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DataIQ Member’s briefing – Is finance the next big skills area for data leaders?

Finances rule a huge part of business operations, so should data leaders consider finance skills the next big area of focus? There has been ongoing debate about how data teams can communicate with other departments and how this influences the value and standing of data. A group of DataIQ members explored the ways in which delving into finance skills could be the next way to improve businesses.
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Communication and connectivity 

The conversation kicked off with one contributor stating that they came to their current data role at a global law firm from a financial background and immediately noticed that there were “two very different ways of working” when it came to data. “It was a very steep learning curve for me,” stated the member before explaining that the finance department had a quantitative focus and viewed performance with a different lens. It was agreed that having different approaches to data is not a problem if it works with the scope of a specific department, but the fact that different approaches are being used – and this is often an unknown for data offices – is where the problems can arise. The members highlighted that an emphasis on communication between individuals and teams across departments is needed to help better understand what each department requires from data. As a member from the insurance sector stated, “I think [the learning process] can be quite informal and just reading a book is a start,” showing that there is a low barrier to entry for data professionals to delve into financial skills.  

In addition to appreciating a different approach to data, it was noted that there are unique terms for data used across departments and this led to situations where members have had to ask for definitions. To be able to understand department-specific jargon is essential in developing a cohesive culture and smooth operations between departments. DataIQ members have frequently mentioned wanting to improve the data literacy of other departments, but the inverse is also true that data teams can become more literate in other disciplines, including finance. The retail member of the discussion said, “I try to remove the word ‘data’ from conversations and use the word ‘information’” in a bid to make data more accessible and easier to understand outside of the data office. As one contributor mentioned: “I do not know if [finance] is a skills area, but I think it is for data leaders to understand finance terminology.” A member from the insurance industry added to these thoughts by stating that “to be a business leader, you need to understand finance, and you need to understand how the finance works.” It was then discussed if multi-department training programmes could be introduced, or simply have department leaders coaching other teams to understand the basics of their operations and aims.  

Despite this acknowledgment of needing to understand other departments, it was noted that there is a perceived barrier (particularly between data and IT). The group agreed that to be able to break the barrier means allowing more people to have wider commercial conversations within an organisation. A member highlighted how their finance director had seen the division and implemented training modules to counteract the barrier focusing on key financial performance metrics, understanding what finance looks like and analysing the key drivers of profit. A member from a food retailer added that “building some bridges with the finance team” would be a key part of improving finance literacy across the business and the knock-on effect of this would be improved storytelling demonstrating the value of data. A government-funded service provider echoed this sentiment and explained that their data team has found itself “in between the technology department and the finance department to help them come together and see how we can work through different costings”. This positioning had also helped improve cross-department storytelling which had improved the standing of the data department.  

A couple of the roundtable members talked about their experiences in positions in other departments and how moving into data, this had helped them. A member of the roundtable told the group how they were previously a “country head of a business running a P and L, which was very uncomfortable to begin with, and a real step out of the comfort zone.” Yet the experience gave them new understandings and confidence when it came to finances and topics outside of the data sphere. The once again highlighted the need to engage with different departments and experience their approaches to data to create a culture and series of operations that can seamlessly blend the teams. As another member added, “our finance partners and colleagues are actually extremely receptive and extremely collaborative” when it came to wanting to improve data literacy. Could it perhaps be beneficial to data offices to hire internally from different departments and incorporate the knowledge of other departments the new hire can bring into the data realm? 

The price of choices 

Nothing in this life is free, and that is particularly true for data offices looking for the next upgrade and investment to improve their craft. A member of the roundtable from a retailer explained that teams must understand that the development of things such as data pipelines “have a cost and have an impact”. This then needs to be further understood into terms of not only cost, but also what are the ultimate benefits in return and whether these benefits are worth the investment. 

This led into a short discussion about demonstrating the value of data, which has been a recurring topic in multiple DataIQ roundtables in recent months and is a difficulty that many members have highlighted. The group agreed that education for both data and finance departments on each other’s operations would be needed to easily rectify this problem, with one member adding “finance is there to best understand numbers and the technical teams will understand the benefits around implementation of products.” This was expanded upon by a roundtable member from a national news organisation that described how their data and finance teams had been working together following a new subscription-led business model. A public sector service provider explained that they have managed to prove the value of their data by “[letting] the stories and impact and use cases do the talking” to highlight data’s worth.  

Technology has been a prime solution for efficiency and transparency in recent years, but investing in software, architectures and upskilling staff can be a costly endeavour, which is why longevity is desired. The group agreed that the data office tends to be the most forward-looking in terms of technology, but this should not be the case. When discussing the operations of financial teams, one member identified that, in their experience, the finance team “has a lot of manual or archaic Excel work.” They went on to explore the idea that “there could be a meeting of functions” between data and finance by bringing “some of the data driven practices and technologies to what [finance] is doing” to develop efficiency, connectivity, communication and futureproofing. However, this would involve investment, not only financially, but also in time and being able to communicate the value of this is difficult to do.  

To summarise the longevity aspect, a member from the retail sector said, “I think, in the future, all businesses will still be having the debates of what to spend money on as there’s always more things to spend money on, but I think it will be recognised that data is an asset. There will still be a question of how big data needs to be and whether an organisation really needs to upgrade this year or next year. I do think it will be ongoing, but I do think data will be closer to finance than it is now.” 

There is definitely a desire to improve financial literacy within data teams but identifying it as the next big skills area might be a stretch. A common understanding of operations, aims and data value is needed across the organisation, which can be achieved with informal training and heightened communication and transparency. It will always cost to improve data, but data also always has a value – although it may not be a financially tangible value – so having close cooperation between data and finance can be an overwhelmingly positive outcome for both departments.  

Make sure you sign up to the upcoming DataIQ roundtables to get involved in peer-to-peer conversations that will improve your data journey.  

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