Data quality decides whether a data-driven strategy works

We have plenty of data these days. Enormous amounts of it. We measure, we collect and we dashboard our way through the week. Let’s be honest though: there is a wide gap between having a lot of data and being able to do something with it.

If you want to make real work of growth, innovation or a strategy that holds up, your data has to be in order. That goes beyond how you store it. It is about quality, relevance and usability.

So suppose you are responsible for data-driven working in your organisation. How do you make sure your data actually helps with product development, marketing, sales and building an edge over the competition?

Here are a few things that help me in conversations with clients and in internal decisions.

1. Start with the question, not with the data

What do you want to know? What do you want to steer on? Too often we start collecting before we are clear on what we want to solve. Pick your strategic goals first and connect your data to those. Only then do you know which data is genuinely relevant and worth digging into.

2. Data quality isn’t glamorous and it is decisive

Wrong customer records, duplicate entries, unclear definitions (when exactly is someone an “active customer”?). These things undermine trust in data. Make clear agreements through data governance, build good processes and check regularly. Small and clean beats large and polluted.

3. Make sure you have enough data, and above all relevant data

More is not always better, and we all know it. Only relevant data is usable: data that says something about your customer, your market or your product. Combine internal data such as sales or support with external sources such as industry figures or market research. That gives sharper insight than staring at your own navel.

4. Use data for innovation, not only for reporting

Data is a source of renewal rather than an accountability tool. Use customer data to spot new needs, test ideas with A/B experiments, and look at behavioural patterns to improve features or propositions. The best innovations often come from insights you already had and hadn’t noticed yet.

5. Make it practical for marketing, sales and communications

Data should make the work easier. Let marketing segment on behaviour rather than only on demographics. Help sales with lead scoring or insight into customer behaviour. And give communications access to what comes out of NPS and customer feedback. That is when data starts working for you.

6. Build a culture where data matters to everyone

Data is not an IT party. Everyone in your organisation should be getting something out of it. Make sure people understand what data means, how they can use it, and that they can trust what comes out of it. Once that lands, data becomes an ordinary part of how you work.

Start small, think strategically

Working with data is a means rather than a goal. It is a way to make better choices, learn faster and get closer to your customer. So start with what you need now, and build a solid foundation for later while you do it.

Where this meets the commercial side

A sales team that can’t trust its own CRM data will fall back on gut feeling, and gut feeling doesn’t scale. If that sounds familiar, get in touch.