If you had a crystal ball that could tell you exactly what would happen tomorrow, you would probably take a trip to the nearest casino. I know I would.

In the real world, the global financial services industry known as the big players managing assets, private banking, and insurance, deals with billions of euros and still remains consistently profitable. Some might think that they have top-secret magic crystal balls or DeLorean time-traveling cars to predict the seemingly unpredictable future. Instead, economists and analysts rely on the next best thing: predictive market research. Even though a term like predictive market research isn’t as cool as crystal balls or Dr. Brown’s DeLorean, it remains fascinating.

When most people hear “market research,” they picture someone standing in a shopping mall with a clipboard, asking you on your busiest day what brand of toothpaste you prefer. But in macroeconomic strategy, market research is a sort of science focused on analysing current and future market trends in our messy lab that we refer to as the economy. This discipline dictates how massive institutions (that deal with billions of euros, every single day) allocate their cash, protect or hedge themselves against incoming recessions, and stay ahead of the competition.

Finding the signal in the noise
We live in an era with too much raw and chaotic information. In that setting, the core job of an economic analyst is to then uncover and examine this data to find hidden patterns.

How is this actually done? Economists gather massive amounts of information from (for instance) business databases to build large datasets with columns and rows, and multiple variables. In financial data, this is usually in the form of time series (how the same variable e.g. GDP changes every year in a certain country) or panel data (how inflation changes across different countries and years/months). They then deploy statistical tools to crunch the numbers, and ultimately predictive modelling (simplified mathematical equations of an economic phenomenon) to separate movements in a variable into core components that affect it, and the unpredictable rest (economic noise).

A perfect modern example of this is the rise of ESG (Environmental, Social, and Governance) standards. Historically, analysts only needed to look at a traditional balance sheet (overviews of assets and liabilities/debt that funds the company) to predict if the company is going to grow and make more money tomorrow.

Today, predictive market research needs to know revenue and costs, but also external side-effects of their operations, known as externalities. Externalities are the costs of doing business not reflected in balance sheets, such as noise pollution (and worse sleep quality for nearby residents) from constructing a new Westfields shopping centre. Today, these externalities are previously unpriced costs businesses used to impose on society, like its carbon footprint or supply chain labor practices (e.g. child labour). An economic analyst has to quantify these strange and non-traditional metrics to predict how future climate regulations or shifting consumer ethics will impact a company’s operations. Tricky, right?

Whether you are predicting ESG risks or modelling complex relationships with econometric methods on traditional financial metrics, the goal is to look at messy data to forecast where a sub-sector of the market is heading next.

The art of translation
However, having the right data and the perfect predictive model is only half the battle. You can build the most elegant, statistically significant forecast in the world, but if the end-user doesn’t understand it, the work is useless.

This is where economics shifts from a pure science to an art form. The most critical skill in market analysis is translation. It would be naive to think that someone who hasn’t stared at your months of work will understand it right away. Economists and big consulting groups like the big 4 do this by writing reports with visual adaptations of the data so that decision-makers can understand the narrative at play.

Why it matters
Good market research is like Google Maps (or Apple Maps, but that’s another debate). It prevents institutions from flying blind. Analysts examine competitor and product analysis within the financial services industry to provide a map that guides the sector through confusing economic environments. In the end, it ensures that the institutions are two steps ahead when the economic landscape shifts.