Getting off the data treadmill

Getting off the data treadmill

Getting off the data treadmill

Most companies start their data journey the same way: with Excel. People who are deeply familiar with the business start collecting some basic data, slicing and dicing it, and trying to get a handle on what's happening.

The next place they go, especially now, with the advent of SaaS tools that aid in everything from resource planning to sales tracking to email marketing, is into the analytic tools that come packaged with their SaaS tools.

These tools provide basic analytic functions, and can give a window into what's happening in at least one slice of the business. But drawing connections between those slices (joining finance data with marketing data, or sales with customer service) is where the real value lies. And that's exactly where these department-specific tools fall down.

So when you talk to people in that second phase, understandably, they're looking forward to the day when all of their data automatically flows into one place.. No more manual, laborious hours spent combining data. Just one place to look and see exactly what's happening in the business.

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Once you give people a taste of the data and they can see what's happening, naturally, their very next question is, "Well, why did that happen?"

And that's where things break down. For most of the history of business intelligence, the way you answered "why" questions was to extract the relevant data from that beautiful centralized tool and send it off to an analyst. They would load the data back into a workbook, start from scratch on a new report, and you'd wait.

By the time you got your answer, it was usually too late to use that knowledge in making your decision.

The whole thing is kind of silly, though -- you'd successfully gotten rid of a manual, laborious process and replaced it with one that is, well, manual and laborious.



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