Data scientists are often thought of as the lifeblood of organisations’ Internet of Things (IoT) projects
These individuals hold the key to the heart of every company’s ability to make more informed decisions with their data. With the skills to unlock the true value of data to drive organisations forward, business leaders are becoming increasingly reliant on the data scientist for success. Think of it like this: In the same way a car may be useless without any fuel to move it forward, a business can’t truly tap into the potential of its IoT if it doesn’t have anyone to drive it forward.
It’s clear then, that one of the reasons many businesses are choosing to shy away from IoT projects is a lack of skills and experience in the field. So, does this mean that we will become more dependent on the data scientist? Or should we be turning to other measures to ensure our businesses are well and truly equipped with the relevant skill sets to help them make use of IoT and keep pace with the ever-increasing competition?
The shortage of data scientists
According to Gartner, by 2020, more than half of major new business processes and systems will incorporate some element of IoT. As more and more businesses begin to implement IoT projects, they will need to be equipped with the right skill sets to implement these projects successfully. With the current shortage of data scientists, artificial intelligence (AI) is one way that we can begin to automate a more mature and integrated IoT. This means that we need to be offering higher-level training in technologies such as AI and IoT to help bridge the gap between the shortage of skills and the need for these skills. The benefit of AI is that it will help companies to scale their projects, while allowing staff to focus their time on jobs that technology can’t do. Meanwhile AI can focus on the mundane, repetitive tasks that employees have less time to do. AI then becomes an enabler for IoT projects.
In fact, reports continue to tell us that insufficient staffing and a lack of expertise are the two things hampering the IoT market. Research from Immersat Research Programme found that 33 per cent of organisations would benefit from additional skills, whilst 47 per cent believe that they lack the right skills entirely. According to the report, the three main skills that organisations are lacking in are data security, data science and technical support. The solution though, isn’t to simply hire more data scientists. We need to understand the importance of other technologies such as AI and machine learning in enabling these IoT projects so that we can ensure we are training our future workforce in the right skill sets.
The sharing economy
The current view of businesses is that only one person (the data scientist) is able to solve any IoT problems. This is the wrong attitude to have.
There seems to be an obvious and somewhat necessary solution here to ensure that employees within an organisation are able to understand their IoT data and apply it to their own sector of expertise for maximum business benefit.
One of the ways to resolve this skills shortage is to think about training Millennials to drive IoT projects forward in the future. Millennials are our future workforce and, given they are used to being constantly connected, they are perfectly placed to drive further connectivity. You’ll hear this described as entering the sharing economy. Therefore, as we enter this more circular economy, we need to equip employees with the necessary skills in AI, ML and deep learning (DL). By opening up the opportunity for individuals to specialise in these areas, businesses will be able to apply analytics to streaming data for deeper insights. This will enable more predictive decisions to be made and falls into sync with what a data scientist would be doing day by day.
Therefore, we need to focus on implementing more training in tools that can help to automate and enhance roles, enabling employees to focus on the work that an application cannot do:
- Implement more training – To bridge the current skills gap, we need to focus on offering more training courses in technologies that can act as an enabler, including AI, ML and DL. By allowing more employees to specialise in these skills, businesses will be able to benefit from greater analytics for more predictive decision-making. With more specific and targeted training courses, there will be greater opportunity to upskill the workforce.
- STEM isn’t the only answer – There’s been a lot of emphasis on STEM recently. But, this 20th century thinking is not the only way to do it. We need to be focused on engineering new businesses and bringing new approaches to the market. A data scientist can be important in designing future business models. So, let’s offer more training in design thinking. It’s not just about the scientific skills a data scientist pursues. The skills to enable a company’s strategy are equally as important.
- There is no one, single required skill – As the workforce of the future prepare to work in a more connected workplace, there is no single required skill. Ultimately, IoT and digital transformation are linked. Therefore, whilst a data scientist used to be the secret ingredient to create a successful IoT strategy, it’s not the only ingredient needed anymore. The data scientist is replaceable if we focus on building a workforce that possess skills in AI, DL and ML. If we can keep pace with these new technologies, we can ensure we are equipped with the necessary skills to automate our projects more widely.
Ultimately, the IoT industry is progressing rapidly and no one is sure as to where it will go next. However, if one thing is for sure, it’s that we need more than just a data scientist to implement these projects successfully. We need to build a workforce that is equipped in AI, DL, ML, data analytics and predictive decision making to alleviate the current pressure. The time to get ready is now. Why wait?
About the Author
Anthony Sayers is an IoT Evangelist at Software AG. He is a senior technology expert and strategist focused on the Internet of Things (IoT) that drive business outcomes.