Five rules for the data-driven business

What is the most valuable asset a business has? There are a number of potential answers, but for most businesses today, one of them is 'data'.

Thank technology for that. Most businesses, no matter what industry they're in passively collect data that can be analyzed to provide deep insight. From point of sale systems to computerized record keeping software to web analytics solutions, businesses have a wide range of tools that collect data on a 24/7 basis.

More and more businesses are getting smart about how they collect data, and are giving analyses of this data a prominent place in their decision-making processes. But becoming a data-driven business isn't easy. There are plenty of pitfalls that can turn data into a liability.

Here are five rules for data-driven businesses looking to avoid those pitfalls.

Remember that you can collect too much data

More and more businesses have recognized the importance of collecting data and analyzing it to drive important decisions. That's a good thing. But many make the mistake of collecting as much data as they can find. This is not only distracting; it can reduce the quality of data-driven decisions because those decisions are only as sound as the analyses they're based on. When too much data is collected, there's a greater likelihood that the wrong analyses will be performed.

Key metrics derived from data should be tied to goals

Numbers in and of themselves are often of limited use. Sure, knowing, for instance, that your company spends, on average, $40 acquiring each new customer is a good thing to know. But how much should you be spending acquiring each new customer? Chances are that's a lot more important, which is why, in many if not most cases, metrics should be associated with goals.

Context helps

When setting goals, context is your friend. Back to the customer acquisition example: what is the average cost of customer acquisition in your market? What reduction in customer acquisition costs would boost income by 10%? By adding context to your equation, you can make sure that the goals you've tied to key metrics are meaningful to your business.

The past and present aren't the future

Data is inherently limited to yesterday and today. Predictive analytics solutions apply yesterday and today's data to anticipate what the future might look like, but predictions, no matter how sophisticated, are still just predictions. The data-driven business uses data to make educated decisions; it doesn't naively believe that data is a crystal ball.

Don't dismiss the qualitative

Hard data is wonderful, but if you're only paying attention to the hard data, you're missing out on a huge part of the big picture. How do your customers relate to your products and services? What is most important to your stakeholders? These are questions that can help guide a business down the right path, but the most important aspects of the answers to these kinds of questions won't always be provided by numbers that can be crunched.

Published by: econsultancy

Published 22nd November, 2010

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