SmoothSpan Blog

We’ve all read the headlines about user-generated content, which has become a big deal in the modern Web world.  The rap is that only about 1% of that content is any good.  While many writers are down on the idea, 1% of the web is huge and growing like crazy, so it matters.  There’s another rash of articles dealing with user-generated metadata or user-generated structure.  These are all worthwhile concepts that show how people using the web can add back tremendous value. 

It’s the Data, Stupid is the title of a thought-provoking WSJ piece that made be think of another wonderful user-generated contribution.  Ben Worthen, the article’s author, has this to say:

One of the hottest techs right now is software that helps business people view and interact with their companies’ data. But none of this software will help a lick if the data you’re working with isn’t any good.

This is a huge problem for businesses right now.  There’s an old joke making the rounds of BI circles to the effect that the answers gleaned from the first BI project was great right up until the second BI project started producing answers that didn’t agree with the first, at which point we were worse off than before the first when at least ignorance was bliss.  According to Worthen, Accenture has surveyed businesses and learned that only 29% make data quality a part of their initiative.  Having worked in Enterprise software for some time, I can tell you that most of the data one encounters out there has problems of one kind or another.  Nearly any project has to deal with cleaning up the data well enough for whatever purpose it is to be used for. 

But during my travels, I came upon a unique situation where users were actually incented to massively improve the quality of the data.  I’m speaking of the Incentive Compensation experience at Callidus Software.  Most people don’t think about it, but there is a huge amount of data that must be collected to calculate sales compensation that is directly relevant to many questions on the revenue side of the business.  The data mart associated with such systems can easily answer questions such as:

• Who were the most important customers for each period and how is the relationship evolving in terms of repeat business?
• What were the most important products sold?
• Who were the best sales people?
• What were the best territories?

There are many more examples, but this data was solid gold for our customers.  I got this news at one user conference some years ago when I was essentially mobbed by a group of customers.  One of them indicated that while their title was VP of Compensation, they were producing reports out of the incentive data mart for virtually every functional organization in the company.  The reason people were looking in the comp datamart was that the information there was unusually accurate.  Since salespeople were being compensated on it, and since they had visibility to see the data through a web page our software provided, an entire group of people were suddenly motivated to clean up the data.  It helped that our software could actually reward them for doing this by going back and restating results.  The  VP’s of Compensation for these customers were demanding tools to help them with delivering this information to others, so eventually we built the TrueAnalytics product.

The moral of the story is to find ways to incent your users to clean up the data and they will do so, spectacularly.  But they need visibility and a reason to care before it can happen.