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What are the most effective ways to measure forecast accuracy?

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Forecast accuracy is a key metric for program managers who need to plan and allocate resources effectively. It measures how close the actual outcomes are to the predicted ones, and helps identify and mitigate risks, gaps, and opportunities. But how can you measure forecast accuracy in a reliable and meaningful way? In this article, you will learn about some of the most effective methods and tools to track and improve your forecasting performance.

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Henrique Martins

Portfolio Manager | Program Manager | Project Manager | Product Manager | PMO | Agile | Strategic Layer | Engineering &…
Aboubaker Jadelaoun

Quality Assurance | Organizational Excellence | Process Re-engineering | CMQ/OE | Lead Auditor ISO 9001:2015 | PMP |…

1 Forecast error

The simplest way to measure forecast accuracy is to calculate the forecast error, which is the difference between the actual and the forecasted value. You can use absolute or relative values, depending on your preference and context. For example, if you forecasted a revenue of $100,000 and the actual revenue was $90,000, the absolute forecast error is $10,000, and the relative forecast error is 10%. However, forecast error alone does not tell you much about the quality of your forecasting process, as it can be influenced by many factors, such as seasonality, randomness, or outliers.

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Aboubaker Jadelaoun

Quality Assurance | Organizational Excellence | Process Re-engineering | CMQ/OE | Lead Auditor ISO 9001:2015 | PMP | Business Transformation | Risk Management |
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Forecast accuracy may be impacted by many hurdles, Such as the quality of data used, so if data are not accurate, or biased, our forecast may be flawed. oversimplification, by not accounting for all factors and relation ships that may affect our program, in addition to unpredictable events or risks that may affect our programs, where all risks should be predicted based in lessons learned from previous projects, and by several methods such as brainstorming sessions with all key stakeholders, as those risks may have a huge impact on our overall program progress, budget, and schedule, risks may be Natural disasters, political upheavals, technological breakthroughs, or other unexpected events that can significantly deviate our forecasts.

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Vivek Raj

ACCA || CFP? || CWM? || IFOA || IAI | Financial Analyst | Harvard HPAIR'21 | IIT Patna'24 | Queen Margaret University'25 | Thought Leader in Finance & Strategy | Global Finance Mentor | Innovating Business Analytics
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To see how good your predictions are, compare them to what really happens. Use things like Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE) these numbers show how close your predictions are to the actual results. Also, check the percentage error to understand how big the mistakes are compared to the real values. Keep doing this regularly and tweak your predictions based on what you learn. By using these simple measurements, you can figure out how accurate your forecasts are and make them better over time.

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2 Forecast bias

Another way to measure forecast accuracy is to assess the forecast bias, which is the tendency of your forecasts to be consistently higher or lower than the actual values. Forecast bias indicates whether your forecasts are overestimating or underestimating the outcomes, and by how much. For example, if you always forecast a higher revenue than the actual one, you have a positive forecast bias, which means you are too optimistic. To calculate the forecast bias, you can use the mean forecast error (MFE), which is the average of all the forecast errors. A positive MFE indicates a positive bias, and a negative MFE indicates a negative bias.

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Vivek Raj

ACCA || CFP? || CWM? || IFOA || IAI | Financial Analyst | Harvard HPAIR'21 | IIT Patna'24 | Queen Margaret University'25 | Thought Leader in Finance & Strategy | Global Finance Mentor | Innovating Business Analytics
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Forecast error is like checking how much your guesses are different from what really happens. It shows if you're getting things right or if there are big mistakes. You can use numbers like Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE) to measure this difference. Now, bias is when your guesses always lean towards being too much or too little it's like having a consistent mistake. Watching both error and bias helps you understand how good your predictions are and if there's a pattern in how you're making mistakes, so you can make better guesses next time.

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3 Forecast accuracy rate

A more comprehensive way to measure forecast accuracy is to use the forecast accuracy rate (FAR), which is the percentage of forecasts that are within a certain range of the actual values. For example, if you set a 5% tolerance range, and 80% of your forecasts are within 5% of the actual values, your FAR is 80%. The FAR gives you a sense of how precise and consistent your forecasts are, and how well they capture the variability of the outcomes. You can adjust the tolerance range according to your needs and expectations, but keep in mind that a higher range will result in a higher FAR, and vice versa.

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Vivek Raj

ACCA || CFP? || CWM? || IFOA || IAI | Financial Analyst | Harvard HPAIR'21 | IIT Patna'24 | Queen Margaret University'25 | Thought Leader in Finance & Strategy | Global Finance Mentor | Innovating Business Analytics
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The forecast accuracy rate is like figuring out how often your guesses are correct. It shows the percentage of times you get things right out of all your predictions. For example, if it's 90%, it means you're correct about 9 times out of 10. Watching this rate helps you see how good your predictions are and helps you make them better.

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4 Forecast performance dashboard

A practical way to measure forecast accuracy is to use a forecast performance dashboard, which is a visual tool that displays various metrics and indicators of your forecasting performance. This dashboard can help you monitor and compare your forecasts against the actual values, identify trends and patterns, as well as spot anomalies and errors. You can create your own dashboard with software tools or spreadsheet applications, or use templates and examples available online. Some of the elements you can include in your dashboard are a line chart that shows the actual and forecasted values over time, a bar chart that shows the forecast error or bias for each period or category, a table that shows the FAR and other statistics for each period or category, a gauge or meter that shows the overall forecast accuracy or performance score, and a histogram or box plot that shows the distribution of the forecast errors or biases.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Henrique Martins

Portfolio Manager | Program Manager | Project Manager | Product Manager | PMO | Agile | Strategic Layer | Engineering & IT
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When we talk about probability we have some methods and tools to try to be as assertive as possible, some that I can mention are very famous are crystal ball, lang factor, a very rich material for defining contingency from AACE International, among others.

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What are the most effective ways to measure forecast accuracy?

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1 Forecast error

2 Forecast bias

3 Forecast accuracy rate

4 Forecast performance dashboard

5 Here’s what else to consider

Program Management

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What are the most effective ways to measure forecast accuracy?

1

2

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5

1 Forecast error

2 Forecast bias

3 Forecast accuracy rate

4 Forecast performance dashboard

5 Here’s what else to consider

Program Management

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