12-step Data-informed Decision Making Methodology

There is a common misconception about data-informed decision making. Once the right analytic tools are implemented and individuals are trained on analytics, the data will turn to knowledge and will translate to better decisions. It sounds great in theory.

But in practice, there is a spectrum of critical capabilities that need to be in place at an organizational level, including a data strategy, an analytics framework, a data literate workforce, diversity and inclusion, a culture of collaboration, creativity, and communication. At an individual level, making data-informed decisions requires systemic thinking, the ability to be aware of your biases, the ability to challenge the data, and the ability to accept failures and learn quickly from them.

There are many models out there for decision making. Our model blends together the need to ask the right questions, source the right data in the right format, critically appraise and analyze the data using an analytic framework, apply your personal expertise and that of others while being aware of any unconscious bias, communicating your decision to all stakeholders, and building a review framework and mechanism to monitor the decision and iterate through the process again based off the findings.