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Data Strategy: Success or Failure

A data strategy can mean the difference between profitable growth and your business imploding.

Let me explain…

The CEO was furious.  His face was a crimson red and there was a vein bulging in his neck – I don’t know about the others in the room, but I was a little concerned about his heart.

He was, to put it bluntly, pissed about his inability to get an accurate read on the business in real-time.  He wanted to know about revenue and expenses.  He wanted to know about sales and marketing.  He wanted to know about customer service and support.

And he wanted to be able to turn on his computer, log-in and have one screen that he could look at for real-time, up-to-date accurate answers.

He finally got that initial blast of frustration out of his system, stopped to breath and try to regain his composure.

And, as you can easily imagine, there was an uncomfortable silence filling the room.  Most of the people where sitting there trying to figure out how they might be able to become invisible or transport themselves out of the conference room.

Then the head of IT chimed in with “We can get you that…that’s easy.”

And he was only partially wrong.

You see, the key to the knowledge the CEO was seeking requires a strategy – a data strategy.  And that strategy requires everyone to understand what questions need to be answered.  And then you need everyone to agree on what data is necessary to answer those questions.  And then you all need to agree on acceptable sources to use for gathering the information – because you don’t want to spend all your time creating reports that turn out to be the reason for the CEOs next melt down.

  • What do you want to know?
  • What do you need to answer those questions?
  • What do we have now and do we trust it?*
  • What are acceptable sources of data in addition to our own internal sources?
  • Who is responsible for gathering that data?
  • How will those responsible gather that data?
  • How will those responsible ensure the data is current, clean, accurate on an on-going basis?
  • Where will it be stored so it is safe  and secure yet easily accessible for those with authority to see it, handle it, work with it?
  • How will it be analyzed?
  • How will that analysis be presented to those people that need to develop practical recommendations for next steps?
  • Who needs to approve the recommendations so action can be taken?

* This is where you need to spend some time making sure you know what you have and agree that it is of an acceptable quality.  That means a data dictionary that defines what data is captured in each field – rather than everyone sitting around thinking they know what that data in that field really means.  (Some of you may laugh at that…but one of my ‘favorite’ things to do is ask “why do you have X in three different locations in your CRM?”  And the reason is, typically, “…I don’t know why that one is there, it was there when I was hired.  This other was put in when the former head of sales asked for it…and I am not sure how it is being used today because when he left, I noticed that the sales team wasn’t using it all that often.”

That’s your step-by-step guidelines for creating a data strategy.

Note: There are other questions – what’s mission critical?  What are the requirements for keeping data fresh/accurate/clean?  Security and back-up issues.  And more…but this is a post about the high

Why is this important?  Because it will save time.  It will save money.  It will avoid on-going arguments over “I don’t trust the report” or “I don’t like that data”.  It will help your organization get behind the use of data so they understand how they need to do a better job collecting the right data and storing it in the right place.  And it will help your organization make better informed decisions that drive improvements in those key areas that mean the difference between profit and loss.

Let me give you a real world example of what the alternative is…

The CEO ends his tirade and the head of IT tells us all it’s easy to do…so the head of IT goes off and starts putting together a dashboard based on what he/she thinks is the solution.

A week later, at the next big meeting, he/she presents the work…and the rest of the hour is spent, typically, in one of two ways.

Option A is the CEO thanks the head of IT and everyone else in the room remains silent.  Then, over the course of the coming weeks and months, the CEO and head of IT refine the work – coming to conclusions that no one else in the organization believes is an accurate reflection of reality.  Eventually people start bringing their own data and reports to the room in an attempt to prove that “my version of reality is better than your version of reality.”

Option B is that the people in the room start poking their fingers at the work done by the head of IT…not in a “…the best way to look at this data is X, not Y, because…”  Nope, instead it’s more along the lines of “…that’s not the right way to look at the data because…”  And the end result is 60 minutes of everyone calling B.S., refusing to accept the quality of the data or the quality of the recommendations – as well as the implications that “…your version of reality is so much more negative than mine…”

The reason you want to invest in the approach I put forth earlier is that it gets everyone involved in creating the solution.  It gets everyone involved in sharing those little data secrets that they have with the data they work with all the time … and that are unknown to the rest of the company, including the head of IT.  It forces everyone to agree that the course of action is the best at this time and that everyone should be working together in order to identify ways to make it better, more accurate.  And it sets up a process for further discussions on how to improve the capture, storage, analysis and reporting…because you’ve created a collaborative environment focused on getting the most out of your resources.

Over time, you will all get better at this.  You will enjoy those ‘A Ha’ moments where someone realizes that an overlooked source of data could have a huge impact on your analysis and recommendations.

Got questions? Want to share your own experiences?  Feel free to leave a comment or contact me…I would love to talk with you.



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