Earlier in the program, you framed your analysis by establishing your objective, theory, and model. Then, in Module 4, you defined a plan to either complete your analysis or test your model, based on the availability of data and/or data resources. Here, you’ll generate insight by carrying out your plan.
1.Implement Your Plan: Either complete your analysis by gathering data and applying your chosen analytic method, or test your model by making key assumptions and/or leveraging a few available data points. Here, you’ll share key outcomes from your analysis.
“What if I can’t access the data I need?”: It is not uncommon for data projects to run into surprise “roadblocks.” If you encounter a situation where critical data unexpectedly proves unavailable, you may be on the way to significantly expanding the bounds of your organization’s understanding of your world – a great thing! At this point, we recommend returning to the Guide to Identifying Data and Guide to Identifying Methods provided in Module 4. Can you identify a proxy for the unavailable data? If not, choose a method to test your model to provide initial insight and lay the foundation to gather the unavailable data post-program. Then implement this revised plan and move on to Step 2.
2.Provide Supporting Detail (Optional): As desired, provide 1-3 slides of supporting detail summarizing the analysis/test you performed.
3.Quantify Your Model: The purpose of doing the analysis was to quantify your model. Update your model using the results of your analysis or indicate any assumptions or “back of the napkin” calculations you made to test your model.
4.Generate Insights: The purpose of creating a model was to use it to generate business insights. What have you learned about how the world operates regarding your core metric and (if possible) what recommendation will they lead you to make?
5.Assess Potential Cognitive Bias In Your Theory: In this module, Professor Devin Pope will explore nine biases. Consider how they might have impacted your theory and, as relevant, identify steps you could take going forward to refine your analysis.
6.Assess the Potential Limitations of Your Analysis: Here, you’ll “stress test” your analysis by determining whether it might be subject to one or more common data pitfalls. For a further explanation of these limitations, refer to the Guide to Understanding Data Limits and Objection Handling located under the Resources tab in this Module.
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