Why 14% of the global workforce may need to reskill due to automation

Abboud Ghanem, Regional Vice President - MEA, Alteryx

There is no question that data has become the lifeblood of the modern-day enterprise. From engineering, to manufacturing to retail, organisations globally are all looking to leverage data insights through analytics to deliver breakthroughs. We see this at an individual level as well with the digitally enabled specialist who can command a higher salary than their non-digital counterpart, or the analytically savvy professional who can find more opportunities and higher wages than their non-analytic peers.

As globalisation brings more competition in every industry, it is these types of data-driven competitive advantages that will set companies and countries apart in the future. We see companies across every vertical and industry driving upskilling across their workforce, helping their employees become more data aware and capable of automating business processes by leveraging AI and ML in their work.

But accessibility and understanding of data is still an issue for many businesses struggling to transform and take advantage of the digital economy, collecting data is one thing, having the right culture and skill sets to digest, understand, and turn it into a breakthrough is another.

Skills gaps are affecting industries around the world, and the Middle East and Africa is no different. An analytic divide is separating individuals and companies who have analytic skills to leverage the information that is available and automate processes from those who do not have those skills.

With unprecedented automation set to alter the business landscape like never before, this gap could continue to grow. In their latest research on automation, titled, Jobs lost, jobs gained: Workforce transitions in a time of automation, the McKinsey Global Institute predicts as many as 375 Million workers or roughly 14% of the global workforce, may need to switch occupational categories as digitisation, automation, and advances in artificial intelligence disrupt the world of work.

The kinds of skills companies require will shift, with profound implications for the career paths individuals will need to pursue. While every journey is different, there are common patterns in how this upskilling and data culture occurs.

Employees frequently start by learning a new platform or self-service technology that enables to automate analytic processes. They then apply the technology to what they were already doing. They assess if they can wrangle data faster and easier and analyse it or find patterns more readily. Once they are comfortable on this step, they move along the analytics journey towards automating existing processes. At this first step of the transformation the savings are modest, measured in time savings that can be put into higher value work.

A key component of upskilling the workforce is around the velocity at which you can accomplish it and the best way for people to learn is when they collaborate. It goes back to the well-known saying; power is not in what you know; it is what you share. As knowledge workers of any discipline continue to upskill and easily learn new techniques through self-service solutions that include an option for employees to self-onboard, they can move beyond human decision making and use predictive analytics to quickly harness the hidden power within thousands of disparate data sources and automate processes to uncover actionable insights.

The next step is typically adding analytics to the process, with forecasting, anomaly detection or more basic analysis to allow optimisation of a business outcome. In this step, processes begin to be re-engineered and changed. Let us look at an example that we all can picture during this current Covid-19 situation: the shipping of goods.

A major manufacturer has thousands of products that they ship. Each product has hundreds of parts that have to be managed to ensure no disruption in the production cadence. The standard shipping times for all parts have been entered into their fulfilment system and based both on how fast the plant is consuming parts and, on the sales forecast, orders are made to ensure the supply parts show up before running out. Everything is working smoothly until suddenly the supply chain is disrupted and shipping times start to change dramatically.

How does the manufacturer re-enter all the new shipping times into the system to ensure the re-ordering is happening at the right time? Certainly, a team of people could manually go work on this, and depending on the number of parts, eventually they would have the system updated. A day later, though, the shipping times could begin to change again, and this would cause a never-ending cycle to update the system. Alternately, a simple analytic model could be built that monitors the shipping times in real-time and automatically updates the system with the most current estimates.

Analytic Process Automation, APA, replaces time-consuming, repetitive manual processes to enable every employee to focus on getting much deeper insights from their existing data quicker than ever before revolutionising the speed in which they can make business critical decisions. But for automation to be successful, self-service human-lead data science is required.

Over the coming years, it will become apparent that to achieve success in a competitive market, companies have an immediate need to shift focus and embrace a model that provides insights faster and speed decision making. One of the most important aspects this journey is the upskilling of people. Empowering anyone in the business to ask hard questions about the business and get answers quickly, without needing to rely on highly trained specialist professionals.

Key Takeaways:

  • Companies across every vertical and industry are driving upskilling across their workforce.
  • Skills gaps are affecting industries around the world, and the Middle East and Africa is no different.
  • Analytic Process Automation replaces time-consuming, repetitive manual processes.
  • Organisations are looking to leverage data insights through analytics to deliver breakthroughs.
  • Companies have an immediate need to embrace a model that speeds up decision making.

Abboud Ghanem of Alteryx writes that upskilling of people is the most important aspect in achieving success in a competitive market.