Don’t wait for perfect data – your existing data is more useful than you think

“We don’t have that yet.”

“It’ll only be worth it once we get this.”

“We should wait until after that happens.”

If you’ve ever made comments like these as reasons not to start a data project, you might be guilty of trying to wait for perfect data.

While it’s natural to be wary of basing major decisions on incomplete or outdated information, your hesitation to get started may be causing more problems than you think.

So why should you stop waiting for perfect data?

Perfect doesn’t exist

If you’re determined to wait for perfect data, you’ll be waiting forever. Where data is concerned, perfection – especially within major organisations – does not exist. Making better decisions with data will always be an iterative process.

You will always be able to improve your data, no matter how good you think it is. It can always be cleaner, and it can always be more thorough. In other words, it can always be perfected. It’s easy to convince yourself that you’ll be ready to start your data project after a certain event has happened – a new system being implemented, a new process being established, or the latest organisation or departmental restructure taking place.

But there will always be something new on the horizon, and the goalposts are often likely to shift. So stop waiting, and start taking action.

Your existing data is more useful than you think

When it’s used in the right way, ‘good enough’ data is all you need. It can be cleaned and combined to be the best it can be – and that ‘best’ will still be imperfect.

But that’s okay. Imperfect and incomplete data can still deliver value if you’re willing to experiment.

You might find that analysing different datasets from previously siloed sources can lead to cost saving discoveries, or more efficient planning. Even on a small scale, positive results in these areas can help to build momentum and reassure other stakeholders that it’s worth making the effort to continue the project and improve the data as you go.

You’ll be better placed to identify missing data

You may worry that your current data doesn’t even reach ‘good enough’ status. Understandably, this could lead to reluctance and concerns that you really are better off waiting until things improve before committing to doing anything with the data in question.

When you experiment with your existing data, you’ll often find that small insights can make a big impact on your hypotheses and how you approach the project as a whole.But you’ll struggle to figure out what you’re missing if you don’t make use of what you already have. By actually gathering and utilising your existing data, you’ll be better equipped to identify the gaps to be filled and get a sense of what’s possible.

The right software can handle the mess

When you do try to start working with the data you already have, you’re likely to be faced with many messy datasets. It’s easy to feel frustrated and overwhelmed when you think you’re ready to start experimenting and find that the situation is worse than you originally thought! But the right software can work with you at this stage.

A tool like Rail BI can help you to display all of your different data sources and even any duplicate datasets, which you can view side-by-side as you start to make sense of it all. It helps you to migrate and improve your data over time by acknowledging where you’re starting from and dealing with what’s actually in front of you.

Remember that you don’t have to solve all your problems at once. You can start small and discover how the software can be instantly useful while also helping you work towards a single source of truth. Rail BI meets you where you are now, building on your existing systems to help you reach a better place.

Ready to get started?

You’ll be surprised at the insights you can discover and the benefits you can gain with imperfect or incomplete data. When you’re willing to experiment and iterate, the process itself will lead you to more complete and reliable data over time.If you’re prone to trying to wait for perfect data, the idea of getting started before you feel fully ready is always going to seem a little intimidating. But the perfect time and the perfect data will never come.

The best path to improving your data is to start making use of the data you have now.

It’s time to stop waiting.