Why relying solely on market forecasts could be compromising your business decisions. And what to do about it.

What's the benefit of knowing what goes into your market forecast?

You want to know how robust the forecasts generated are. Can you depend on it? How do you explain how this forecast arrived at its conclusion? 

Statistical models
Having an idea of which statistical models were used to generate a market forecast is how you can ascertain the accuracy and reliability of the forecast you’ll base your decisions on. 

Data sources
By getting a clear picture of the data sources, you’ll be able to evaluate the relevance and quality of the data used in the forecast. Truly understand the anatomy behind the forecast you’re looking at. This is of significance because different data sources could have underlying biases or limitations, and understanding where the data comes from can help in identifying potential sources of error or uncertainty.

Perhaps, you have an internal team of analysts that works actively with forecasting.

Having this information is a great source to help you or your team:

- Replicate the forecast methodology

- Test different statistical models, test out new leading indicators

- Benchmark results

- Refine your existing forecasts All of this optimizes transparency and reproducibility and also makes it easy to present it to your key stakeholders. 

When you have all that data - an overview of your market through market forecasts, your internal data and indicators, and internally-generated forecasts, here’s how you can successfully evaluate and refine your forecasts continuously:

Monitor forecast accuracy: Regularly evaluate the accuracy of their forecasts against actual outcomes to identify areas for improvement.

Identify and address errors: When errors are identified, market intelligence managers should investigate the causes and adjust their models or data sources as needed.

Incorporate new data: As new data becomes available, incorporate it into your models (that you’ve identified)  and evaluate its impact on forecast accuracy. Indicio does this automatically in minutes by building & backtesting models, and performs model averaging, which gives you a clear picture of which of these indicators are relevant to your main variable.

"The more reliant you are on the market forecast,
the greater accuracy you’d need from it.

Typically, market reports are generated yearly.
If you’re factoring this data into your primary forecast,
how timely is the data?"

How individualized is the information presented in these market forecasts, and why might it be important to your forecasts?

‍Granted, you might just be reliant on these market forecasts acting as a support to your primary forecast.

In that case, it might provide a general overview of the market you’re operating in. Market reports have a tendency to provide generalized information about an industry, and the data may not be specific to your organization's forecasting needs. This lack of specificity can result in inaccurate forecasting that does not align with the organization's goals or market position. 

Why? It is tricky and can be a challenge to capture the specific leading indicators that have a direct impact on your business.

Some markets are more complex than others - that could be true for your market. If you’re not identifying and using the relevant leading indicators in your forecasting, how does this impact your forecast accuracy? 

This depends.

How reliant are you on the market forecast to dictate your organizational decisions?

The more reliant you are on the market forecast, the greater accuracy you’d need from it.

Typically, market reports are generated yearly. If you’re factoring this data into your primary forecast, how timely is the data? It would potentially not capture the market trend shifts that might occur in the following month or the upcoming quarter, and this delayed intel could culminate in compromised decisions.

Delayed intel = Not entirely accurate forecasted numbers

In today's fast-paced business environment, relying on outdated market reports can be costly.

By the time these yearly reports are published, the data may have already changed, rendering these insights (that you might base business decisions on) irrelevant. And this is where having a tool where you can plug in new data and interplay that with your internal data can provide a significant advantage.

‍Here's an example.

Forecasted numbers in a market report are based on passenger car registration numbers. These registration numbers are usually only reported on and available the month after. This time lag is reflected in the information you receive in a market report. 

And this means you’re not dealing with the most updated intel. 

So what then?

‍In Indicio, you generate real-time forecasts, meaning you can access the most up-to-date insights on market trends, consumer behavior, and other relevant data points. Immediate and quick access to economic data sources like FRED, Refinitiv, and Oxford Economics, lets you see the impact of any change in the market.

This allows you to make timely, informed decisions that can help you stay ahead of the competition and make strategic moves before it's too late. (And expensive.)

By leveraging the benefits of real-time, accurate forecasts, you can optimize your business strategy, be ready to pivot and improve your bottom line.

What’s the alternative?

We’re not suggesting that you should disregard market forecasts in their entirety. Rather, use it to keep updated and get a good overview of the state of your market.

But when it comes to making decisions - decisions that allow you to leave room for uncertainty, and ensure that you’re ready to meet and plan for market shifts, you might want to rethink your forecasting strategy.

Benefiting from no-code forecasting, built by statistical models experts and driven by ML

By using algorithms and statistical models, Indicio analyzes large sets of historical and current data to identify patterns and trends and displays their impact on your forecasted data.

With a methodology that is both designed to provide accurate forecasts, all while incorporating your internal data, it provides you with insights into future market trends that could have an impact on your specific business concerns. How exactly are these indicators identified?

It's essential to identify the leading indicators that are optimized for accuracy.

How can this be achieved using Indicio? With Indicio, you can access multiple data sources in just a few clicks, giving you access to normalized, aggregated leading indicators with high levels of accuracy and ultra-low latency. 

What's the methodology?

Our methodology identifies statistical models with high out-of-sample accuracy, meaning that the model's accuracy is evaluated at each step forward, rather than just having a high model fit.

This approach is more valuable because we're looking for a model that describes the future accurately, rather than one that relies solely on historical data. It's critical in helping you determine the data points that best represent your business's current situation and market position, enabling you to make strategic decisions moving forward.

Get access to real-time updates based on changes in market conditions or other relevant factors by conducting a scenario analysis of your forecasted data. This ultimately gives you the agility to adjust your ongoing strategies and plan accordingly.  

A repeatable forecasting process limits inconsistencies and errors

Bias and inconsistencies in data analysis are a minefield. We’ve discussed what type of biases can occur here, correlation bias for starters.

Individual biases can influence the assumptions made by analysts, which could lead to inaccurate forecasts.  How can you work around that? 

Putting a repeatable process in place can improve the accuracy and reliability of forecasts, leading to better decision-making and more successful outcomes. This could mean being able to make monthly updates easily, having easy access to identify new variables, and being able to explain the results presented in the forecast.) 

"Studies show that 64% of annual forecast targets become outdated within four to six months, and only about 1% of businesses accurately forecast with a 90% accuracy when looking one month ahead."

What’s the win when increasing the frequency of your forecasts

Let's not overlook the benefits of increasing the frequency of your forecasts, something which general market forecasts might not provide.

Amidst the current uncertainty, there’s a clear advantage to generating or updating your forecast every month or more frequently, in comparison to only doing so yearly.

Studies show that 64% of annual forecast targets become outdated within four to six months, and only about 1% of businesses accurately forecast with a 90% accuracy when looking one month ahead. It’s increasingly considered good practice to regularly reassess their market positioning to identify areas where they can increase efficiency.

That said, it's not just a matter of forecasting more often; it's crucial to have real-time visibility over the impact of your business's leading indicators. With instant access to real-time data, you can identify the most relevant leading indicators and ensure they're incorporated into your forecasts. 

Build a customized forecasting process that fits your business needs

While market forecasts provide a general overview of the industry, they may not be specific to your organization's business needs or have the capabilities to ensure 

Ensure that you understand the workings behind your market forecasts and get the agility to detect market trend shifts early that could have an impact on your business.

By incorporating new data into models, identifying and using the relevant leading indicators in forecasting, regularly monitoring forecast accuracy, identifying and addressing errors, you’ll make crucial steps towards a well-rounded forecasting process - one that’ll provide a repeatable forecasting process and give you results you can count on.