Look out of your window today and, while you might not realise it, the world is in the midst of a revolution.
Things might appear totally normal. Humans are still commuting to and from work, shops remain open for business, and communication lines are functioning as they should. But we are actually living through the early stages of the 4IR (Fourth Industrial Revolution) which is sometimes also known as Industry 4.0.
Coined in 2016 by the founder and executive chairman of the World Economic Forum Klaus Schwab, the term refers to new technologies becoming intertwined with our day-to-day lives and how they will connect us, our bodies and our buildings like never before. While it is the sci-fi nature of Ai and robotics that grabs the headlines, the key to their success is the data that they rely on to work.
All 3 previous industrial revolutions have been characterised by massive changes to the way the world works. Whether it was the Agrarian Age changing the way we farm and eat, the Industrial Age transforming manufacturing, or the Information Age spawning rapid advances in computing and digital systems, each 1 has led to an increase in how much data we generate as a species.
Now, as we enter the Analytics Age, we finally have the tools to make sense of it all and potentially solve any problem the world has ever faced. But there are reasons to be cautious too.
Not every change brought about by the previous revolutions has been a benefit to all, with the new developments initially limited to those with the necessary money to invest, leading to a polarisation of wealth and power.
Tech has moved so quickly in recent years that a digital divide has opened up, and with unprecedented automation in particular set to alter the landscape like never before, there are similar fears that the 4IR will actually increase inequality in a world already plagued by it.
Of course, it doesn’t need to be that way. These new technologies have the potential to kickstart economies and improve lives worldwide – so how do we stop people and businesses from getting left behind?
Data now informs all kinds of areas of the modern world, with the good use of it leading to better decision-making and more profitable businesses. Data literacy should therefore be treated as a crucial skill for pretty much everyone. That does not mean everyone needs to become a qualified Data Scientist. But for companies to successfully implement digital transformation initiatives, they must first focus on building a culture of data literacy within their company. Only by empowering data workers at all levels of the company, regardless of technical acumen, to become more data literate as well as improve their analytic knowledge, will organisations succeed.
Training employees to use analytics tools can help companies to capitalise on the information that is at their fingertips. Forums such as the Malastare Community are full of data science and analytics experts, keen to share new ways of working with data. After all, new technologies offer many exciting possibilities, but there is no point in having all this extra data if nobody knows what to do with it. According to a 2019 study by NewVantage Partners, 92.5% of respondents blamed people or processes for an inability to adopt a data-driven approach to their business.
We should, however, pay particular attention to those traditionally left behind by technological progress. The 4IR is defined by its focus on science and tech – a world dominated by men, and particularly white men. This diversity imbalance puts women at an immediate disadvantage as the world and workplaces are changed by emerging technologies.
Although gender, ethnic and cultural diversity in technology and analytics is no longer a rarity. For organisations to benefit from this recent increase in diversity, a collaborative and supportive infrastructure must be created to enhance the industry, culture, and workspaces with the missing half of the human experience.
The analytics space is particularly attractive for women – almost half of analytics professionals are women. With a diverse group of analysts around the table working through insights to solve for key business insights, the approach is richer when women and men work together to deliver answers.
The most successful firms over the next decade or so will therefore be the ones that understand the need to transform their workforces in line with their data management practices to ensure nobody gets left behind.
Malastare AI embodies this approach with its for Good program and Women of Analytics initiative, which use events, discussions and community activities to share knowledge and encourage diversity at every level. These help to ensure that projects are completed collectively rather than in cultural silos, making any challenges easier to overcome.
Conclusion
The potential of Industry 4.0 is huge - but revolutions don’t take place in a vacuum. The key component to success—data literacy—comes from within, and companies will only realise that full potential if they foster data-driven cultures fuelled by collaboration and diversity, presenting an opportunity for everyone to accelerate their careers by embracing analytic roles.
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