CFOs and their teams may not consider themselves “evangelists” today, but now is the time to demonstrate the power of analytics.
It may be hard in some cases to think of the word “evangelist” and not mentally modify it to “televangelist” – those people you see on TV preaching and, occasionally, asking for financial donations. That’s definitely not a role that aligns well with CFOs or others in the finance department, but being an evangelist for BI and analytics might not seem much better.
The idea of evangelists as a job title is not new to the IT industry, of course. Software companies have employed them for years, usually to help developers appreciate the merits of a particular operating system or programming language. Finance professionals, on the other hand, are better known for evangelizing sound practices in managing costs, reducing risks and ensuring capital resources are used appropriately.
A recent blog post from an Oracle executive called “Evangelizing Analytics: The New Calling For Finance Professionals” may, therefore, come as a bit of a surprise. According to the author of the piece, though, there may be no better function in a modern enterprise better suited to the job:
Finance teams need to take the lead in promoting an analytic culture within their business. There aren’t many department leads who doubt the benefits of insightful analytics. Marketing departments are improving their performance by analyzing how their campaigns perform. Human resources teams are taking deeper dives into data to recruit the best talent, and more importantly, retain them. But as finance departments demonstrate how an integrated approach to data analytics enables better decision-making across the enterprise, more business units are likely to take notice.
Even if finance teams agree, there may be some question about how exactly to get started. To answer that, it may be worth looking at a column on Credit Union Management which, though obviously aimed at a particular niche within financial services, offers a helpful breakdown of how to think about BI and analytics in general:
Descriptive analytics—historical information depicting “what happened?”
Diagnostic analytics—demonstration of cause and effect to assess “why did it happen?”
Predictive analytics—monitoring and tracking trends and behavior to predict “what will happen?”
Prescriptive analytics—allowing an organization to turn insights into strategy and tactical planning to supply answers to the question “how can we make it happen?”
Over the long term, most organizations will want a BI strategy that spans all four of these areas, but perhaps finance departments can get the ball rolling by choosing the one that will provide the quickest buy-in from other departments. You can always build a more holistic analytics culture from there. After all, as even experienced evangelists know, it may take a few minor miracles before you can turn a skeptic into a true believer.
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