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How do you communicate the importance of variance explained to non-statisticians?

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In the world of Business Intelligence (BI), variance explained is a key concept that sheds light on how well your data model captures the patterns within your data. Imagine you're trying to predict sales for the next quarter. If your model's variance explained is high, it means the factors you've considered do a good job in predicting those sales figures. For non-statisticians, think of it as the model's ability to capture the essence of a story. The higher the variance explained, the more of the story you know, and the better your decisions will be based on that story.

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Carlos Cervantes Lepe

Business Psychology | ?? People Analytics Consultant | Country Business Manager | Digital Marketing
Chapmann Leung, CFA, ACCA

Financial Manager at FedEx Express

1 BI Simplified

To convey the significance of variance explained, use relatable analogies. Consider a weather forecast model; if it has high variance explained, it means that the model accounts for most factors that influence weather patterns, resulting in accurate predictions. Just as you would plan your day better with a reliable weather forecast, in business, understanding variance explained helps you trust the predictions and insights derived from your data models, enabling more informed decision-making.

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Carlos Cervantes Lepe

Business Psychology | ?? People Analytics Consultant | Country Business Manager | Digital Marketing
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Para efectos comerciales la varianza explicada es el grado de elementos que has considerado para hacer un pronóstico. Como ejemplo, si predices que vas a crecer en el a?o, podrías considerar elementos como precios de tus competidores, gasto en publicidad, la temporada, ventas históricas, etc... Si tu varianza explicada es alta , supongamos 80 %, significaría que podrías explicar el comportamiento en ventas y atribuirlo a los factores considerados, el resto (20%) sería por factores que no estás incluyendo (ej. proveedores, inflación, etc). Otro ejemplo sería tu varianza explicada es del 40%, esto querría decir que el 60% del comportamiento en ventas se debe a circunstancias o factores que no haz incluido en tu modelo...

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2 Real-World Impact

Discuss the practical implications of variance explained on business outcomes. A model with high variance explained can accurately predict customer behavior, sales trends, and risk exposure, which directly affects strategy and profitability. This clarity allows you to allocate resources efficiently, target the right market segments, and avoid potential pitfalls. It's like knowing which investments are likely to pay off, rather than taking a shot in the dark.

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Chapmann Leung, CFA, ACCA

Financial Manager at FedEx Express
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Another important is to create a story and message to senior management on what are the pain points of business and how to improve the business with action and impact. This is the value of financial analysis to support business owners on taking action instead of only understanding the actual problem

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3 Decision Confidence

Highlight how variance explained impacts confidence in decision-making. When a significant portion of variance is explained, it implies that the model's predictions are based on solid evidence from historical data. This assurance is crucial when you're making decisions that could affect your company's bottom line. It's like having a trusted advisor whose recommendations are usually spot on, giving you the confidence to act on those recommendations.

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4 Communicating Value

Explain that variance explained is a measure of value from your data insights. In BI, you're often tasked with extracting valuable insights from raw data. Variance explained essentially quantifies how valuable these insights are by showing how much of the outcome they can predict. It's akin to understanding the worth of a piece of information before betting on it in a high-stakes game.

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5 Beyond Numbers

Emphasize the importance of looking beyond just the numbers. While high variance explained is desirable, it's also important to understand what it doesn't tell you. It won't reveal which specific variables are important or how they interact with each other. Therefore, while variance explained is a powerful tool in your BI toolkit, it's part of a larger narrative about your data that requires further exploration and interpretation.

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6 Continuous Learning

Finally, stress that understanding variance explained is part of an ongoing learning process in BI. As you become more familiar with how your models work and what they're telling you, you'll be better equipped to ask the right questions and make adjustments that can lead to even more accurate predictions and valuable insights. It's a journey of continuous improvement, where each step forward can lead to more refined strategies and successful outcomes.

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7 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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How do you communicate the importance of variance explained to non-statisticians?

1

2

3

4

5

6

7

1 BI Simplified

2 Real-World Impact

3 Decision Confidence

4 Communicating Value

5 Beyond Numbers

6 Continuous Learning

7 Here’s what else to consider

Business Intelligence

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How do you communicate the importance of variance explained to non-statisticians?

1

2

3

4

5

6

7

1 BI Simplified

2 Real-World Impact

3 Decision Confidence

4 Communicating Value

5 Beyond Numbers

6 Continuous Learning

7 Here’s what else to consider

Business Intelligence

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