Too much data? - It's like walking through Jell-O

While I have been a marketing guy for most of my career, I spent the last few years working with an amazing team building out a data analytics function. We took on this challenge because it always seemed unnecessarily hard to get data. Seemingly simple questions would take days or weeks to answer. It quickly became clear - the issue was not lack of data, it was too much data. 

My go-to analogy for this situation: “Walking through Jell-O.” It’s doable, but it’s slow and unpleasant. Too much data is overwhelming. More specifically, too much unstructured data means that analysts and decision makers have to work way too hard. Often, they give up. 

Too much data can actually be worse than no data at all. When there’s no data, you make decisions with the best information you have. But, when there is data, you start to think, “Well, we could know more.” And that’s when decision making gets completely bogged down. 

So what’s the solution to clearing out this “Jell-O”? We can borrow an answer from Marketing: focus on the customer, or in this case the internal end-user. What are they trying to accomplish? What data do they need? When do they need it? How do we make their job easier? 

In most cases, end-users are decision makers who need information to make decisions “right now.” There’s no time to wade through Jell-O. The goal: Get the right people the right data in the right form at the right time to make the right decision. 

• The Right People: As in marketing, we need to start with who is using the data and why. It’s easy to just dump data on people. It takes more effort to understand who is making business decisions and what they actually need to know to do their jobs. 

Lesson 1: Spend time with end-users to understand what they need to do their job  

• The Right Data: Data needs to be accurate.  If the end-users don’t believe the data, they won’t use it. 

Lesson 2: Ensure high data quality to create credibility.

• The Right Form: Equally important, perhaps more, is that the data is in an easy to use form … with all unhelpful data removed. Making someone dig through unstructured data for a week to make a decision needed in the next hour renders the data useless. 
  
  Lesson 3: Make data uncluttered and convenient to access  
  
  
• The Right Time: Getting data too late is no more useful than no data at all. 
  
  Lesson 4: Ensure data is available when decisions need to be made 
  
  
• The Right Decision: Get the best available information into the hands of whoever needs it. Perfect data that is hard to get at, late, or unavailable to the key decision makers does not help the organization achieve its goals.
  
  Lesson 5: Design analytical tools for the decisions to be made

All of this seems fairly straightforward on the screen, but in real-life it’s easy to lose track of the end-user. Aligning data to decision making is fundamental to creating a more “self-aware” (or “proprioceptive”) business that is geared toward delivering on strategy.

If you are interested in talking more about how to ensure strategy gets activated and executed, visit www.proprioceptive.io or shoot me a note at jeff.sigel@proprioceptive.io.

Note: AI generated image.