The guide to accurate forecasting
and its impact

What is a leading indicator?

The term leading indicator was first used in economics. The objective was to determine measurable indicators that if monitored could predict the ups and downs of the economy in the future. If the number of mortgage defaults begins to increase that’s a warning signal (a leading indicator) that the economy might also head for negative changes.

Other leading indicators for the economy include manufacturing activity, the stock and housing markets, consumer confidence, and the number of new businesses entering the market. Leading indicators are extremely helpful when it comes to quickly identifying market shifts.

A common problem for companies that do not use leading indicators in their forecasting is that they miss the shifts when they occur and are therefore at risk of attaining large discrepancies between the forecast and outcome. This is when it starts getting costly because they don’t have the capacity nor the time to actualize the alterations needed within, for example, production or sales that could potentially resolve the discrepancy. They are also usually unique to companies so they can be a bit more challenging to build, measure and benchmark.

"A common problem for companies that do not use leading indicators in their forecasting is that they miss the shifts when they occur, and are therefore at risk of attaining large discrepancies between the forecast and outcome."

What has leading indicators have to do with accurate forecasting?

Companies of today are stretching their capacities on all levels: production, work environment, recruitment, marketing, and so forth. All in order to grow and outrun, or keep up with, competition. But rapid growth spurts and fast decision-making tend to come with certain pain points. Such as pushing the limits of both workforce and production, leading many companies to exceed their finances and take unnecessary risks. As a way of mitigating risk, trend analysis has long been a go-to strategy for businesses to avoid costly mishaps and stay ahead of competitors.

Trend analysis is the process of looking at the current values of particular metrics to predict future ones. This can be stock prices, sales figures, production, and price trends. By finding patterns in the data, it’s possible to determine whether a current market trend, such as gains in a particular market sector, is likely to continue or not.  

But to evaluate the effectiveness of trend analysis, all components need to be considered -- seasonal, cyclical, and long-term trends. If done wrong and without a high level of accuracy, could have severe consequences for the business. Therefore, attaining an understanding of how external factors affect the market by knowing which data to use and how to use it for forecasting rises to be the key to unlocking businesses’ success and potential. 

The importance of leading indicators

Identifying the right leading indicators can improve your capacity planning

A market forecast bought from an external provider usually only takes public data into account. Using Indicio, users get access to data from data providers within selected sectors, globally. By applying the latest in statistical learning to the models, you can easily find leading indicators that affect the market, and its impact on your organization.

Oftentimes, market intelligence strategists create forecasts using their data in Indicio to forecast their market share. Many are not aware of the data goldmine they are currently sitting on. Internal data such as order volume, promotions, and stock levels can improve one's sales and market forecast accuracy anywhere from 40 to 60 percent and invalidate a general market forecast from a market research firm that only takes public data into consideration.

Additionally, by adding external data such as purchasing managers index, financial volatility, and Chinese freight volumes, it is now possible to capture economic development, thus identifying market shifts in advance, instead of relying on historic data.

How does a data-driven approach to forecasting look?

Built on the back of machine learning, Indicio's forecasting methodology involves running advanced statistical models and incorporate big data simultaneously, without giving way to the human factor.

It's key that the models are built to be as de-biased as possible because it's not a single person who makes the last call. Rather, the platform chooses the most appropriate machine learning algorithms, then automatically optimizes data pre-processing, feature engineering, and tuning parameters for each algorithm to create and rank highly accurate models.

It then recommends the best weighted set of models to deploy for an organization's data and prediction target. Thus, instead of creating statistical models that would take a statistician months to develop, with Indicio, you get an almost instant build of hundreds of models and deploy the best-performing model within hours.