Upskilling in the Times of Data — What It Means and What It Takes

3/16/2020 Kiran Shankar

Upskilling in the Times of Data — What It Means and What It Takes

There’s no denying the impact of Artificial Intelligence (AI), machine learning, and automation on the very nature of mainstream industries. In just another decade, no sector is likely to remain untouched by digital transformation. 

Yet, even as they shift the curve on operational efficiencies, product innovation, and customer experiences, emerging technologies are making Luddite concerns valid.

Organizations are acknowledging the importance of reskilling employees — especially those with a flair for IT — to cope with the changing nature of processes and work in the 21st century. In companies with low employee turnover, building new skills and future-proofing the workforce is practically an industry imperative.

For those companies boasting low turnover rates, the problem of slow employee development is all too real. At RRD, investment has been made in a training program to upskill employees in one of the most valuable skills in technology — data science.

Reskilling for the future of technology

This program, in partnership with a leading business school, took aim to create a cohort of data analysts who showed promise as potential data scientists. The program, at the very outset, was designed to reskill employees already in the system, and it started with identifying the right talent across disciplines and business units. 

The selection criteria included technical assessments and personal interviews. The process was designed and executed by a designated learning and development team with guidance and input from the Data Science Council. After multiple rounds of review, an initial list of 400 nominees was whittled down to 28 candidates qualified for the program.  

The curriculum for this cohort of 28 participants was delivered in two phases over a period of seven months, first part-time and then full-time (which included classroom and experiential learning). The program required milestone completions, performance in capstone projects, hack-a-thons, academic assessments, achieving minimum cut-off scores in interviews and group presentations. A final score aggregating overall performance was collated, which provided an indicator of the talent spread as well as a comparative outlook with the industry.

Being a technology-led company competing against industry majors in several sectors, this investment in employee growth fulfills an important organizational need for emerging technology skills.

Building an internal pool of talent

Data science has rapidly become a market imperative, as companies are constantly looking for simpler ways to unlock the value of the massive volumes of electronic data generated by Internet of Things (IoT) devices. By combining the established fields of statistics and mathematics with the modern fields of data analysis, machine learning, and information science, data science can offer companies the key to that lock.

The immediate challenge for businesses, however, is that the demand for data scientists far outstrips supply. Reskilling and upskilling programs can help discerning data-driven businesses build an internal pool of talented data scientists and technologists. These programs, while future-proofing companies’ growth, can also be lifelines for employees.

The Future of Jobs Report 2018 by the World Economic Forum shows:

  • 54% of all employees will require significant reskilling and upskilling by 2022
  • 133 million additional new roles may emerge, while 75 million jobs may be lost in the large enterprise segment
  • 38% of businesses expect to extend their workforce to new productivity-enhancing roles [source 1]

Continuous reskilling will ensure that employees do not fear technological advancements and are ready for the future of work.

Hard skills + soft skills = power skills

There’s really no doubt data science training makes employees more competitive and future-ready. However, the training’s insufficient unless coupled with broader soft skills — e.g., communication, adaptability, emotional intelligence, problem identification/resolution, relationship building, and business acumen. 

Such comprehensive soft skills training will enable employees to enhance their tech skills, provide valuable strategic advice, and, above all else, buff their capability to absorb and learn. These are key competitive advantages in the markets where businesses differentiate themselves through personalized services and solutions.

Significantly, while offering its mid-career reskilling program, RRD took into account the trainees’ considerable experience so it could design customized modules to offer the best learning experience. The organizations that are best poised to win at reskilling are the ones that can identify gaps, focus on employee experience, as well as build a wholesome company culture.

Where do we go from here?

The World Economic Forum and Harvard Business Review have both forecasted jobs in the areas of AI, machine learning, and analytics, where data science finds significant application, will be the “hottest” jobs of the future [source 2]. 

This means there will be stricter gatekeeping, and those who wish to pursue, or already have careers in the fields of Big Data and data science, will have to constantly up their game. Upskilling programs like the one implemented by RRD will give ambitious employees a chance to be in the thick of things and design valuable data stories.

Better still, their new skills, new thinking, and new aptitude will give both the organization and employees the tools to succeed in the industry of the future and make a difference in the world.


Kiran Shankar is President of RRD Global Outsourcing

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