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Picking up from Tuesday’s post about the Three Big Lies in Data

I give you…  the World’s Most Honest Scorecard!  


In Moments of Honest Reflection, Most Organizations Would Acknowledge that
this Describes their Relationship with Data

The Most Important Numbers Generally Don’t Exist


The two graphics above kinda “steal the thunder” of this point, but I’ll elaborate anyway.  One of the grandest surprises for me, after leaving Microsoft, is just how blind the world is to its own data.


I think the biggest problem in the world of data today is STILL that we simply DO NOT HAVE the “numbers” we need.  Call them metrics, values, KPI’s, whatever – they are numbers, about your business, that would inform/drive improvement.

Pause and let that sink in for a moment, because a) I am 100% confident in saying it   and b) I think it’s time we admit that to ourselves.  How can we expect tools vendors (or the Gartners of the world) to be talking about that if WE ourselves aren’t willing to admit it?

It’s OK, Everyone.  Let’s Have a Group Hug.

imageNo one should feel guilty about this hard truth.  I’ve interacted with hundreds of companies, in one way or another, since leaving MS.  And NONE of them had all of their important numbers.  (Yes, absolutely – some were farther along than others, but to even having 40% of your “needed” metrics would earn a gold medal at the Olympics).

In fact, that is the reason clients come to us in the first place – they have data, and they need help turning it into information.  So you’re not alone in this, far from it.

We are just NOW reaching a crucial intersection of tools and awareness to change this reality.  There was, quite seriously, no way to avoid this “we lack our numbers” reality until now.

Where does this lead?  It all leads back to an “unsexy” term.

We need models.  And no, not Giselle Bundchen.  I mean “engines that turn data into information, and that can quickly/flexibly answer varied questions about that data.”

Furthermore, we need models that can be built QUICKLY, and quickly adapted to changing needs and awareness.  SSAS Multi-Dimensional Cube technology – the forerunner of Power Pivot – was/is great at modeling.  But in practice, it is too cumbersome to pass the “quick/flexible” test.

Next Week

I will come back to this with some tangible advice on how to actually evaluate tool sets.  Things you should ask vendors, things you should ask yourself, and principles you should consider.

Rob Collie

Rob Collie

One of the original engineering leaders behind Power BI and Power Pivot during his 14-year career at Microsoft, Rob Collie founded a consulting company in 2013 that is 100% devoted to “the new way forward” made possible by Power BI and its related technologies. Since 2013, PowerPivotPro has rapidly grown to become the leading firm in the industry, pioneering an agile, results-first methodology never before seen in the Business Intelligence space. A sought-after public speaker and author of the #1-selling Power BI book, Rob and his team would like to help you revolutionize your business and your career.

This Post Has 12 Comments
  1. Wow, what an interesting post. The info in those charts is kind of crazy to say the least and so are the ramifications.

    For years, the world of data analytic tools has kind of operated like the emperor’s new clothes: everyone praises King B.I. on how beautiful his clothes are only to find out that in reality he is somewhat naked. Maybe that’s a bit harsh, but I do think that when facing these charts and being armed with Power Pivot and knowledge on how to use it, some great opportunities may be ahead whether everyone realizes it or not. King B.I. can actually get some awesome clothes if using the right tools and skills/knowledge…

  2. I’ve been pretty successful at conditioning the management to describe their “pain points”, the “why” questions that they are asked, rather than requesting reports. With this higher level of insight I can usually assess their data needs much better than they can, not to mention what format (report, scorecard, dashboard, etc.) will serve them best. So often we “techie” people rush off to deliver what has been requested without understanding the need in the bigger view. It is very hard to push back when a VP makes a request, which is why I’ve talked with all of them to help them understand that turning data into “intelligence” requires insight. They usually understand, so long as I have laid the groundwork ahead of time. A bonus is that some of them have started to do a better job of assessing their needs themselves.

    1. I’ve experienced the same thing Colin! I used to ask management for the information that they want to see on their report (names of columns, etc.). That lead to disastrous results because most don’t know what they want until they see it.

      Recently I have focused on “pain points” and “why” as you put it and now I’m able to get to what they want a lot faster.

  3. Rob, it feels like you are teasing us. Is this Step 1 in a Twelve-step recovery program? Admit that you have a problem 🙂 Jokes aside, I do agree with you. Organizations are flying blind most of the time. I feel the ones that have no metrics are better than the ones which have ineffectual metrics; at least the former are not operating under any delusions.

    It seems for this series you will focus on “models” But the human element is equally or perhaps more important. The ‘Data Gene’ people that you have mentioned in the past. Even with the right ‘Data Gene’ people around, it is a time taking process. As the ‘Data Gene’ person shepherds the whole organization on this journey. At the last Seattle Modern Excel Users Group meeting we got a chance to hear Seth Brickman speak about the BI transformation at Holland America. And he repeatedly emphasized working with people, the customers as well as his own team. The whole transformation took two years, and the journey still isn’t over (may be it never is).

    Having said that, they did use Power Pivot and I do believe Power Pivot is the magic elixir, the catalyst that makes these transformations possible and speedy. Just remember to slow down for others on the road as well 🙂

    You can read a boring version of Seth Brickman’s story here (he’s a truly great speaker and his live version was as engrossing as any Disney tale)

    1. Heh heh I am glad it sounds that way. I’ve just seen enough at this point that I can confidently say this is basically universal.

  4. Hi Rob, a fantastic post. Can’t agree with you more. The two charts are very interesting and insightful. Now i want to read your thoughts on evaluating tools, etc. When is the next post on this series please?

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