NEW YORK — CFOs were encouraged to add external economic analysis to their business intelligence planning during the CFO Live conference yesterday.
External factors influence 85% of business, yet almost 70% of executives make their decisions only using internal business intelligence data, Richard Wagner, CEO of Prevedere, told the audience.
Wagner pointed to a former client, a cosmetic retailer, that saw an uncharacteristically high 20% growth rate on one of its product lines. As a result, it planned to assume another 20% growth rate the following year.
Wagner worked with the company CFO to conduct a parallel plan using external data analysis. They found its main customer base demographic for the product saw its $50,000-a-year average salary getting squeezed and, as a result, the group was buying more cosmetics online to save money. The external-data analysis showed an 8% decline instead of 20% growth, and that’s what ended up playing out — a $300 million revenue miss.
As another example, a manufacturer of drill bits for certain types of big construction projects saw a big jump in demand and considered selling the business while sales were strong. The company relied primarily on internal data to forecast continued strong sales, but sales over the next few years dropped sharply, greatly decreasing the business' attraction to potential buyers.
Identifying external data
There are different ways to select which external data sources can predict where business is going.
Wagner's company helps businesses identify external data sources by using an engine to crunch huge amounts of data, and see which factors align with the client’s historical sales data. If a company’s historical data shows a 20% growth rate over a few years, for example, Wagner’s company will see which external data sources show a similar 20% growth rate during the same period.
In another example, Wagner worked with a company that needed to forecast the demand of microphones to be installed in prisons. These microphones allowed inmates' visiting friends and family to securely communicate inside the prison walls. However, at the time an external set of data involving lower demand for gas at gas stations signaled that economic downturn was causing people to reduce their gas expenses. Less gas consumption meant more phone calls instead of in-person prison visitations, which subsequently meant lower demand for microphones.
"Look for changes in external factors that correspond with that over time," he said. "You have to have an engine that quantifies that change. You process everything using machine learning — start to learn from that."
The key, he said, is to identify the right external data sources to predict business operations, which will require high-speed big data crunching.
