At the recent Hub 15, the third annual Anaplan user conference, one of the more intriguing sessions B2BNN attended was presented by two consultants from Deloitte. During this session, Edward Majors, principal, Deloitte Consulting, and Vishnu Narins, manager, Deloitte Consulting, delivered a presentation and interactive demo on predictive analytics for the B2B financial planning process.
In a familiar refrain about Moneyball, Majors opened the talk by citing the Brad Pitt movie of the same name about how the Oakland Athletics have succeeded in the inefficient major league baseball evaluation market against their rivals with three times the budget. “The Oakland Athletics threw away the model for evaluating talent,” he says. So if the Oakland A’s could throw out a century-old protocol for assessing ballplayers, why can’t B2B planners discontinue using the even older high finance model, Majors asks.
In reality, B2B financial planners can go beyond the traditional thinking and training, because, according to the Deloitte presentation, “Behavioral economics teaches us that inefficient markets result when industries are dominated by judgment-driven decision-making.”
Over the course of 35 full-life cycle performance management system implementations for Fortune 500 companies, Edwards has heard more than one client ask for Deloitte to take a 15-year-old financial planning system and port it to Anaplan. “And they want it in six weeks,” he adds.
In managing B2B financial planning, clients need to use a decision optimization framework, according to Majors. That’s because “80 to 90 percent of data that’s important is external and unstructured,” he says. This necessitates that clients go back and reprioritize “what matters,” notes Majors. “Build for what’s important today and tomorrow.”
Specifically, B2B financial planners must encourage the organization to focus on outcomes that have the potential for a large impact on the organization. Don’t neglect considering customer profitability, product portfolio and integrated business planning.
Cola and coconut water as business inspiration
At this point, Edwards concluded his prepared slides and Narins continued on with the interactive presentation. The data she presented was modeled on a large cola company
Based on this data, cola products have seasonality, according to Narins. “People drink more cola when it’s warm,” she says. Using the forecasting functionality in Anaplan, Deloitte’s forecast for the cola company was 98 percent accurate—more accurate than that of the client, according to Narins.
Basically, the demo served as a case study for a new product introduction of coconut water. Because this large cola company did not have the usual 24 months of historical data, instead Narins demoed how B2B planners can use old assumptions based on the cola product to model the forecast for coconut water.
To increase the accuracy of the forecast, Narins says that Deloitte tried to incorporate unstructured social media data into the coconut water introduction model. Primarily, it was based on Twitter data. With this data, Narins was able to illustrate how the sales of coconut water would be higher at different popularity levels as reflected in Twitter data.
In addition, other inputs can be made to the coconut water introduction model based on varying levels of R&D and promotional spending. These inputs are made easy and automated in Anaplan, which can update forecasts in real time with changes in data.
According to Narins, the key takeaways her demo include:
- Sales with the highest volume may not have the highest profit margin
- B2B planners should focus on the products with the highest profit margins
- Better decisions can be made when taking into account differences in products and the countries where they are marketed
- Look for inspiration at high impact products, such as cranberry juice, which has a low sales volume but a high profit margin
Photo via Derek Handova
