If you were able to, would you create a forecast based on intuition? Would you stray away from data-driven decision making and planning, and just go with your gut? What about always being a month behind on revenue predictions? Only people out of touch with reality would answer yes to these questions.
You may think, “I don’t do any of those things because I am a wiz at Microsoft Excel!” How long would it take to recreate that workbook if your team started right now? If you’ve worked in finance for any amount of time, you’ve probably developed a loving relationship with Excel by now. But the reality is that some analyses are just too time consuming or difficult to create and reproduce, or the data is simply too large to be analyzed in Excel.
This was the case with one of my favorite clients. There was a need to develop a bottom-up billing forecast. For too long they had been developing high-level billing forecast figures based on top-level historic performance. They wanted to gain further insight into the reality of their billings forecast, with a need to analyze this data by subsidiaries and products, at a minimum. This proved to be extremely challenging as they had multiple subsidiaries containing thousands of customers, with each customer having multiple contracts and each contract having multiple lines representing multiple products, all with varying billing terms. Sound familiar?
Initially the client tried accomplishing this in Excel, through a motivation killing combination of data file exports, data cleaning and formatting processes, and “if statements” with nested index matches. Not only did this create a variety of cases where errors could arise, but once an error was noticed, it was nearly impossible to diagnose the root of the problem. Of course, nobody felt confident in the numbers.
I could practically see the hair greying when I first heard about this goal from them! Together we were able to resolve this issue using Adaptive Insights with the following steps:
- Gaining a deep understanding of the unique problems and exceptions with their data.
- Integrating to their contract source system to automate the flow of data. Through this integration, we were also able to automate the data cleansing process.
- Writing decision logic in Adaptive Insights that was able to review the various parameters of a specific contract and forecast (or discontinue forecasting) out the billings appropriately.
- Using Adaptive OfficeConnect, my client was able to update a billing forecast report deck instantly, as well as perform more in-depth billings analysis.
I could feel the relief with this accomplishment as their team was now able to report accurate billings figures to their board of directors. While this was a great accomplishment for them, the value-add didn’t stop there! With this new billing forecast, we were now able to:
- Add in customer health variables to forecast customer specific renewal rates.
- Update their balance sheet forecast and cash forecast to gain greater insight into their corporate health into the future.
- Use actual historic customer and billing data to become predictive about when a customer may be considering cancellation or is prime for upsell and cross sells.
This doesn’t even include the future capabilities of being able to:
- Layer in open SalesForce opportunities.
- Measure marginal product revenue with changes in product—or product line focused advertising and marketing campaigns.
- Numerous other business intelligence and predictive capabilities.
Too many companies today have employees spinning their wheels developing analyses and forecasts in Excel that come much too late and are barely (if at all) reproducible. In addition to these issues, once the analysis is complete it takes additional time to layer this data into balance sheet and cash flow forecasts, and you’re still looking into the past with a thick fog in front of you.
It’s been played out, but it’s still true. Companies that use data to make data driven decisions and forecast and stay away from intuition-based decision making and forecasting create a competitive advantage. Make these data driven decisions fast and easy to analyze and well. I’m sure I don’t have to tell you how powerful that is.
