What is a “good” forecasting process for executives and business leaders?

What is a “good” forecasting process for Executives and Business Leaders

A "good" forecasting should comprise of all critical aspects: accuracy and thoroughness but should be flexible enough to inform a wide range of vital business decisions – contract negotiation, capital reallocation, operation, and production plan and so on.

But the trickiest part for executives and CEOs is that there is no "standard" forecasting process. It's undeniable that different organizations focus on various sector-specific factors, business cycles and are pretty different on how they approach or utilize this forecast. A producer of automotive components will be keen on forecasting the price volatility of metals. Or a player in the agribusiness industry might use the estimates to improve their farming productivity.

Let's see how other business leaders feel about the forecasting process based on McKinsey's recent study. 40% of them revealed that the forecast is not precise and costs extra time and effort.



Another aspect is that 90% use financial measures as critical metrics for forecasting instead of forecasting decision-making in strategic or operational factors. For example, there has been limited attention to forecasting can help business from an executive decision-making perspective (e.g., investment decision making). Only focusing on financial metrics could be a deadly fallacy for executives and business leaders, because forecasting results can be used by both CFOs, CEOs and executives to present forward-looking financial measures and aid decision-making in strategic or operational aspects and immensely help them navigate through significant issues.



It's time for financial, strategic and operational executives to rethink and find a way to work together to enhance the decision making across the firm. CXOs can leverage the forecasting based on strategic or operating parameters to improve data-driven decision-making within the firm. In other words, CFOs and CEOs need to integrate real strategic or operational insights into forecasting, combine them with crucial financial forecasts to form a comprehensive picture about the company and aid executive decision making based on data.

The good news is that emerging technology makes the automation of Artificial Intelligence and Machine Learning way more accessible than in the past. With the advancement of technology, executives can use more granular data and advanced AI-based models to increase the accuracy of the forecasts and derive meaningful insights for decision making. We list three critical questions to guide the executives to increase the adoption, accuracy and reliability of forecasting within their firms.

Have we built a momentum case?

Many financial planning and analysis teams only focus on economic forecasts but rarely discuss how external and market cycles affect their key operational or strategic metrics. A live and unbiased momentum for forecasting will include internal data from all sources: finance, sale, operation, purchasing department and critical external factors: market trends, price fluctuation, market cycle. Through AI/ML platforms, executives can assess business decisions and even understand the drivers in the market affecting their businesses.

Have we explored automation to forecast?

Once you have determined the critical input data, you need to combine them into the forecasting modellings in the easiest way so that your employees across your organization understand the process without any technical know-how. It's not easy to integrate data and derive meaningful insights if we follow the traditional forecasting process with fixed steps, leading to inaccurate predictions. Advancements in AI/ML are modelling, and cloud infrastructure makes this process easier and smoother. Platforms enabling AI/ML forecasting can allow executives across the organization to derive meaningful insights from the internal and external data quickly. AI/ML platforms can also be integrated easily into your available database with flexible APIs.

Have we measured effectiveness at a detailed level?

Taking a closer look at data and measures at a fine-grained level, executives and business leaders can spot trends in key metrics. Specifically, the drivers explaining the forecasts can help them understand your business better, helping you clearly understand why a specific metric is showing an upward or downward trend. Further, it helps your team to be prepared for short-term and mid-term business fluctuations and serve as an early warning indicator for the business risks.

Getting Started Now with Forecasty.AI

Business leaders and executives can start with small, steady steps by reuniting different teams to build the organizational momentum of data-driven decision-making. Explainable and easy-to-use AI platform from Forecasty.AI can support your next step to help your employees across your administrative units derive highly accurate predictions, making business decisions faster and smarter.

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