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Simple Predictive Finance: Why the Dream Is a Reality

For a couple decades, there was a quote about prediction that everyone seemed to jump on,“Prediction is very difficult, especially about the future.” This not very provocative sentence from the first half of the 20th century (by Physics Nobel Prize winner Niels Bohr) was popular for good reason. How could you possibly be able to predict anything except death and taxes? (Another famous quote, but I won’t go there…)

Where I live, people may not even listen to the weather forecast, since it doesn’t have a great impact if you’re expecting 95 or 97 degrees in Central Texas on an average summer Saturday. You’d fire up the grill anyway!

So how could you even believe that business people would listen to your guerilla ideas? How about forecasting your probability of achieving your profitability goals for the whole month when you’re only two days into it? The typical reaction is, “ARE YOU NUTS? No way this is possible. At least I think it isn’t. Is it? Ok, tell me how!”

There are six points that I believe can help people better understand the context of predictive finance. I’ll cover the first couple today, and discuss the others in the next few weeks.

Complexity Is the Killer of Efficiency

The role of the finance executive has inarguably grown more complex over the years. Complexity is the killer of efficiency. Finance needs simple solutions to solve the next decade’s challenges to accommodate the shift to a service organization within the company.

A high school teacher of mine once told me, “Henner, you don’t have to know everything, you just need to know where to read about it.” Please note that—although I still might look like a tween— this was pre-internet and especially pre-Big Data. Nowadays, CFOs who are very knowledgeable of analytics capabilities are asking a lot from their finance teams. The days of the finance expert as “the green visor-ed, pocket protector wearing, calculator carrying record keepers” are over, to quote the well-known Prof. Nancy J. Jones from San Diego State University.

Accountants and controllers, treasurers, and finance operations experts now are “advisors and planners, partners in the management of our businesses, large and small, who need to understand how to get data out of the system, how to validate it, and then interpret it… no longer focusing on how to get the data into the system,” says Jones. In short, finance experts need to provide value to the whole organization to justify their paychecks. They need to acquire the requisite skills (and courage) to take the leap to their new business roles and quickly before they become obsolete.

But this means a lot of complexity to all of them. While we all have to accept the fact that finance in itself is complex in nature, there’s a charter to simplify the way that finance experts can support running their company’s business. This can be achieved by having an easy-to-use and maintain finance system, that doesn’t need to reconcile data between systems (like one for controlling and one for accounting, another one for planning and an extra one for reporting, then the various treasury ones dis-integrated and don’t forget the audit, compliance and risk management pieces…) and instantly (in real time so to speak) delivers insight into the impact of any given change in information.

The often-used (but in the meantime) very boring marketing buzz term “Big Data” has always been reality. Most of the time not in a digital fashion, and also beyond peoples’ comprehension, but modern technology now makes it actionable and simple. Today, running advanced mathematical or statistical algorithms across all data at your fingertips is reality. To make it simple, automate and embed in your operational processes.

Serve the whole organization and become a business partner and support to differentiate from your competition, add value to the bottom line, and strategically consult the executive leadership team of your company to achieve sustainable growth. And all this while achieving operational excellence at reduced cost by supporting every finance function to deliver on the promise of simple data and intelligence provision.

Use Tools to Analyze and Predict

In order to predict the future, finance experts have to understand the past and the present. Finance analytics at your fingertips support understanding root cause relationships and can guide the way to simulations of optimal outcome.

The pendulum swings often in analytics. First, there were departmental units created to support the finance team with “analytics” —those days focused on reporting and analysis. But soon after, the C-Suite undertook all efforts to centralize as teams reported different numbers on simple questions like, “What’s the profit in the south region with our top three selling products?”

But having the (then called) centralized business intelligence department manage user access (and unfortunately, the report creation also) wasn’t the golden standard either. Departmental requirements took weeks to realize and even then delivered only a percentage of what was needed. This was the beginning era of self-service analysis.

But then again the chasm between corporate structure and departmental needs became bigger, so that we’re now in the state of a so-called “governed data discovery” (see Gartner). Controllers now have the possibility to generate their own analyses, visualizations, and even predictions within their usual context.

Finance analytics tools provide the finance department with easy access to internal and external information and cater to fact-based decisions.

Next Time

Next week (Simple Predictive Finance—Everything Is Profit and Loss) , I’ll cover the mission of margin improvements, and the importance of continuity and sustainability. Join me as we continue the discussion on how to transform the finance function.

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