Closing the Data Talents Gap – Start Spotting Opportunities Internally

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The demand for data science talents has exploded. For four consecutive years, LinkedIn listed Statistical Analysis and Data Mining in the top three of skills in demand. The best jobs include positions like data scientists, engineers and analysts. Yet, according to a 2015 MIT Sloan Management Review Survey, 40% of the companies are struggling to find and retain data analytics talent. This alarming outcome is fed by a recent study of the European Commission, in which they indicated we will need another 769.000 skilled data professionals in Europe until 2020 to fill the gap. That this is still a hot topic in 2017 became evident during our panel session at the Big Data and Analytics Innovation Summit in November where the Data Talents Gap was one of the topics of recurring concern.

Data will become (or, to be honest, should already be) an integral part of the organization. Jobs from all levels will change. Where a call center agent should understand the output of a churn prediction model and use it to prevent customers from leaving and a financial analyst at a bank should understand why the algorithm rates some people as high credit risk and should know how to take action accordingly. Businesses demand different skills than those possessed by the existing workplace, such as tech skills that evolve incredibly fast. In addition, requirements that qualify the right candidate are getting stricter as the roles are not just focused on analyzing data, but on the creativity to identify and enable data opportunities that contribute to the company’s efficiency, predictability and effectiveness. Companies are on the lookout for T-Shaped individuals that demonstrate a perfect balance between hard (analytical, technical) and soft and general (problem-solving, communication, creativity and teamwork) skills. A holistic skill set that is scarce, and so fierce competition is unavoidable. We all want data talent. Talent that is hard to find. What can your company do to close the data talents gap?

The Profile of a Modern Data Scientist

Campus Recruiting
There are a number of universities in the Netherlands offering programs with strong quantitative background, such as the University of Amsterdam, Erasmus University, University of Utrecht and TU Delft. In addition, there is a rising number of universities offering analytics and data science programs, or related ones like Artificial Intelligence, Operations Research and Econometrics programs. To gain awareness among fresh graduates it is worthwhile to keep strong ties with Universities and student associations. Develop (preferably in close collaboration with universities) internships and student projects, both as a recruiting tool and as a way to prepare students for the business world. Students can be a great asset for research and a valuable source for innovation.

Foreseeing exponential growth, the flow of fresh graduates will not nearly be sufficient to close the entire data talents gap. In addition, it can be quite challenging for legacy firms to recruit talented graduates. So we should be searching in different areas to close the data talents gap in such a way that it is sustainable and we keep control of the continuity and growth of our businesses. In that respect, have you already started spotting opportunities internally? You would be surprised what is already there.

Identify talents and start training them
Looking inward for staff who have the potential and drive to learn new skills could be very beneficial. Giving the opportunity to a pool of people to develop themselves will have a positive effect on employee satisfaction. They will become more adaptive to change and, consequently, will stimulate their co-workers to grow along as well. In addition, training opportunities also have a positive effect on employee loyalty resulting in the safeguarding of knowledge within your organization.

In identifying talent, don’t limit your search by focusing on existing skills but rather focus on competencies. While skills in Python are useful, teaching competencies like teamwork, communication, critical thinking, and especially, business understanding and domain knowledge may be more difficult. Select the competencies required and develop a profile to identify emerging and existing talent. In your search, look also, and particularly, for people who once studied in a technical direction, or even Excel wizards, statisticians and data-savvy programmers that have the aptitude to make a switch.

Develop talent by organizing in-house analytics education, offering them a set of relevant online free courses, setting up apprentice-mentor programs and have them work on real business problems (in a controlled manner) to give them the opportunity to gain practical experience.

Analytics Courses
Creating in-house analytics education can be time-consuming, relies heavily on expertise which cannot be used in money-making projects and thus may not be the fastest and cost-effective strategy. As speed is critical in the ever-changing field of data science, you could consider customized analytics courses hosted by experienced external providers. Such external providers are more agile in updating analytics course material and are able to accelerate and deepen the skills of your talent pool. For most people it is difficult to apply the learned skills in business practice, for this reason it is key to find a partner that is able to provide an optimal balance between theory and practice.

PostNL builds up their Team’s Data Science and Machine Learning Expertise

Centers of Excellence for Analytics
To make analytics easily accessible and to increase adoption of analytics by your workforce you can set-up a Center of Excellence. The term Center of Excellence has been used by Gartner (Morello, 2002) to describe a cross-functional team responsible for a specific discipline across an organization (e.g. knowledge management), with the ultimate goal to reduce time to value and to sustain in-house knowledge. Centers of Excellence focused on Analytics generate and refresh knowledge, competencies, and skills on analytics to facilitate and promote the use of it. Focus could be on subjects like statistical programming, techniques and business value creation to support decision-making. Knowledge can be shared via Master Classes, Lunch & Learn sessions, Workshops, Community Sessions, Hackathons or by doing small Proof of Concepts (PoCs).

ORTEC’s Knowledge Sharing Events contribute to Innovation and Fun in the Workplace

The run-up to become data driven
Becoming a data-driven enterprise takes time, especially when it involves transforming your workforce. In the journey towards a data driven company it could particularly be beneficial to collaborate with experienced consultants to cope with complex analytics challenges and to take the first leap into embedding data into your organization. To secure sustainable growth and to stimulate knowledge sharing on the job you should go beyond solely relying on consultants for all data projects. Therefore, consider combining consultancy projects with complementary training hosted by the consultants to safeguard their broad know-how and the domain knowledge built up in the past period.

The best approach to closing the data talents gap is, without a doubt, a combination of external outreach and internal development. But what strategy you choose depends on the current analytical capability of your organization. Take a step back and assess your demand (what are your long term analytics needs) and your supply (what is the level of knowledge and skills of your current staff). Compare and contrast the two helps you to determine the gap. Subsequently, you are ready to assess the pros and cons of outsourcing, hiring and further development of your current staff. It will provide valuable insights in where you need to be focusing at during what stage of your journey. Although closing the data talents gap isn’t an easy fix, there are many opportunities in making steps towards creating a better-equipped and sustainable workforce.

About The Analytics Academy
The Analytics Academy (part of ORTEC Data Science) supports companies towards the data-driven enterprise and aims to decrease the shortage of Data Science talent in the Netherlands. They help you to think strategically about your analytics capability with support of the Analytics Talent Scan or assist you in discovering what your company or team needs to become more data-driven through a 2-day introduction course. In addition, The Analytics Academy offers tailor made in-house education for all functions and levels within the organization to refresh the minds, (re)train the skills and restart the careers of the Data Scientists of the future. As the Analytics Academy is a cooperation between University of Amsterdam, ORTEC Data Science and Amsterdam Data Science, they can offer the best of both theory and practice. If you believe that you lack data science skills or are worried your company lags behind your competitors, feel free to contact us via the website or get in direct contact with Robert Monné via robert.monne@theanalyticsacademy.com or +31(0)6 15 29 13 11.

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