom states: The more data a team has, the better their ability to generate sharper, revenue-producing insights.  Is that really true?  As far back as 2013, the Harvard Business Review questioned this convention, and even laid out a scenario that many of us in sports can relate to in the first paragraph:

“Companies are investing like crazy in data scientists, data warehouses, and data analytics software. But many of them don’t have much to show for their efforts. It’s possible they never will.” 

One of the reasons stated in the article is that organizations are expecting more value than data can actually provide.  At a macro level, more data just equals more data.  The value of data isn’t having more of it, and then storing it in one place.  Though many teams are paying for it like it is.  The value is in the analysis, actionability, and insights of the data you do have regardless of how much of it you have.

It shocks our clients to hear that some field of data has no correlation with sales results.  They paid a lot of money to acquire, store, and integrate data with the hope that they would find actionable insights. This is an expensive, inefficient and time-consuming process that more often than not results in minimal returns.

Reverse the process

The process shouldn’t start with collecting as much data as possible with the hope that the data will help achieve your business goals.  It should start with defining your strategic business goals, and then identifying which fields of data can help provide the insights needed to reach those goals.  By reversing the conventional process you accomplish three things:

• Provide a clear link between your data strategy and your strategic business goals
  This is a no brainer.  Building a data strategy around strategic business goals guarantees your data has a direct impact on business results.
• Increase efficiency by prioritizing “need to have” over “nice to have” data sets
  The process for integrating and storing data can be quite laborious.  It can last months and even years if you attempt to store all of your data. However, by identifying which data sets are important you expedite the integration time considerably.  Which means analysis happens at a much faster pace.
• Reduce costs by only paying for the data you need, and not the data you don’t
  This may seem like an obvious point, but most teams pay entirely too much for data that has no inherent strategic value. There was a time when data consumers had no choice but to pay for expensive bundles of data in an all-or-nothing model.  Providers of data and sellers of antiquated data storage technologies had every vested financial interest in utilizing fear tactics to buy more robust packages than were needed to effectively derive actionable insights from data.

It’s time to “cut the cord”

The world is rapidly changing, though. Consider that cataclysmic shift in how we are buying entertainment content. Cord cutting has grown by 50% in the past 8 years – as consumers have discovered that there is a better way to watch their favorite sports team or catch an occasional movie than paying for 700 channels that they will never watch. In other words, less is more.  The big data world is no different. By reversing the purchase process, and investing in that which delivers value, you save money while ultimately driving revenue.