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Reactive vs Proactive Analytics – Shape the Future

Jordan Morrow, Global Head of Data Literacy, Qlik


How many of us feel like every time we work on a data and analytical project we are putting out a fire?

How many of us feel like every time we work on a data and analytical project we are putting out a fire?

With the world in an unprecedented lockdown situation, there is a lot of “reactive” work going into data, analytics, visualizations and the like. Unfortunately, there is also a lot of misinformation and incomplete information going around, potentially negatively impacting that work.

As I sit and think, I feel reactive analytics was a problem in the data and analytical world even before our current situation. Why is this? Why do we sit in a perpetual state of reacting to things, instead of looking ahead and proactively projecting, or better yet, forecasting and setting trends? I feel a lack of data literacy and truly understanding data and analytical strategy play a big part.

In a conversation with a friend on this topic, we determined there is an amazing opportunity, right now, for companies to seize on proactive data and analytics. Data and analytics demand usage in the future, not only from companies, but also from individuals. Imagine a world where, instead of reacting to situations, we have built out proactive models that enable us to “predict” the future. Imagine a data and analytical world where we cannot just put out fires, but use analytics to set the market trends, not react to them. Imagine a world where you, as an individual, use data and analytics to make decisions that can greatly impact your life.

One thing we should all be focusing on is how we can use data and analytics to help us come out of the current situation and be in a position of strength for the future. Each of us, individually and organizationally, has the opportunity to be proactive – not reactive – in analytics. How do we do this? I want to focus on three key pieces:

Improve Data Literacy – How can we hope to be proactive in our analytical work if we are not improving our data literacy skills? When we define data literacy as the ability to read, work with, analyze and communicate with data, we are given a series of things we can be studying and learning. How well can we read data to understand a situation and then predict future outcomes? How comfortable are we in working with data or are there still knowledge gaps keeping us from making use of it? How well can we analyze and ask questions of data? Finally, are we comfortable communicating our results and analysis?

Overall, data literacy is more than just a “nice to have” anymore; it is an imperative, and the current situation is showing us that.

Become Outcome Focused – Far too often, I find that organizations know they want to use data and analytics, but if you ask them what their goal is, they can be very vague. They want it to run their business, to design marketing and so forth. Organizations need to become more specific with their data and analytical vision. We don’t just want to know what happened last month. We need to know what happened last month in comparison to multiple datasets and benchmarks, and then look at how this process can reveal opportunities. In essence, you should become much more focused on what you want your work to do.

Drive Data-Informed Decision Making – Finally, we should utilize this time to learn more about data-informed decision making. We can develop data literacy and be more outcome focused all we want, but if we don’t know how to turn that into a decision, it will just be an unrealized development. We need to learn how to turn our data literacy and outcome focus into a decision.

Overall, ours is a time we will look back and reflect on as potentially the most surreal of our lives. During this time, where we are reacting a lot, we can set the tone for a lot more proactive work. Each of us and our organizations can develop skills in data literacy, become more outcome focused and learn more about data-informed decision making.