Last Updated: February 10, 2021
This article was written by- Andrew Duguay, Chief Economist
Modern executives have faced their fair share of challenges throughout the last decade. Today’s leaders have faced unique challenges, from marketplace chaos to the constant consumer behavior dynamics. However, one of the most onerous demands to date seems to be how to transform a business into a truly data-driven organization. So it is not surprising that during the unprecedented pandemic-recession, one of the most common questions we field is, “Why are we poised to bring value when data and circumstances are constantly changing?”
Repeatability is the keystone to a positive ROI on virtually any analytics project. When you can do analysis, and understand market drivers influencing your business at a point in time, that has dependable value. However, it’s limited as soon as market conditions change. In the current economic environment, things are changing fast and frequently. Many analytics projects may not be worth running if the cost to conduct them exceeds the immediate value, knowing the shelf life is short.
Within the array of today’s mutable data are units of information that are viable business indicators for your company. The problem is filtering the millions of data elements to find these kernels of insight. Unable to process all that information manually, the unique business indicators are unattainable and unfathomable. If you have a repeatable modeling process that can adapt to changing market conditions to feed the changing information into repeated business processes, then you have something that brings value over and over again and can pay for itself repeatedly.
Until recently, econometric modeling still entailed the physical gathering and manipulation of external data by people, typically in spreadsheets. Now, thanks to new technologies like machine learning, advanced analytics, and cloud computing, data-rich econometric calculations are possible. It is impossible to overstate the importance of these predictive capabilities.
Prevedere has pioneered technology to garner relevant live connections from 3.5 million external datasets for analysis, with our proprietary AI engine. Our technology continually seeks new and changing correlations to business performance and algorithms that create projections that update alongside new data-point releases. Together, our platform creates a repeatable process that can prove valuable and cost-effective, where other predictive analytics efforts may have fallen short in the past.
As a result of the COVID-induced recession, virtually every business will need to retool their forecast planning. Prevedere developed the Economic Scenario Planning Solution to address the current business landscape in which data is evolving at unprecedented rates and is not following the patterns used in traditional forecasting models.
The Economic Scenario Planning Solution provides companies with a clearer vision to revise forecasts and identify potential scenarios that could impact industries. This offering enhances an organization’s ability to build dynamic planning models and adjust quickly to possible market changes in advance of any key inflection points.
About Econometric Modeling
The value of analyzing external data to forecast future performance was suggested decades ago in a 1971 Harvard Business Review article. This econometric modeling methodology showed great promise, demonstrating that trends in general economic conditions altered a product’s future sales rate. These “leading economic forces,” the article stated, influence “subsequent changes in specific industries.”
Importantly, the article affirmed that historical patterns in external data can be expected to persist for a period of time. “Statistical techniques are based on the assumption that existing patterns will continue into the future. This assumption is more likely to be correct over the short term than it is over the long term, and for this reason, these techniques provide us with reasonably accurate forecasts for the immediate future.”
The continuation of historical patterns in external data makes econometric modeling a desirable forecasting method. The challenge (at the time) was the human input needed to develop the models. The article concluded on an upbeat note, stating that more powerful mainframe computers would eventually take on this task.
Up until quite recently, econometric modeling still entailed the physical gathering and manipulation of external data by people, typically in spreadsheets. Now, thanks to new technologies like machine learning, advanced analytics, and cloud computing, data-rich econometric calculations are possible. It is impossible to overstate the importance of these predictive capabilities.
As a 2019 study by McKinsey & Co. states, “Analytics create value when big data and advanced algorithms are applied to business problems to yield a solution that is measurably better than before.”
Today, econometric modeling is considered the best method to predict near-term, mid-term, and even long-term business turning points, selected in 2018 as the most accurate predictor of identifying economic headwinds and tailwinds by the Institute for Business Forecasting and Planning.
Ignoring the predictive power of these models comes with a cost. Missed forecasts are the major reason why shareholder value decreases in public companies, often resulting in the replacement of the CFO for the person’s inability to see and analyze what lies ahead.
“The stakes are high,” the McKinsey study states. “Analytics has the potential to upend the prevailing business models in many industries. Those who advance furthest fastest will have a significant competitive advantage. Those who fall behind risk becoming irrelevant.”
To avoid this fate, companies need to pull out the handful of insights from the trillions of gigabytes of external data that correctly predict their future performance.
Planning and forecasting based on historical performance is no longer valid in today’s economic climate. As you look ahead beyond the immediate crisis and consider your business plans, having visibility to external economic factors and being able to consider how your company will fare in the “new normal” economy are paramount. This is what we call Intelligent Forecasting.
Prevedere helps companies answer, “what’s next?”, using global data and AI technology.
Whether it is a black swan event like the COVID-19 pandemic, less severe shocks like falling oil prices, or the regular contraction-expansion business cycles, Prevedere provides executives with insights on global forces impacting their business.