Rules for Bankers to Follow When Using Data

One of the key hingepins of Capitalytics' offering is that your bank's data -- data about clients, employees, markets, and products -- can be used to provide a more profitable banking operation. By understanding the factors that drive revenue, both positive and negative, we feel strongly that community bankers can end up in a better place than they might otherwise find themselves.

As a result, we've found several common issues that typically plague bankers when they try to start a project that involves collecting data and analyzing that data in order to understand the proverbial "where they are" and "where they are going".

1. Define your hypothesis.

Do you have any idea of what you're trying to prove? Perhaps it is suspected trend in a specific market that you can position yourself to exploit. What's your basis for believing it? If you are correct, will implementing a solution or a strategy "move the needle"?

2. Plan to fail ... and adapt.

Hunches don't always work out. If you have identified a problem, but realize that you don't know what the solution is, how will you track down the root cause? Do you have the data you need in order to identify the root cause? If not, where can you find it?

3. Start small.

Now that you have a hunch about how to exploit or fix the problem, how do you cost-effectively begin to test it? Rather than investing thousands of man hours, can you scope the project to prove or disprove your theory and test your solution to it on a small scale ... geographically or otherwise?

4. Know what you can invest in the project up front...

How much "capital" (time, or relationship) do you have to invest in a project that will likely morph?

5. ...and what that maximal investment might return.

Make sure you manage the expectations of those involved, by knowing roughly what to expect in the best-case scenario.

6. Data quality is Job 1.

As we've said before, when it comes to your data and the decisions you make with it, "garbage in equals garbage out". What will you do when you encounter the inevitable imperfections or inconsistencies in your data? How will you ensure that your conclusions and decisions are based on accurate, reliable data and not the result of anomalies or inconsistencies in the format or semantic meaning of the input data?

7. Make sure that you aren't trying to swim against the tide.

You will likely find that most of your organization's problems are rooted in its cultural issues. Are you sure that your conclusions and recommendations will be embraced by your organization? And if not, are you willing to expend the effort necessary to change people's minds?

Contact us now to see how Capitalytics can help you design and implement a program to maximize your organizaion's operational returns!