Reflecting on the crucial components of any data strategy

Picture of Robert Cartledge

Robert Cartledge

Last month, I was delighted to be asked to join a panel debate at the Real Deals Tech Innovation Conference in London. The topic of the discussion focussed on the growing importance of data as an asset for private capital market firms and how a coherent data strategy can deliver huge value. As a topic we are almost evangelical about at it|venture, it was great to be able to discuss this with fellow professionals.

Like many good panel discussions, we were under Chatham House Rules, so I can’t go into the minutiae of the discussion, but there are a few high-level points that I think are worth sharing and that I feel comfortable doing.

We began the panel discussion, ironically, with where to begin.

The first question put to the panel focused on data transformation projects and how to successful deliver them. Where should firms begin and, importantly, should they hire their own people to do them or outsource?

From our perspective, we always recommend spending time at the outset to clearly define the business need, scope and business case for the project. Once this is in place you should then spend the time to identify a small home-run use case and focus everyone’s efforts on solving that challenge. Go for something that can be achieved quickly, not something that needs months (or even years) to deliver. Because delivering success rapidly, even if it is a relatively small project promotes overall business buy-in, demonstrates ROI and makes the case for future projects far easier to sell.

I simply cannot stress how important firm-wide business buy-in is (there’s a bit more on that to follow).

As to whether firms should hire internally or bring in expertise on a project basis, there is no one size fits all answer. Of course, I understand I have somewhat of a vested interest in this, but engaging with external expertise does allow firms to hit the ground running. Because, the chances are, businesses like ours have probably solved the same challenge for other firms in the past or can provide an impartial view on the best cause of action. We may not be your “forever” solution, but we will help you move at pace and ensure you set your business up for long term success.

What do firms get wrong?

Our experience tells us that, more often than not, the number one reason for integration and data strategy projects not delivering the expected benefits is a lack of proper planning. Laying foundations and doing the groundwork is nothing short of critical. A well thought through approach that considers everything (what are you trying to solve, why are you trying to solve it, where is data moving from and to and critically, is the data quality good enough) is the most important part of the integration. If you get that right, the rest usually follows.

When data strategy moves from ideation to implementation is when firms usually learn how good (or bad) the quality of data is. How do they get data right, both retrospectively and moving forward?

This was a follow-on point from the previous question. We’ve covered the importance of rigorous groundwork, because, as the saying goes – if you put a certain thing in, you’re going to get the same thing out.

What is equally as vital is establishing a data culture within an organisation and the need for ownership that comes with it. That’s not an easy thing to do – people are busy, and the need to update systems is often very low on the list of priorities. But it is vital.

Our experience at it|venture very much favours the carrot over the stick. Show people the benefits of good data and they will be incentivised to maintain that quality. But you simply cannot get away from the fact that culture is crucial for a successful approach to data.

One thing it is worth bearing in mind is that, in most cases, the people who input the data in an organisation are invariably not the ones who consume it; the ones who use it to make key business decisions. So, facing up to this and trying to build solutions that make inputting data as easy as possible are key. Again, this is work we often carry out at it|venture as part of laying the right foundations and building the best possible foundation for success.

Many firms would admit they are not data-driven organisations (with data in disparate places, and in a wide range of file types, often simply in people’s heads!), but many have now moved on to AI. Are some organisations doomed because they are so far behind the curve?

We don’t think anyone is doomed, but we do think that many organisations need to move quickly. No matter where an organisation is on their data journey, even if that’s at the limbering up stage before they have even begun, it is not too late.

At it|venture we use a discovery approach when we meet with new clients to identify precisely what stage they are at in their data journey. It’s hardly revolutionary, but then the best approaches to change never really are. We find that all firms can be placed in one of five categories. From nowhere, to AI ready (and a few stages in-between), if we know and understand where your firm is currently at, we can work with you to get you where you need to be. You can find out more about that, in detail, here.

And finally, looking back on the tech projects you’ve been a part of, what is the one thing you’d like everyone else to know before they start integration with the unplugging and re-plugging of systems?

I’m not sure there is really one thing, it’s more the sum of a few parts.

Ensure you understand the problem you are solving, engage all users throughout, deliver results that improve their experience and stay on top of the technical developments that happen almost daily. Do not let perfection get in the way of better because use in the real world, with a programme of iteration, is unequivocally the best way to get valuable feedback and, ultimately, build the best solutions.

If you need some help, we’d be only too happy to provide it.


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