The Art and Science of Data

I have a confession to make. I love data. I mean, I really love data. When I can harness data and information to unlock greater business value, that’s the mark of a very good day. Early in my career, I had worked for weeks on a strategic plan. It had all the right mix of growth levers, financial projections, market analysis, and more. When reviewing it with my manager, he asked me a question. “What is one thing you know is always true about any plan you create?” Being entirely too tired at this point for a riddle, I asked him to tell me. His answer was something I would never forget. He said “It’s wrong. All plans are wrong because no one can predict the future with 100% accuracy. So the question is… how wrong is your plan? How will you know if it is veering toward ‘wrong’? What are the signposts that you will monitor so you can be agile enough to adjust and deliver on the promise of the plan, even if that delivery varies from the original proposal?” Lesson learned – a plan is incomplete without the metrics and data being identified that you will monitor to drive for success.

Why is data so appealing and exciting? By definition, it’s historical— a record of the past that may, or may not, help figure out the present or future. How you look at and analyze data really matters as it can shape what you will or won’t find. And as a marketing leader, this evaluation process is critical to tapping the power of data itself.

One of the most amazing things about data is that there’s both science and art to it. The science part is the accumulating and analyzing of data to make the most informed decisions possible. Typically, people look at larger trends in the data. What stands out as significant? Where are the clusters of commonalities? What does the trend line look like?

The art part is the human lens that follows the science. What did you expect to see but didn’t? What did you not expect to see but did? Did the science unearth any unintentional bias that you can now see and address? When you look at various trends together, what interesting correlations or contradictions stand out?

While the science of data is rather straightforward, the art of data is more subjective. Interpreting data involves a degree of humility over the limitations of the data itself. Unfortunately, over time, I’ve seen fewer and fewer people taking the time to practice the art of data interpretation. This can translate into a lot of missed opportunities. But by channeling your “inner artist,” business leaders can help unlock even more value from their business and their people.

The big question now is whether AI can handle the art as well as the science of good analysis? The answer is maybe. AI can help bridge gaps and fill in likely options beyond the initial data set, if the data model is trained correctly. With the help of machine learning algorithms, AI systems can automatically analyze data and uncover hidden trends, patterns, and insights that can be used by businesses to make better-informed decisions. For example, Twitter uses AI to evaluate tweets in real time and score them using various metrics to display tweets that have the potential to drive the most engagement. And countless banking and financial institutions are using AI and augmented analytics to generate personalized portfolio analysis reports.

It will be interesting to watch how AI continues to develop and intersect with continued human oversight. According to Gartner, by the end of 2024, 75% of enterprises will operationalize AI, driving a 5x increase in streaming data and analytics infrastructures. Over time, it is very likely that AI will be able to handle both the art and science of data. But the key will be AI and humans working collaboratively to ensure proper oversight.

With the pace of business moving faster than ever, knowing how to orchestrate good analysis is more important than ever. For leaders, this means making sure your data scientists (and artists) are armed with the right tools and skills and have ample time to do their work. It also means learning the language of analytics itself so that you can truly understand the plethora of opportunities that data and proper interpretation can unearth.