Decision making is driven primarily by intuition. The person in the leadership is often the one who drives the agenda, strategy, and priorities for the organization or team. The same digital technologies that are transforming a variety of industries is also changing the way that leaders make decisions. The fact that business processes are being carried out by computers or AI does not negate the importance of human judgment and intuition. Expediting the mundane through automation leaves much of the creative and strategic work for teams and leaders to do.

Big Thought: Quantitative Intuition is a framework for guiding data driven decision making. It leaves room for experience and gut to guide the path forward, while also backing up premises with insights driven by data.

Leaders can enable quantitative intuition through utilizing new approaches to solve problems. These approaches can include:

  • Asking both convergent and divergent questions. Convergent questions lead to single answers, and divergent questions lead to multiple answers, or identification of root causes.
  • Framing the problem. Put your problem into a larger context if that is possible. Be willing to identify knowledge gaps. Clarify priorities by gathering the input of others.
  • Working backward. Generate options for the actions that can be taken as a result of the problem that you are facing. Reverse engineer your data and to identify the blueprint from where the issue originated from.
  • Becoming a data interrogator. Assess whether the data that you are using is reliable. Put your data into the right context. Compare your data over time and to your competitors. Test your worst-case scenario boundaries.
  • Developing an intuition for numbers. To make an approximation, start with a rough estimate. Break the problem into smaller factors and make estimate for each. Ignore minor details.

To create a culture of quantitative intuition, build teams that have a variety of skills. These skills should include the ability to be agile, analyze the context of data, and to synthesize. Data scientists, data engineers, data translators and data artists will help you accomplish this. Choose leaders who can harmonize among different skillsets to deliver value to the broader organization.

To learn more about QI, read Decisions Over Decimals by Christopher Frank, Paul Magnone and Oded Netzer.

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