The power of baseline data in measuring impact

This is my second year running the Data Champions program and as I'm embarking on the course with a new group of participants this year, I'm struck by one of the key learnings from last year's cohort - the significance of establishing solid baseline data. Setting up and defining baseline data proved pivotal when the Data Champions participants presented the impact of their year-long efforts. While we had some fantastic successes and really impactful projects, I noticed that those with the strongest baseline data were able to provide so much more tangible evidence of their accomplishments.

Just for a moment, consider the analogy of a successful weight loss journey. To be able to measure the impact you need specific details like the number of kilos lost, the duration of the journey, or the noticeable changes in clothing fit. And to get that data, you obviously need to establish where you're starting at.

Similarly, in the workplace, discussing the impact of projects, teams, and initiatives becomes professionally more meaningful when backed by a solid baseline. Even when my own journey into the world of data started in the education sector, tracking student outcomes allowed me to witness gradual improvements. These really served as small victories that sometimes were only perceptible because I was able to compare my students' successes to the baseline data I'd collected.

Often we look to quantitative metrics for baseline data because they serve as straightforward data, especially in areas like sales, revenue, or profit margins. However, in many scenarios, relying on qualitative data for your baseline is so valuable because this kind of data cannot be so easily retrofit. We can easily go back and generate spreadsheets of sales figures at the time but we so often forget what perceptions were like at the beginning of a project, or what our reflections on current practices were. This kind of data is not so easily gathered after the fact and that's why I emphasise the importance of collecting qualitative baseline data.

Incorporating perceptions, both internal and external, early on in a project can set the stage for meaningful assessments down the line. While quantitative metrics offer clear benchmarks, qualitative data (often harder to capture) enriches the narrative by providing context, sentiment, and the human aspect of change. Not only that, I often talk about how crucial triangulation is and collecting qualitative baseline data is a really effective way to ensure a holistic data set and view of your impact.

So what are some examples of qualitative baseline data? Well process data, often neglected, offers one avenue for qualitative baseline information. Changes in processes, documented through visuals, screenshots, or even photographs, serve as tangible evidence of transformation. Things like changes in meeting structures, agendas, or workflows can also be captured visually, allowing for retrospective analysis and showcasing the journey of improvement. Even in an era of survey fatigue, there are creative ways to extract valuable qualitative data without necessarily using surveys, such as personalised emails asking about perceptions or other targeted questions sent to a few key stakeholders before starting a project.

One unique approach I use with the Data Champions is video diaries, where participants record their thoughts, concerns, and observations at the beginning and periodically throughout their time in the course. We revisit these videos each time we meet and not only do they unveil progress but also the evolving mindset and confidence of the individuals involved - something that is so difficult to capture retrospectively because perceptions are something we easily forget as our knowledge grows throughout a project.

In summary, while quantitative metrics provide a numeric snapshot, qualitative baseline data breathes life into the story, making it relatable and impactful. So before you embark on your next project, consider how actively seeking and documenting three or more data sets can provide a robust baseline and ensure that when you revisit your data journey, you can truly measure the impact of your project. And by taking the time to focus your efforts on collecting qualitative baseline data, you can ensure the story told is not just numerical but rich with experiences, reflections, and the undeniable proof of transformation.

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I am a data storyteller and grounded researcher, and I help organisations use their data more effectively and help them tell great data stories. If you'd like a hand with data storytelling or strategy, I'd love to chat with you.

Keynote speaker | Author | Facilitator