From a labor market perspective, we are entering an era where unique roles and skill combinations will become more of a reality. To generate fresh job opportunities for our employees, it is crucial for workforce planning to grasp the intricacies and adopt a highly strategic mindset. Last week, NASA launched a first-ever public meeting of the working group about the study of the Unidentified Anomalous Phenomenon (a new name for UFOs), which was unheard of before. Astrophysicist David Spergel, who chairs this effort, summarized it beautifully. “Today’s existing data and eyewitness reports on UAP are insufficient to yield conclusive evidence because of lack of quality control and poor data curation.” As a result, the working committee is proposing big data standards to report. So it is not an alien problem but a data problem!
We are entering a zone where creating high-quality and relevant data and having a higher order of skills to use it will become important for enterprises. Even though ChatGPT showed the world that any user with any skill could use the platform, Enterprises may have to think about this little differently.
Here are some recent Workforce Planning Trends that we presented at an Enterprise event:
Unique Roles and Skill Combinations
Let us take the example of Stitch Fix – an online stylist startup. Tatsiana Maskalevich is the director of data science but she also styles clients. Stitch Fix teaches every employee about styling. (regardless of a data scientist, software developer, accountant, HR, etc.). When you know the business well, the algorithms can be better used, and the limitations can be better understood. (This case study is adapted from the book Working with AI by Thomas H Davenport)
More Skills for Humans – Not Less
From a skills development perspective, this creates a two-way opportunity for companies. Take skills like Data Science across to nontechnical resources and business skills to Technology and ML resources. As evident, the outcome of ChatGPT does not diminish the need for skill development; rather, it emphasizes the importance of enhancing human skills through upskilling.
More data experiments on Labor
In this context, another work done by Abhijit Banerjee comes to my attention. Abhijit Banerjee is an Indian economist awarded the Nobel Prize in Economic Sciences in 2019, along with Esther Duflo and Michael Kremer, for their experimental approach to alleviating global poverty. Banerjee is known for his work in development economics, particularly his research on poverty, education, and healthcare in developing countries. He has contributed significantly to understanding the impact of policies and interventions on the lives of people experiencing poverty, using rigorous field experiments and data analysis. In one experiment, Banerjee used gossip as a data injection layer to enhance immunization in India. By providing immunization stats to key central leaders in a village-based rural network, Banerjee determined that the health compliance stats improved.
Today, we can conduct an unbelievable number of experiments in studying promotion and resignation in employee networks (as an example) and narrow down the impact of the dissemination of information in such instances. Workforce Planning in conjunction with People Analytics can do magic that was not feasible even a few years ago.
We are over-indexed on Jobs and Under indexed on Skills with Context.
Indexing skills does not mean tagging skills for each employee/JD asset. It means truly understanding the context through the following layers.
- Business Intentions
- Digital Intention
- Digital Products
- Core Skills
- Soft Skills/Power skills
Together these elements give the Skills Context. Here is an example of such Skills With Context Mapping
Diverse Data Sets:
We can harness various data assets and integrate innovative concepts like the Degree of Urbanization (Degurba) into our strategic workforce planning. This capability opens up exciting possibilities for optimizing our approach and maximizing the potential of our workforce. Several platforms are evolving that need to be monitored. I came across Terrastories, an open-source platform to map and share indigenous and other local communities.
Historically, Workforce planning has not been able to map indigenous and local communities, and platforms like Terrastories can bring in deeper location intelligence, especially in Sustainable Supply Chains. The data is still evolving on this platform, but the possibilities in the areas of the supply chain are immense. Here is an example of The Brokolonko range located in Suriname. It is a part of the Guiana Highlands, a mountain range that runs through Guyana, Suriname, and French Guiana. The Brokolonko range is located in the northeast of Suriname, in the Sipaliwini District. The community here has rich fishing and mining skills, and the stories reflect the same