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Developing forever skills in the era of information overload

Kevin Hanegan, Chief Learning Officer, Qlik & Chair, Data Literacy Project Advisory Board


When you are being bombarded with such high volumes of information, it becomes hard to process it all, let alone understand its relevance and use it to make intelligent decisions.

A recent article in the New York Times raises the notion that experts are questioning the importance and value of measuring COVID caseloads, with the rise in use of rapid tests at home. After all, most of the results of at-home tests are not reported. This leads to inaccurate data around the infection rate and how the virus is spreading, which provides a critical barometer to inform decisions pertaining to the pandemic response.

Unfortunately, the outcome of this change is often confusion, as officials scramble to develop new approaches without a crucial metric, which leads to conflicting advice to the population. That’s not to say that we shouldn’t reassess and update processes as we gain more data about a situation – it’s a critical component of Data Literacy. But if there is too much information, or if it’s communicated in a confusing way, people can end up not trusting the data or the recommendations that come from it.

This conundrum can be applied in a business context too. Most organizations recognize the trend towards using data in the decision-making process, but few understand how to use it to tell a meaningful story and how this can drive the desired action. When employees are being bombarded with such high volumes with information, it becomes hard to process it all, let alone understand its relevance and use it to make intelligent decisions.

As technology becomes more abundant, this information overload poses a significant challenge. While data has huge value, over reliance on it can lead to less of a focus on developing non-technical skills like curiosity, creativity and collaboration. Perhaps counterintuitively then, Data Literacy is not all about data.

I see the important baseline skills to help us make sense of mass volumes of information and make truly informed decisions falling under three pillars of ‘forever skills’ – understanding complex situations, teamwork and collaboration, and adapting to change. These attributes will define our skills development in 2022 and what employers are looking for, while helping individuals become more data literate and make better data-informed decisions.

Understanding complex situations

While advances in automation and AI are making it possible for an increasing number of human tasks to be automated, machines still lack emotional and social skills as well as higher cognitive skills such as problem solving, critical thinking, creativity, and systematic decision-making. Therefore, understanding how to mitigate bias and challenge assumptions, while maintaining creative curiosity, will ensure that we can dig deeper into the story that data is telling us.

Teamwork and communication

Individuals can possess all the technical skills needed to leverage data, but if they don’t have the ability to understand what the stakeholders really want, they will not produce value. This is where ‘forever skills’ such as active listening, inclusion and storytelling with data come into play.

Adapting to change

The world continues to rapidly evolve and technology is constantly changing the way we work.  What is required to stay current is not just learning the latest technology, but the ability to unlearn outdated ones, and to be resilient and adapt to the changes. This year, ‘forever skills’ like unlearning, intellectual humility and exponential thinking will become more valuable as we evolve our skillsets to meet the demands of a changing world.

Although we are sometimes presented with too much information, becoming data literate enables us to distinguish between signals and noise, as well as anticipate and evaluate incoming and current realities. As we’ve discussed, this isn’t necessarily just about nurturing technical skills – developing the forever skills outlined here can be just as valuable when data is so ubiquitous.