The question then becomes, how can I fix things so that my users will start using the database again?
As I’ve written previously, when it comes to data accuracy, you have to have instilled in the organization a virtuous cycle of data management. Good data begets better data.
But beyond that, you have to rebuild the trust in staff that the data is accurate and being updated. And how do you do that? By changing what your users believe.
As consultant Alan Weiss points out, beliefs inform attitude, which in turn informs behavior. Or to invert the equation, in order to change behavior, you have to change attitudes, and in order to change attitudes, you have to change beliefs.
In this case, we have to change the belief that the data in the system is “bad.” So how do we do that? Here are a couple of suggestions:
In the scenario above, the users believe that the data is bad, thus their attitude is that the data and database are useless. Their behavior is reflected in that no one is actually using the database. By moving their belief to “the data is good,” through sweeping data clean-up, their attitude toward the data and the database will change, and in turn, their behavior will change.
A scenario like the one described above is not an overnight fix. The steps outlined above are a multi-month process. But the return on that investment will pay very high dividends for years to come.
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