After building a demand-forecasting model with a ±4 % error margin, you must brief the company's CFO and COO at next week's steering-committee meeting so they can decide whether to invest in additional manufacturing capacity. Each executive has ten minutes and no technical background. Which communication approach will most effectively help them reach a decision during the meeting?
Email a CSV file of every forecasted data point and ask the finance team to create pivot-table analyses for the meeting.
Prepare a one-page executive summary slide showing a bar chart of forecast demand versus current capacity, bullet-pointing the expected financial impact and a recommended course of action.
Share the full Jupyter Notebook containing model code, hyper-parameter settings, and residual-error plots so the executives can review the methodology.
Demonstrate an interactive scatter-plot matrix of all model features and their correlations so the executives can explore the drivers of demand in real time.
C-level stakeholders typically need a fast, high-level view of business impact, not technical detail. A single-slide executive summary that pairs a clear visual comparison of projected demand versus current capacity with a brief narrative of financial impact and recommended actions delivers exactly the strategic information they require. The Jupyter notebook and scatter-plot matrix overwhelm non-technical executives with methodological or exploratory detail, while a raw CSV off-loads the analytical burden onto the audience. None of those alternatives supports quick, confident decision-making in the allotted time.
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Why is a visual bar chart better for communicating with executives than detailed analysis?
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What should be included in the financial impact bullets on the executive summary?
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What is the importance of tailoring communication to a non-technical audience?