I was once told that the words “data analytics” make business executives go deaf. They are barraged daily with articles, blogs, consultants, salesman, and colleagues talking to them about the “power of data” and how everyone is going to lose their job to Sofia the robot.

It is a challenge to distil the signals from the noise about what data analytics really means for a business. What is the key information they need to make better decisions about data, and what is just garbage about the latest blockchain companies?

Often businesses get this horribly wrong and can spend millions trying to sort out their data, with some flourishing but most floundering. Acquiring highly skilled (or not) individuals to fulfil roles that are not needed, buying inappropriate software platforms or impeding workflows with analytics is not uncommon. These mistakes are often time consuming, costly, and cause many to shy away from data analytics.

You can’t blame them for getting it wrong, either. People are constantly being asked to make important investment decisions on data analytics teams, technologies and processes that they don’t fully understand, and frankly they shouldn’t have to. From our experience, people just want information to make better decisions and improve the way they work. This focus is often lost with data analytics, but, there are some things all businesses can do to improve the value they get from data analytics.

  1. Grasp the basics

Businesses often want insights, but they do not know what to do if they had them. If you know what decisions you need to make, then supporting those decisions with data analytics becomes straight forward. This step is vital in cutting through the noise.

  1. Know where you want to go

Once you have become aware of the decisions you need to make, then understanding what types of information you need to inform those decisions is key. Reams of charts on a complicated dashboard may look cool, but how do they actually inform the business? The key is being able to simplify the masses amounts of data into key insights.