About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Excel in Data Management – Why it Still Has a Role to Play

Subscribe to our newsletter

By: Martijn Groot, Vice President of Marketing and Strategy, Asset Control.

In the world of technology infrastructure, Microsoft Excel is often seen as both a blessing and a curse. That its usage remains so widespread today is testament to the power of the tool, as well as the quality of the marketing and distribution that supports it.

One of the biggest benefits of Excel, outside its pure functionality as a data organisation and analytics solution, is that there is zero threshold to using it. Its prevalence and ease of use is such that people can start working with it quickly and easily, and get fast results and immediate gratification.

We all know the downsides of course. Many have experienced the challenge of key person dependency, which tends to surface whenever a 100 Mb spreadsheet comes to light with macros nobody understands (apart from the employee who created it, who is now either on holiday or no longer with the company).

Another risk is duplication of data. Different versions of Excel all with their personal tweaks often float around organisations and nobody keeps track of them. The third, and arguably most important risk factor, is where Excel is used for the wrong purpose across the organisation. Operational risk and risk of data noise is introduced when Excel is used as a step in a data processing chain rather than merely as an endpoint for presentation or reporting, or as a data source.

This, for me, gets to the heart of the matter. Excel can and should have a part to play in data management, but it needs to be used in the right manner. An analogy might be helpful here. If we compare the space of data management solutions to the realm of transportation, I think Excel occupies the spot of cars. Cars are easy and accessible. They are often parked right in front of your house. Everyone can use them. However, when everyone uses them, you tend to get stuck in traffic. Plus they pollute. And you have adverse side-effects.

Mass transit is better in many ways. Where cars work very well is in last-mile connectivity. Bringing you from your house to a transport hub. Moving 2,000 people for 100 kilometres between two cities is best done by train. Transporting 200 people 1,000 kilometres between two cities, with or without a stretch of sea in between, is usually best done by plane.

The same pattern of thinking applies well for Excel. It undoubtedly has a role – but it is important organisations don’t overuse it or use it for the wrong purpose. You would not cycle 100 kilometres to work, and you would never even consider constructing a high-speed railway line using just five kilometres of track, or building two airports to bridge a 10 kilometre transport route.

In this context, my advice would be: consider using Excel for that last mile connectivity and start seeing it as part of the solution rather than the problem. Excel can work well in conjunction with a data management backbone, but in best case scenarios it should act as an endpoint – either as the point of data creation in the form of a report or a presentation for example, or as a data source.

To start with the first case, many organisations use Excel to create their own local models – and that is a legitimate use. The data can be submitted (with or without context, such as the business logic and/or calculation parameters) to a data management system as one input source. For example, front-office traders or portfolio managers could submit pricing information using Excel. The data management system could then combine these inputs with external data sources, keeping track of audit, lineage and source changes.

Similarly, at the other end of the process, Excel could be used to tap into a data infrastructure in order to create a source of trusted information for anyone looking to do quick calculations or preparing MIS reports.

Excel is overused and when it forays into use cases where it is inappropriate it leads to operational risk, spreadsheet dependency and version control nightmares. However, if you put proper bidirectional integration behind it, Excel can be critical for any industrial strength solution. Indeed, Excel and a proper data management backbone working in tandem is an unbeatable combination.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: How to simplify and modernize data architecture to unleash data value and innovation

The data needs of financial institutions are growing at pace as new formats and greater volumes of information are integrated into their systems. With this has come greater complexity in managing and governing that data, amplifying pain points along data pipelines. In response, innovative new streamlined and flexible architectures have emerged that can absorb and...

BLOG

Clearwater Looking to Bridge Front-to-Back Office Tech Gaps with Acquisitions

It’s difficult for data and technology companies to fully service financial institutions’ front-to-back operations when behemoth providers are offering closely integrated capabilities at scale already. Clearwater Analytics, however, has a strategy that it believes will work not by necessarily competing with the big aggregators, but by working with them and filling gaps that they don’t...

EVENT

ESG Data & Tech Briefing London

The ESG Data & Tech Briefing will explore challenges around assembling and evaluating ESG data for reporting and the impact of regulatory measures and industry collaboration on transparency and standardisation efforts. Expert speakers will address how the evolving market infrastructure is developing and the role of new technologies and alternative data in improving insight and filling data gaps.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...