The Enterprise Data 
Challenge

Enterprises have never been more eager to get value from data. After all, accurate, fresh data offers a multitude of benefits; it helps organisations optimise operations, differentiate against competitors, develop new products, serve customers better, steer the business in a new direction and the list goes on. There’s no limit to what businesses can do with the right insight at the right time.

All of this means the pressure’s on decision-makers to put their data to good use: because it’s washing into the enterprise, from a huge number of sources, all the time. And business leaders know that if you’re not using data effectively, not only are you missing opportunities but you’re putting your business at risk.

But, many businesses just don’t know where to start…

The reality is that for most businesses, access to relevant information is still too costly, slow, and risky. As a consequence, business data still often remains disconnected from the value it can bring. As the amount of data available to enterprises increases, its usefulness for informed decision-making remains elusive. 

So what can businesses do about it?

We work with finance organisations to help them develop data strategies that can drive true value from their data. And while the problem is largely the same for all of them - they can’t get reliable insight from their data fast enough for it to be really valuable - the solutions, and particularly the priorities, vary from business to business. 

Having said that, here are some steps businesses can take that we’ve found universally useful:

• Approach your data project “value-first”. The “data-driven enterprise” won’t happen overnight. But a single, clearly defined data project can be realised relatively quickly. Define a use case, its tangible benefits, and an agreed-on timeline for your first insight project. Ideally this will be something that’ll make the C-Level listen up. We’ve found that cost-saving initiatives in Finance - such as the opportunity to save sales tax, or the ability to introduce intercompany charging - are great candidates for a pilot. Once decision-makers have seen the value and hard cash this delivers, it becomes easier to get buy-in for projects in other departments, for new use cases, and ultimately for a different approach to handling your company’s data - and the insight it holds.

• Acknowledge that your insight problem has an underlying data problem as its root cause. That means that data engineers and the business need to work together on solving it. Since, the two “camps” tend to approach projects with different mindsets, it’s important the keep checking in with each other to ensure the project stays on track. This is a mediation and empathy play as much as it is a tech and business issue.

• Make business insight a priority, by putting together a team responsible for data management. Without, a team responsible for driving insights it will be impossible to make progress. This team can take the shape of new-hires or a group of data consultants.

We’ve arrived at these learnings from dozens of data strategy projects we’ve worked on with businesses across Ireland and abroad. We’ve seen that starting with these three steps can break the data deadlock, get important conversations going, and raise awareness of the need to bridge the data/insight gap.