How good is your Data Strategy?
If you’re already undertaking data projects, what’s your end goal? What are you ultimately trying to achieve, and what roadmap are you following to get there? It may sound obvious, but you wouldn’t be the first organisation to launch into a data project without first establishing an end goal and a clear strategy to get there. It’s why Data Governance, for instance, is so often missed in the process, resulting in data projects that are slow to deliver value and frustrating to get off the ground.
First step: Define your Data Strategy. The following points will all play into that strategy, but what exactly each step will look like will depend on your organisation’s goal, culture, existing technology and data practices.
How good is your Data Quality?
Before you can get results from your data, you need to ascertain its quality in the here and now. We have a saying at Amplifi: garbage in, garbage out. If the data you are putting in is inaccurate, inconsistent, out of date or just plain unreliable, the results you get from it will never be good enough. For instance, if you’re introducing an automated customer support function, but your customer data is wildly inconsistent, full of duplicates, essential fields are missing and the contact details are out of date, you’re not going to support the customer so much as frustrate them.
Next step: A Data Quality assessment is a critical step to being ‘data ready’. It will examine the data you have, the data you need, and outline what exactly that data should look like to deliver your goals.
However, a Data Quality assessment alone is not going to ‘fix’ your data. It will bring it up to standard, but without the right measures to maintain it, that quality will start to decline almost instantly. This brings us to our next point.
How good is your Data Governance?
Data Governance often conjures up an idea of rules, boundaries and formal assessments – but the reality is very different. Yes, it does include rules and boundaries, but it’s more liberating than it sounds and is much more focussed on enabling and empowering people to maintain high quality data for their benefit, as well as the benefit of the business. It’s part handbook, part gospel, and it should – if it’s done well – have everyone singing from the same data hymn sheet moving forward.
Next step: Start a Data Governance initiative. Getting external help is recommended, as working with a partner can help overcome internal political barriers. Consultants will also have tricks up their sleeves to make governance stick.