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  • Mark Herman

The Perception Misconception for Decision-Making

When I look back on my career I realize how many strategy sessions, decisions, meetings and conversations I’ve participated in that were based on what I call “Perception-Based Management”. You know what I mean. Things like:

  • Traditional – “This is how we’ve always done it.”

  • Experiential – “Because when I was in that role . . ."

  • Assumptive – “I know Accounting will love it if we do it this way . . ."

  • Presumptive – “We made money last year, so we’ll be fine this year.”

  • Small Picture – “Sales are up, so we must be doing well.”

At the risk of being assumptive, I think most of you can relate to some or all of those perception-based management techniques.


But, the business world is quickly finding out that perception is no longer cutting it in today’s competitive marketspace. Questions like:

  • What’s our “real” cash flow?

  • What’s our optimal purchase quantities?

  • Where should our Marketing dollars be spent?

  • What’s our Production or Sales forecast?

  • Which product lines are killing us?

  • How can we prevent unplanned downtime?

All of these are valid questions that require forward-looking answers!


While a crystal ball would be nice, the truth is that today’s competitive landscape requires decisions grounded in “fact-based, forward-looking” information . . . which can only come from extensive analysis of your company’s data. ALL of your company’s data.


And that’s where Data Analytics comes in. Each of the questions posed above can be answered using your data and basic analytic techniques.


What exactly is data analytics? Well, let’s try to explain it like this.


Assume you have three doors with no way of seeing through them. You’ve been told there’s a treasure behind one of them, but you can only open one door. In this situation, your confidence in succeeding wouldn’t be very high, would it?


Now, imagine there’s a keyhole in each of the doors which allows you to see inside the rooms. Aha, now I’m pretty confident you’d pick the right one, correct? And that’s what data analytics does. It provides that insight into areas that prevents us from having to guess at our answers.


Contrary to what you may have been told, data analytics is more than just a reporting tool. Data analytics is the “collection and comprehensive evaluation of data from different sources – core business units, shop floor equipment, 3rd-party add-ons, external providers - to provide enterprise-wide, forward-looking, decision-making capabilities” for use in the following formula:


Data + Analysis Techniques = Data-Driven Decisions


Data-Driven Decisions. The new term which, I believe, is moving past “Digital Transformation” as the new buzzword in the business world. And, rightfully so.


Forrester reports that data-driven companies grow more than 30% annually on average. Which means if you’re not using your data to make decisions you will quickly fall behind your competition. The somewhat good news, however, (also according to Forrester) is that only 31% of companies consider themselves data-driven, which still leaves you time to get a leg up on your competitors.


There are 4 major types of analytics on which data-driven decisions are based:



Descriptive – What’s Happening in My Business?

  • Details current and past events.

  • Most frequently used type of analytics.


Diagnostic – Why Is It Happening?

  • Often accomplished by “drill-down” dashboards to find the source of a problem.

  • Where most companies stop so far as analytics is concerned.


Predictive – What’s Likely to Happen?

  • This is where you first start getting an edge by applying modeling to your data.

  • Allows you to start doing forecasting based on current events using co-dependent variables.

  • Example: Cycles, temperature, oil pressure can all predict machine maintenance intervals.


Prescriptive – What Do I Need to Do?

  • Uses machine learning to recognize and react to patterns in your data.

  • Provides ability to overcome future challenges.

  • Example: Optimize purchasing through analysis of Supplier and Logistics variables.


As you can see in the illustration, Descriptive and Diagnostic are more “backwards-looking” tools, while Predictive and Prescriptive move you into “forward-looking” solutions.


As you move from backwards to forward-looking analytics, your value on your data investments increases as you start getting more results from your efforts.



So, it’s time to move on, folks. No more guessing. No more throwing darts at the wall. The time for moving from perception to data-driven reality is now. You’re spending a lot of money to generate volumes of data on a daily basis. Isn’t it about time you start getting a return on that investment?


Interested in Analogyx BI? Click here for a Free 7 Day Trial! Other videos in our ABI Role Call series:

E1: Accounting Receivables E2: Sales E3: Production E4: Executives E5: Marketing

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