Finance and Data & Analytics - better together
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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The Finance Function is learning to be a better bedfellow to Data & Analytics, and vice versa.
Combined, these two skill sets can drive unparalleled value creation within organizations. And, when understood not as distinct disciplines but as two sides of the same coin, Finance, and Data & Analytics can become the true engine room of a business.
In this new series, I'm going to explore the relationship between these two fields, the opportunities that can be realized through their efficient application, and some of the blockers that are preventing that from happening in organizations of every size.
Insight over everything
The increasing focus on data reflects broader developments within business and society, and is contingent on or catalyzed by the emergence of several new technologies. Let's explore some of these key themes briefly, before going into them in more detail throughout the series.
Rationalization. The idea that everything can be quantified and optimized is not a new one; for better or worse, positivism and empiricism are at the heart of the modern business. The rationalization and 'datafication' of every facet of life and business have developed in tandem with data science, and analytics is now widely understood. It has now fully extended into the consumer mindset through the popularity of quantified self-devices.
Sensing technologies. Efficient data and analytics processes rely on good data gathering, or what we might call 'sensing'. Businesses are getting better at deploying sensing technologies, from actual automated industrial sensors to qualitative employee reporting. Just-in-time (JIT) processes, which came to define 20th Century manufacturing, laid the foundations for the idea of the business as a sensing organism - one that is capable of understanding itself and then acting upon its observations.
Granularity. As businesses become more data-hungry, the data they ingest becomes more granular. Information grows more specific, reporting becomes a fundamental process, and data becomes both a signal and a lever - that is, something that can tell us what is going on in our organizations, and something that can be acted upon in order to change outcomes.
Falling cost of computation. Finally, and perhaps most importantly, computationally-intensive tasks are now within reach of almost anyone with an internet connection. The foundational tools of machine learning and artificial intelligence, along with the data-wrangling required in order to make them work, are all widely available. A huge industry has grown up around these developments, piggybacking on the open source community's work to deliver "plug and play" data solutions.
Business data vs financial data
Basic skills in data science and analytics are now fundamental requirements for the modern Finance professional. But there is still friction between the Finance Function and D&A, and the two are not well integrated into most organizations.
In part, this is due to a misunderstanding about the forms data might take. In traditional Finance Functions, professionals are used to dealing with purely financial data - P&L, balance sheets, and so on. This is not the same as what we might call 'business data' - that is, the vast stream of information that modern organizations now gather, concerning almost every part of their operations.
It is here that Data & Analytics can add value, and it is here that the potential for collaboration with the Finance Function remains unrealized.
In the remaining articles in this series, I'm going to look at how we can tackle that. I'm going to look at the lay of the land in Data & Analytics, and explore some ways that this crucial skillset can be better integrated into the Finance Function. Subscribe now and you'll receive the articles as soon as they're published.
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.
Senior Manager at Bayat Rayan
2 年ESG in some economies is like mayonnaise. It is not that eesential in comparison to so many peril the economy and entities are faced with.
Sales | Engineer | Entrepreneur | Business Development
2 年'two sides of the same coin' - shouldn't be a win/lose situation. Data & Analytics can help pretty much every discipline to improve