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SmartData Collective > Big Data > Data Mining > Top-Down Business Intelligence
Business IntelligenceData Mining

Top-Down Business Intelligence

MIKE20
MIKE20
5 Min Read
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“A good plan is like a road map: it shows the final destination and usually the best way to get there.”

Contents
A Familiar Scenario?The Wrong QuestionsFeedback

–H. Stanley Judd

“A good plan is like a road map: it shows the final destination and usually the best way to get there.”

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–H. Stanley Judd

I recently had the opportunity to attend IBM’s Information On Demand Conference in Las Vegas, NV. At breakfast one day, Crysta Anderson of IBM, two attendees, and I talked about some BI implementations gone awry. In this post, I’ll discuss a few of the key problems that have plagued organizations spending millions of dollars on BI products–and still not seen the anticipated results.

A Familiar Scenario?

Recognize this? An organization (call it YYZ here) is mired in a sea of individual reports, overwhelmed end users, bad data, and the like. The CIO hears about a competitor successfully deploying a BI tool, generating meaningful KPIs and insights into the business. After lengthy vendor overview and procurement processes, YYZ makes the leap and rolls out its new BI toys. Two years later, YYZ has yet to see any of the expected benefits.

Many of you have seen this movie before.

So, you’re the CIO of YYZ and your own future doesn’t look terribly bright. What to do? Blame vendors if you want. Consultants also make for good whipping boys. Maybe some regulations stood in your way. And there’s always that recalcitrant department or individual employees who didn’t get with the program. But I have one simple question for you: Where did you start?

As we discussed at that table at the IOD conference, many organizations get off on the wrong foot. They begin their BI implementations from the bottom up. In other words, they take a look at the myriad reports, scripts, queries, and standalone databases used–and not used–and then attempt to recreate all or most of them in the new BI tool. Thousands of hours, hundreds of thousands of dollars, and months of employees’ time are spent replicating the old in the new.

The Wrong Questions

There are two major problem with the bottom-up approach. For one and most obvious, not all reports are needed. The core–and faulty assumption–is that we need tomorrow what we needed yesterday. As a consultant, I personally have seen many people request reports in the “new” system that they would never run. When I would ask a question about the purpose of the report or the ultimate destination, I would far too often hear crickets.

Beyond superfluous reports, there’s a deeper problem with bottom-up BI: it runs counter the whole notion of BI in the first place.

Let me explain. At its highest level, cubes, OLAP, data mining, and other sophisticated analytical techniques and tools all start at the top. That is, the conversation typically begins with high-level questions such as:

  • Who are our best customers?
  • Where are our profits coming from?
  • Which products are selling best in each area?
  • Which salespeople seem to be struggling?

An organization cannot start a BI implementation in the weeds and expect to be successful. It needs to start with the right questions, define its terms, and clean up its data. Only then can it begin to see the fruits from the BI tree.

Simon Says

Fight the urge to “just do it” when deploying BI tools. Failing to reassess core business processes, KPIs and metrics, and data quality issues are all recipes for disaster. Consultants and vendors who believe that you can just figure these things out mid-stream should be ignored.

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What say you?

 

TAGGED:BI Issues
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