Last Updated: February 10, 2021

According to research by analyst firm Gartner, between 70% to 80% of corporate business intelligence projects fail to deliver the insights the business needs. Why? Three major reasons: The inability of most enterprise analytics tools to incorporate internal and external data, the difficulty in gathering the right data to use, and the disconnect between insights and the decisions they intend to drive. 

In other words, business leaders lack the confidence to make decisions based on the data available to them currently. These challenges have only heightened due to COVID-19. Business intelligence must evolve to address these difficulties and meet executives’ needs today, especially amid such volatile economic conditions.

A More Holistic Approach to Planning

Economic intelligence refers to the holistic approach of incorporating external signals with internal knowledge into robust econometric models that provide the most reliable predictors of the future. Economic intelligence consists of the procedural and technical infrastructure that collects, stores, and analyzes macro and microeconomic data for companies. Prevedere’s AI-powered engine collects and analyzes external data to extrapolate leading indicators and inform economic forecasting. 

Economic intelligence is a more holistic approach to future planning compared to business intelligence, which refers to the procedural and technical infrastructure produced within a company. Economic intelligence is particularly useful as it goes beyond a company’s internal data to provide more robust and data-driven analytics during forecasting.

Economic intelligence relies on the quantitative application of statistical models using data to forecast future historical data trends known as econometrics. Econometric forecasting models leverage companies’ past performance and economic signals to predict future outcomes. These economic signals are referred to as leading indicators and are causal factors that project a future change in business performance. A leading indicator can be anything from an internal signal like a change in price to an external signal like unemployment. These leading indicators are the basis of our predictive models that inform intelligent forecasting. 

Prevedere’s engine helps businesses understand what factors have already and will continue to influence their performance, regardless of whether it is internal or external. The most basic level of economic intelligence allows companies to collect digital information, find a relationship between data and an organization, and then test or produce econometric models from that data. 

Leveraging AI for Better, More Accurate Models at Scale

The more advanced economic intelligence systems, such as Prevedere’s, push these tools even further and leverage AI and machine learning to produce better quality and more accurate models at scale. Specifically, this means having the ability to report and distribute insights, proactively send alerts, and update daily as internal or external factors change. Ultimately, economic intelligence platforms, like Prevedere’s, integrate into already existing planning and reporting tools within a business to promote and publish production models.

While implementing and using economic intelligence platforms can seem daunting to those without a more technical background, Prevedere’s services are designed to be used by anyone from the data science team to the C-suite. Typically, data science teams build and maintain the analytics so that business leaders and functional or operational teams can use it to inform successful planning and decision making. The holistic insights provided by economic intelligence can be key pieces to decision making, whether in the office of finance, sales, marketing, demand forecasting, or supply chain. 

For more information, download the Evolution of Business Intelligence report, which was written in partnership with Microsoft and Dr. Barry Keating to describe the critical turning point currently facing traditional analytics, as technology and data merge to help business leaders make smarter, faster, forward-looking decisions.