A lot has been written about the changing role of Finance leader towards a more dynamic business partner, both as a Strategist, who has a stable seat in the board room and raises his/her hand more frequently, and as a Catalyst, in terms of desired acceleration of business – proactively driving new initiatives aimed at new revenue streams creation, agile risk management, and examining existing cost structures thanks to novel data-driven approaches.
Having held a few discussions with multiple Europe-based CFOs recently, I personally feel that there is still a proclaimed intention towards data-driven innovation versus the reality still revolving around more traditional CFO hats of Steward and Operator. These are here to stay, of course, as they are the core finance accountabilities, but questions remain.
Concurrently, there are voices calling for enhanced collaboration within the corporate development camp, namely Finance and HR sitting jointly at the table more often.
In terms of data management, CPM suites like SAP BPC, Hyperion, etc. have been around for two decades, having solid capabilities cultivated over multiple upgrades and versions over the years. Let us bear in mind though, that these tools are predominantly focused on core Finance department data – which poses a question of how holistic/comprehensive (or not) is the data-set we are talking about, AKA, departmental/siloed vs. company-wide cleansed data set, which in the latter case can bring highly desired predictive and prescriptive insights to be leveraged into action by CFO (complementary thoughts on Data Prep).
Kirk Borne, leading data science authority at Booz Allen Hamilton, and I had a recent correspondence, where Kirk highlighted the importance of predictive modelling for the CFO office (I mean modelling beyond traditional CPM approach). This involves the CFO predicting risk exposure and potential consequences, forecasting new lines of business (and investment opportunities), improving anticipatory financial metrics with improved forecasting (of earnings, revenue, sales, losses), and predicting potential customer attrition. And the list goes on.
Analytics can be an instrumental for discovering compliance issues, discovering billing and/or payment anomalies, and - talking about Finance playing the ball with HR - identifying key HR metrics for more efficient human capital management.
Kirk has come up with a nice triad for CFO Analytics, which sums it all up effectively, which I am kindly borrowing from him today:
Data-to-Dollars (or data-to-dividends)
These and other affairs are at the epicentre of our considerations and actions at www.AnalyticsOfficers.com.
If you interested in engaging in further discussion on how to 'accelerate the acceleration' in terms of technology, processes, people and company culture (and existing resources), please reach out.
Thoughts welcome, as always,