Nasdaq CEO Adena Friedman made a powerful comment this week at the World Economic Forum.  The digital transformation of the economy is happening, and it is an unstoppable force.  Companies need to leverage the data they have in a much more strategic way.  Establishing a data COE with clear boundaries on Data Analytics, Data Engineering, and Data Science.  Companies need to continue to find cost-effective talent both locally and globally.  Despite the disruption caused by global events, there remains optimism among international business leaders many areas of the industry will continue to thrive.  At this year’s World Economic Forum, inspirational voices shared their outlook for a brighter future.

The opportunities are far bound, and data can effectively make it successful for you.  If you look at a company like Disney, the last century has been one of the endless reinventions, both in business and artistic terms.  The company has moved its output from projectors to cables to cassettes to bytes.  (Reference:  The Economist – current issue).  Disney will continue to innovate.

For Workforce Planners and Recruiters, the following aspects need to be remembered

• Our view on locations is constantly changing.  Very recently, a Cybersecurity company called TokenEx raised 100 million and created the company in Edmond, Oklahoma, a place not known for being a Cybersecurity hub
• What it takes to learn a new skill is also changing.  More digital and free courses are available for even the most complex tech and business skills

As a result, it will be critical for Workforce Planners and Recruiters to align the activities in the following manner

• Skills Architecture (We wrote extensively last week on this)
• Cost Models by Job Families
  – We should develop a point of view on costs across the global locations.  Say, for example, the cost of skills in the database job family may be cheaper than mobile, which may be cheaper than, say Backend
  – Develop a modeling approach including various parameters.  The following table shows the model we built recently.  We should be able to build something like this across all Job families and locations of interest for you

• Reskilling Engineering
  – Take all of the target roles
  – Judge propensity to reskill into those roles
  – People Assessment (through skill clusters)
  – Identify Learning journeys/learning path assessment

A map of sorts like the one shown below will be helpful.  The target roles in columns and the starting roles as rows will help arrive at optimal paths