“Data For Good Decisions” Series

Mental shortcuts are valuable because it would be incredibly demanding, almost paralyzing, to process every piece of information – significant or trivial – in order to make a decision. Our use of mental shortcuts presents a double-edged sword to intuitive decision making. On the one hand, we need these mental shortcuts to navigate decisions efficiently when we cannot possibly have all the information. On the other hand, relying too much on unconscious processes leaves us prone to biases in the important decisions we are undertaking. As leaders, we all have probably used intuition to make some important decisions. If we know that intuition is subject to bias then we may ask ourselves, how can we leverage our intuition while ‘guarding’ against biases?

In our Data for Good Decisions series, we conceptualize a ‘data-driven mindset’ as a systematic process for integrating metrics and other forms of data to test assumptions formed through our intuition. Approaching challenges with a data-driven mindset is considered a competitive advantage for leaders because it enables swift identification of business challenges and action before it’s too late. By adopting this mindset, we are actively working to minimize the influence of biases (although, it is worth mentioning that we can never be free of them). Now more than ever with unlimited data at our fingertips, adopting a data-driven mindset can help us become knowledgeable data consumers able to draw meaningful conclusions and make important decisions.

As we’ve discussed so far in this series, intuition is important for leaders, especially in a world where information is vast, problems are complex, and decisions need to be made quickly. While it is probably easier and faster to rely on intuition, doing so can introduce biases which can erode decision quality over time.

A data-driven mindset—one that honors intuition while offering a structured method for testing it—can be a practical way to reduce biases in our decision making. It is worth mentioning that it would be misleading to suggest that data alone solves the problem of bias. In fact, a lot of data are subject to bias. This is why we value an integrated approach that leverages intuition as a starting point and bolsters its impact on decisions with data.

When working to answer a research question or add support to our intuition, it is necessary to assess the quality of our data. Poor data often can be worse than no data, leading to flawed interpretations and misinformed decisions. An important disclaimer here is that most data has flaws and thus limitations. The key is to consider the data in the context of our question (hence why critiquing our assumptions and understanding the full picture of the broader problem is so important) while also weighing the flaws. By doing this, we are able to better anticipate the utility and limitations of the conclusions we draw from the data. In order to evaluate data quality, consider the following characteristics…

In the not-so-ideal scenario where your data doesn’t support your hunch, do you stop there? You might, but there is a lot of learning that comes from results you do not expect. You may challenge yourself and ask: are my assumptions about this problem flawed? What else have I learned along the way? What factors might I have overlooked?

We recognize that taking time to examine your results in the context of your research question, and broader research problem, is not always possible for leaders who need to make urgent decisions. However, the key is to lean into the ambiguity and understand that regardless of the result of an analysis, leveraging data to make decisions is an ongoing process. At each critical point—including the moment from examining assumptions, evaluating data, and interpreting results—there are opportunities to pause and get ‘feedback’ about how we understand the problem and the factors we perceive to be relevant (e.g. the data source, the data itself).

As we think about ourselves using a data-driven mindset at work, it is important to note that our environment—in particular, our organizations—shape our effectiveness in being able to truly leverage this mindset. Imagine an organization where leaders believe the best decisions are rooted in data and so they model data-driven decision-making every chance they get. They challenge their teams to support ideas with data. Embedded in the organization is the belief that data is incredibly valuable and so, accessibility to data is prioritized through processes, technology, and infrastructure. Even more, the organization recognizes that if it expects everyone to make data-driven decisions, it must build data literacy skills through trainings and workshops so that employees feel competent and empowered to use data to tell stories, solve problems, and make decisions. Intriguing, right?