January 2023

VLOG: The role of data in driving operating model change

In this video, Duco CEO Christian Nentwich explains how firms are looking to evolve their operating model and the role data automation platforms have to play in the transformation of financial services.


Hello, I’m Christian. I’m founder and CEO of Duco. And I’ve been doing this since it was a little firm in my bedroom to where it is now: a global company.

So, fundamentally, an operating model is how you act day-to-day across business functions. And the interesting thing for me is, how do you redefine the job of each business function, whether it’s a front office or a middle office or back office or IT, and how it collaborates.

In the past, it’s been very siloed. Platforms like Duco actually bring these functions closer together and align what happens in the back of the firm much more with what happens in the front of the firm, and get everybody working together.

The mission of Duco is to be the best data automation platform for mission-critical data. So if your company depends on the data being right and you have hundreds/thousands of people making sure that it is, we can help you do that far more efficiently than you can ever do it today. 

Duco is a big change over how you do this today. Today, you probably have big IT systems and lots of people working on data problems. Tomorrow, with technology like Duco, you get the people who actually understand that data, your finance team, your operations team, everybody gets sustainably involved in dealing with the data and getting efficient processes in place.

Duco does this differently in two important ways.

Number one: Duco is entirely in the cloud. We’ve always been in the cloud and we’ve always been a SaaS company and we’re the only company of its kind like that, which means we bring faster innovation to the market.

Number two: the level of usability of Duco is so high that even relatively untrained people can just pick it up and do extremely complex data manipulation, which is an incredibly difficult problem to solve. And, you know, with our computer science heritage, we’ve been able to solve this problem in a different way.

It’s crazy how a tech company is suddenly running around and talking about target operating models, because what does that even mean? So, we have learned quite rapidly that there’s a limit to the change technology can make without changing processes around it.

And now, the fundamental assumptions around tech have changed so much that people are really struggling to reinvent their organisation, so we’re trying to partner with our clients to help them really rethink how they work day-to-day. 

We see two really big challenges here at the moment. And, you know, one of them is one you described as talent, I guess. Firms are really struggling to hire talent, and to retain talent because they can’t give them good tools because the next generation doesn’t want to use old technology and so on.

And the second problem is that there’s a lot of change resistance that comes in from ingrained work patterns, you know, having done the same thing for 30 years. So, it’s really important to bring people together in the rethinking process and the design of the new organisation.

If you’re in a bank, or in an insurance company or any industry like that, the fact is that a large part of your job is data manipulation, and a big change in the last two years is people have finally figured this out, right?

We go to work and we manipulate data in some way. So you can’t divorce the whole discussion about how you should operate from how you treat your data. That data gets in the way or it enables you, you have to deal with it one way or another.

I’ll tell you what happens when you don’t automate processes around data. You ask yourself a question. Every time you look at a piece of data, can I actually trust this? And to find out if you can trust it, you’re gonna ask 10 people 10 questions and run around and create huge amounts of inefficiency.

When you increase automation around data you can rely on the data and you’re not constantly covering the same ground over and over again. And in fact, mostly, we still underestimate the impact of all of this – the impact of getting this right is absolutely enormous.