Can a Finance professional 'do' Data & Analytics?
Anders Liu-Lindberg
Leading advisor to senior Finance and FP&A leaders on creating impact through business partnering | Interim | VP Finance | Business Finance
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In the first two articles in this series, we've explored the growing importance of Data & Analytics as both a distinct skillset within the modern business and a crucial part of the Finance Function.
The gathering, manipulation, and analysis of data have come to define many business processes, and the impact can be felt throughout organizations. The insights generated as a result of data and analytics practices are enabling businesses to make evidence-backed decisions, test and measure hypotheses, and reduce waste.
Data & Analytics covers a broad range of disciplines and skills but often sits within (or at least intersects with) the Finance Function. It's reasonable to ask, then: could a Finance professional do the job of a Data & Analytics specialist?
What skills do we need?
The traditional Finance skillset revolves around 'hard' numbers, monitoring and reporting on KPIs and other metrics, and providing supporting information to other business functions.
As we enter Finance Function 4.0, that skill set is rightfully expanding. It's increasingly important for Finance professionals to be able to think creatively, to understand the way the business operates as a whole, and to be able to co-operate with other functions and disciplines. Rather than playing a supporting role, the modern Finance Function is an enabler; it operates as a nexus of information connecting different disciplines and generating insight.
There are some key overlaps here with Data & Analytics, a field that is dedicated to helping organizations understand themselves. However, the assumption that both Finance and D&A are 'just about numbers' is fundamentally wrong. Data science is a field of knowledge entirely distinct from Finance. It requires a comprehensive understanding of statistics and behavioral insight, as well as the technical expertise required to safely and methodically gather and analyze whatever data it is that's being collected.
Remember, too, that not all data is quantitative - and, indeed, this is one of the key wedges between Finance and D&A. The ability to digest quantitative information is a crucial skill for D&A professionals and one that is often lacking amongst other more 'classical' business disciplines. Not all data are numbers!
So are these distinct functions?
Yes. And, if we think about it, it's not uncommon for functions and disciplines that are intellectually proximate to each other to develop independently, even within well-integrated businesses - consider, for example, the distinctions between Sales and Marketing.
At the same time, though, it is important that we remain aware of the risks of siloing, and that we work hard to integrate not only Finance and Data & Analytics but every single function across the business. No function is an island - on the contrary, every part of a business should be inseparably intertwined with all the others. They might be proximate or intersecting with other functions and disciplines, but whatever their interaction, they are not alone.
Adding the business partnering 'layer'
But if these distinct skill sets are required, how do we make sure they can all communicate? This is the role of the business partner. We can think of the business partner not as a function within itself but as a separate 'layer' that intersects all other parts of the organization. The task of the business partner layer is to facilitate interoperability - that is, to enable all the other functions to communicate in a shared language, to generate insight in a way that can be understood by every stakeholder, and to facilitate efficient cooperation between specialist disciplines.
To borrow from network terminology, business partnering can be thought of as a 'layer 0 protocol' - one that allows all the other protocols to interact.
Business partnering is the future of modern business and is the primary requirement for success in Finance Function 4.0. What do you think? Can finance professionals do Data & Analytics?
This was the third article in my latest series Finance vs. Data & Analytics. You can read the previous articles below.
While you await future articles why not read my latest series about ESG for finance professionals?
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You can read all the articles in another recent series about if finance professionals should learn to code below.
Continue reading below for more articles about how digital is impacting Finance.
Anders Liu-Lindberg?is the co-founder and a partner at the?Business Partnering Institute?and the owner of the largest?group dedicated to Finance Business Partnering?on LinkedIn with more than 10,000 members. I have ten years of experience as a business partner at the global transport and logistics company?Maersk. I am the co-author of the book “Create Value as a Finance Business Partner” and a?long-time Finance Blogger?on LinkedIn with 95,000+ followers and 160,000+ subscribers to my blog. I am also an advisory board member at?Born Capital?where I help identify and grow the next big thing in?#CFOTech. Finally, I'm a member of the board of directors at?PACE - Profitability Analytics Center of Excellence?where I support the development of new analytics frameworks that can improve profitability in companies around the world.
Project Controls | Cost Controlling | Power BI Project Reporting | Cost Management
2 年I don’t think it would even be a question in a matter of a few years and people of hybrid background would be a norm.
Gesch?ftsführender Gesellschafter bei arq decisions GmbH | Zukunftssichere Entscheidungen dank innovativer Werkzeuge
2 年This highly depends on the industry. The heavier the scope depth, the more operational, the less likely in Finance. A case on top of accounting, e.g. seems highly unlikely as the ledger is too big of a data filter. Personal opinion: absolutely for math savvy Fin professionals and Data deep and intensive Departments. Bringingna data science pro to Finance then might yield value quicker and more lastingly.
Executive Director, Profitability Analytics Center of Excellence PhD, CPA, CMA, CSCA, FCMA, CAE
2 年I always enjoy reading your thought-provoking posts, Anders! I completely agree that the finance profession needs to rapidly evolve to the role of business partner in order to remain relevant. The answer to your question "can finance professionals do Data & Analytics?" is yes, although what "do" means can vary! For management accountants the necessary level of data analytics competency is somewhere on a continuum ranging from little knowledge to master data scientist, with the target competency level different for everyone, depending on factors such as career goals, company size, length of career, and organizational culture. The minimal competency level would be that of an “analytics translator” who understands the data science process enough to work with data scientists addressing business issues. Toward the other extreme are finance professionals serving as embedded data analysts. They have the knowledge and tools to get their hands dirty with data: exploring it, building models, and conveying results to management. More info on how management accountants can develop their data science skills is available at https://sfmagazine.com/post-entry/september-2018-how-to-master-digital-age-competencies/
Financial Director I Chief Financial Officer I Leader I Talents I Director I Finance | Accounting | Audit | Management I Leadership
2 年Y??????????thank you for good sharing Anders Liu-Lindberg