Gartner's 2010 BI Magic Quadrant

Huh? Another “business intelligence” company?

The first time I heard “business intelligence” I thought it meant some psychological measurement like emotional intelligence. Or perhaps a euphemism for brains-on-a-stick management consultants. Talk about a branding failure. As it turns out the world is quite crowded with a whole bunch of business intelligence companies.

So why have we gone and started another?

1. SMBs are underserved.

To date business intelligence has been the province of big enterprise. If you’re a Fortune 500 company you need a BI system just so your left hand can figure out what the right hand is doing and you can report to the Street each quarter.

But if you’re a small or medium business you don’t have $100K and 3 months of integration time to blow on such a system. You probably use Excel…or nothing. There’s a lot of pain here.

2. SMBs don’t know all the questions.

A traditional BI system is like a super-powerful multi-purpose Swiss Army knife. When a big enterprise installs a BI system they hire a BI analyst to drive it and talk to it.

If you’re owner of a small or medium business you’re an expert in running your business. Even if a BI system has the answers you need, you don’t have the time or expertise to figure out the questions which will locate those answers hidden inside the data.

3. Hard computations are hard.

Some of those questions are hard to answer even with a powerful system. Multivariate regressions, cohort analysis, confidence intervals — there’s a reason why most people haven’t wanted to touch these since their college stats course.

It’s now fairly easy to whip together some models thanks to the wonders of Excel and pivot tables. However there’s still a sticking point when you want to bake that into your business processes and update it each week, or each day.

4. Real data is dirty.

Real data has little treasures like 30% stored as both 30 and 0.30, or zeroes where the data was unknown at the time, or misattributions because three fields all have the same label. These can make simple sums untrustworthy and utterly destroy more complex analysis. Garbage in garbage out. And if you’re small or medium business you don’t have an operations team to police the data for you.

5. It matters.

With all of the above difficulties, why should a small or medium business even try? Because data intelligence means they can run their business more quantitatively. It means they can put their tight resources to work more efficiently. Done right, it means they make more money.

Are you a small/medium business, or do you work with one? What are the #6 – #10 on your list of why small and medium businesses need better data intelligence?

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