We live in an age that is full of data. The amount of technology and data is enormous and it is part of everyone’s lives. However, there exists a huge talent shortage in data competence. Why is that? Why do we need data expertise and what would the world look like without data services? Why should your company be interested in resourcing data talents?
The World without Data Professionals
Introduction:
Hannu Järvi has been working with artificial intelligence for the first time in the mid-90s. He has a clear idea of what is artificial intelligence today and what is advertising speech. Hannu has helped organizations in AI strategy work from small organizations to the largest export companies including the University Central Hospital Management Team and the Executive Committee responsible for the AI strategy work of the TOP10 listed company.
Roope Rajala is a passionate learner who enjoys challenging himself daily. With a background in Adult Education and Work Psychology, he has worked in the Talent Management industry for 5 years. His focus is on finding solutions that create a world-class experience for his clients.
How would you define data today?
Data is everywhere and all the operations of the organizations run around data. Data is all about harnessing the opportunity in machine learning, artificial intelligence etc. Growing needs of data competence have created roles that are needed to realize the opportunities of data, roles like data engineers and data scientists.
Why should an average organization be interested in data?
Data-driven organizations beat their competitors in all aspects of the business. According to McKinsey, 2016: Data-driven organizations are 23 times more likely to acquire customers than their competitors, 6 times more likely to retain those customers, 19 times more likely to be profitable as a result. Thinking that your competitors become data-driven and you don’t, in the future, you don’t have a chance in business if you’re not data-driven.
There is three kind of companies: data companies - companies that will come data-driven - companies that will extinct.
What kind of process has it been that theoretical view has realized to the actual profession and huge industry?
The history of data competence is in machine learning, deep learning and artificial intelligence. Data is a topic that has been studied since the 1950’s so it is not a new thing. There have been a couple of AI winters; investors and the academy itself lost interest in the subject. AI needs a lot of data and data didn’t exist back then in the 1990s. The theory behind deep learning has been the same as it was about 20 years ago.
What would the world look like without data?
Data competence will be there and there will be huge investments in China and in the US. It is all about who will have the competence. The world without data is a world with a handful of data professionals who run the businesses. What roles do we others play?
Data competence will be a key driver of growth and competitiveness and those who will have the data competence will dominate the business and economy of the future.
How do you see data talents resourcing?
There is a worldwide shortage of data skills and all the companies try to compete to get these professionals. Those who already have these skills have a good situation in the job market. Eventually, these professionals find their way to Silicon Valley to the companies that are 20 times bigger than here in Europe. There simply aren’t enough people who are experienced. The solution is to up-skill talents who are fresh out of university.
Skills like Python, machine learning libraries, all the tools of the data pipeline and cloud skills are appreciated. Data competence needs people who understand the logic behind how these things work. There is a growing demand for people who don’t necessarily have to have all these hard skills, but we need more people who can bridge the gap between business and data opportunities.
Companies try to find experienced talents that don’t exist. Organizations know that there is a huge opportunity in data and they expect to get rainmakers. It was the same thing in the late 1990s when dot-com was the new big thing. And after that the mobility.
There is one predictor of success: how interested you are in solving the business problems. A typical consulting case for Hovi is that we come to audit a system or data platform or the project. Typically something has gone wrong there. What is very typical there is that you may spend millions and years and you may have done everything right, but you haven’t done the right things. No one, in the beginning, has really thought about what is the objective in this whole case. And it goes back to the basics: you have to have motivated people who are also motivated to solve business problems. They are not only motivated by the technology and all the cool stuff but also what the company is aiming to achieve in these things.
If we don’t dare to recruit future talents now, we don’t have talents in the future.
