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Tagging the JDs across a set of criteria to model work from home index is emerging as a critical priority. Mostly the factors used in our models are People, Systems, and Compliance. This will help you tag the JDs. We are still not fully automated but are working on some of the job roles. An example tag across these components across a few job families is given in this table. The goal is to track your JDs and produce a table like this based on text mining.
The stay-at-home orders brought in by a global pandemic has made it inevitable for the organizations to settle for remote working and virtual business all around. Surprisingly enough, popular opinion and market research confirm the greater effectiveness of remote working, indicated by increased efficiency and productivity across industries.
With the world walking through the labyrinth of unforeseen transformations, the newly adopted practices of remote working are more likely to become the new normal. Owing to the growing hygiene concerns, cost-cutting concerns, and the impending need for social distancing, major organizations prefer remote working as a more permanent or long-term option for their employees.
Drawing from the recent news in the market, major organizations have broken their silence first and spoken about their remote working practices:
- Twitter and Square to roll out ‘Work from Home Forever’ options to its employees
- Majority of Google, Facebook, and Zillow’s workforce to work remotely till the end of 2020
- Mondelez, Barclays, and Morgan Stanley plans on working with minimal or no footprint
- Microsoft, Amazon, and Slack to function remotely till the end of October 2020
With the obvious prospect of longer-term remote working becoming the new norm, talent acquisition heads are faced with a set of novel challenges. The need to identify talents who are not only well-skilled and qualified for the job, but also those who are the perfect fit to perform even during the transition phase is now the task at hand for recruiters.
These challenges have widened the scope for research focused on the areas of productivity and professionalism. National research institutes and academic centres such as the Indian School of Business are conducting surveys and research studies to establish ‘Work for Home Index’ at occupational level, based on the calculated ‘Human Proximity Index’ of occupations.
Draup, typically staying ahead of the curve is working on a new model to calculate the Work from Home Index at the job role level, by the method of text mining on job descriptions. Draup’s WFH-I model extracts data from job descriptions around the major components of the job role such as People (soft skills), Systems (infrastructure), and Compliance (protocols).
The skill requirement of the job role under each of these components is analysed and represented independently, aiding the recruits in identifying the top influencing factor. A cumulative score of people, systems and compliance factors is also available on the table. This is the overall Work from Home Index of the job role (higher the WFH-I, more ideal is the job role for remote working).
Being at the front of adopting to changes at the earliest and aiding their clients to bounce back with renewed strength, Draup’s aim is to make this WFH-I model automated. This will make it a key factor in talent acquisition practices in the near future.
