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As I mentioned in my last blog, Simple Predictive Finance: Why the Dream Is a Reality, the finance function is transforming with advances in technology and predictive tools. There are several key points that I believe can help people better understand the context of predictive finance. I covered the first two (simplicity and the path to governed data discovery) last week. Today, we’ll cover a couple more.

The Mission Is Margin Improvements

Everything in any given organization is profit and loss. From the top floor to the show floor, people will have to understand their contribution to total, be it the purchasing manager negotiating contracts with suppliers, the marketing manager booking ads, the controller preparing financial statements or the senior executive hiring Ivy League students. The mission is margin improvements, and the one who doesn’t understand this will be soon a former employee.

A recent study by cfo.com revealed that 55% of finance executives see “cost and profitability” as well as “growth” as the core charter for their organizations. It’s definitely not a pure finance goal, but it’s a broader corporate goal. This can of course only be achieved if every piece of the value chain understands their contribution to total. Only if you can see the impact of any given action on your contribution can you act accordingly.

A holistic view on finance key performance indicators is a must, as contradicting or even cannibalizing targets destroy margins. Don’t you want to know if your business trip provided a positive impact on your company’s goals? Or how much discount a sales rep can give to a customer while still achieving her quote and the regional profit goals? And how does regional cost cutting (often referred to as the laying off of a bunch of people) relate to optimizing the workforce? Only real-time finance analytics can provide the answer…

Continuity and Sustainability

Continuity and sustainability are a must. Volatility in responsibilities kills profitable growth since change management is a constant task. Advanced analytics in the hands of finance departments help provide continuity as it abstracts problematic areas and provides for guidance on how to solve them beyond gut feeling and current “trends” within the organization.

Gut feeling and singing from the corporate songbook is a common base for decision making. A threat that predictive analysis, as an example, brings to the table is that it contradicts these bad habits and confronts the decision maker with the fact that he’s doing wrong. Not a good start for a long-term relationship, right?!

But it also paves the way for a new dogma: de-coupling analytics from gut feeling, experience, or even wishful thinking. It allows one to abstractly present the outcome as a guidance “from the twilight zone.” “Hey, I’m just the messenger, this is what this predictive finance tool has come back with, Mr. VP of Finance…”

The models created are machine-learning capable, deliver on the promise of almost certainty (95% and above), and help reveal potential outcome in:

  • Guidance: For example, the chances are high (98% confidence level) that we should shift budget allocation from marketing campaign “A Better Choice than Oracle” in Latin America to the HR development initiative “How Sales Reps Talk Finance” in France in order to meet our 2015 goal of 38% margin.
  • Absolute numbers: For example, DSO reduction for large customers in the retail industry will be at 1.9% this quarter.
  • Identifying signals/drivers: For example, there’s a direct causality between the company car a sales rep is driving to the average deal cycle time and size.

Abstract means that this level of decision support will remain constant even if organizations and responsibilities shift in the volatility of a corporate life versus relying on the respective unit manager’s guts.

Next Time

In my next blog of this series, I’ll cover the role of visualizations and the importance of analytics training in finance education.

This blog originally appeared on The Decision Factor blog: Simple Predictive Finance: Everything Is Profit and Loss

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