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Simplicity could be the key to reducing the skills gap

With billions of IoT-connected devices, we are producing more data than ever before. But how do we use all this information? The answer is simplicity.

Simplicity: the key to reducing the skills gap

The growing skills gap is a concern that rears its head almost daily in our board meetings. Across the world, we’re being told that our staff no longer meet the demands of the data driven economy, due to gaps in digital ability, skills, and attitudes to new technology.

This is hard to believe, surely? I would argue that our lack of technical prowess in certain fields is not a skills debate, rather, one about tools. The reality is, many of the tools companies are using today are overly complicated. If you require a degree and 30 hours of training a week to be able to open and use them, what’s the point? And, of course, people won’t be the experts we need and want them to be.

The skills we’re lacking

We are in the midst of a data revolution. According to a report by IBM, 90% of the world’s data was created in 2015–16, averaging 2.5 quintillion bytes of data each day. Not only that, but in 2017 we were expected to create even more data in a single year. Organisations gather data from, and share knowledge with, their suppliers, consumers, partners, and competitors among others.

New data is constantly being created, leading to a growing desire among companies to be ‘data-driven’. As a result of this, proficiency in analytics and data visualisation are quickly becoming some of the most desirable skills for organisations.

Gartner predicts that Australian IT spending will reach A$84.4 billion in 2018, with a change in focus from big data to algorithms, machine learning and artificial intelligence. When it comes to bridging the skills gap, we don’t all need to be data scientists, but we do need to be data literate.

At the same time, data literacy has become vital when it comes to building successful companies and cultures, but where do we start on the journey to data literacy?

“A very particular set of skills…”

To start with, it is important to ensure we have the necessary skills needed to make decisions using the data in front of us. This includes having the ability to not only read the data, but to be able to interpret, converse with, challenge, understand, and analyse the data.

These skills are not something we need to be born with; rather, they are things we can develop, both as individuals and as organisations. As management, we have the ability to provide training and development programs to our employees in order to assist with their development of data analysis. We need to make it a priority to look into providing these opportunities to employees to lessen the skills gap, and ensure our companies move forward into the future with data analysis.

Curiosity killed the cat… but not the data scientist

It’s in our nature to be curious; this is something we learn as children. It’s only natural that we should want to find answers, and so we, as managers, need to drive a culture of curiosity in our organisation. We need to build data-driven organisations, and make decisions based on facts and what is happening in the business itself, as well as in the industries in which we work. To build a successful culture, we cannot be siloed. Asking ‘why’ of our data allows us to break down these walls, and make smarter business decisions driven by data.

Data-driven toolkit

Breaking down figurative walls is not unlike breaking down a literal wall: we need to have the right tools to do it. To forge a successful, data-driven, data-curious workforce, we need to employ tools that empower users. They need to be simple and intuitive – it is through empowering our employees with easy-to-use tools that we can make data analysis second nature to our workers.

The future of data

As technology innovators, we need to be creating technology for the user, making sure that the tools we provide are not only innovative, but simple to use. To help employees be more comfortable with understanding data and how to use it in their daily life, organisations can look to implementing ‘simplified tools’ to assist in the analysis, while also offering training for employees that are less comfortable with the technology. This can be empowering for employees; by focusing on the end user and providing the employee with the skills they need, it follows that the skills gap will lessen as users become more comfortable with the tools and skills they need to be data literate.

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