Strategy Insight Ratio

Strategy Training Strategy Insight Ratio

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Young consultants make some very common mistakes when they start out, and I explain how to use the strategy insight ratio to correct these problems.

1) They tend to dedicate most of their ink to their analyses.

2) They tend to equate the complexity of their analyses with the value they are adding to the study.

3) They spend too little ink on insights.

In this podcast I will discuss two simple checks I would do when I was a partner reviewing the slides of engagement managers, associates and analysts. They allow you to construct a simple ratio which can be improved to improve the quality of your slides.

The part about analyses complexity will certainly surprise you. The complexity of the analyses we do in even complex corporate strategy studies is surprisingly low. While the analyses is simple, the way we arrive at the need to do the analyses is, however, not easy.

You will see this in the first study we are releasing under the strategy training library: careful study structuring + simple analyses + deep insights.

Training by ex-McK, BCG et al. Partners

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2 responses to Strategy Insight Ratio

  1. I completely agree. Strangely enough my consulting career also mainly involved capital intensive industries, but I suspect that is not a pattern. Thanks for the great lesson Tyler.

  2. I had the incredible luck of working with a consultant was was a former CIO, and previously ran an actual modelling company (full of PhDs). What I learned most from him is very similar to what you spoke of here – it is about proper structure. He cut his teeth as an engineer on billion dollar capital projects, so his thinking is incredibly systemic (not necessarily linear, but robust), and an incredible way of turning the complex into small manageable pieces that came together perfectly.

    The project was about rethinking how an entire department ran (becoming customer centric). We started the modelling project by re-establishing exactly what the final model reports would be used for, and how it would fit into the other two deliverables. Next, we build a high level “logic model” which consisted of visual/written descriptions of what inputs would be needed, and how they would be transformed step by step. At this point we knew what they wanted the outputs for (how it would help them) and we had validated our thinking with the client and made any adjustments based on their experience.

    In this project the model was probably 70% of the time to create, and it’s main purpose was to give visibility to costs in a way they had never been viewed before. But the value of the project came from the other 30% of our time, which was how they could use this model to support a customer centric view of their operations. Ultimately the model provided something measurable for management, but the insight came from teaching the client to think differently about how they manage their business, and prioritize projects using that thinking. The model (in conjunction with customer feedback) is merely a tool to help manage the costs and plan scenarios. The cultural shift to prioritize all projects along a customer centric view was the biggest change.

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