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Maximizing Workday Implementation : Workforce Optimization Post-COVID19
Maximizing Workday Implementation : Workforce Optimization Post-COVID19
Thomas C

Content Developer

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Maximizing Workday Implementation : Workforce Optimization Post-COVID19

04 Aug 2020

https://www.youtube.com/watch?v=8IEpWc3pHAM&feature=youtu.be

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The impact of COVID-19 is slowly unravelling across industries. Unemployment trends across major occupations are increasing all over the US. As of April 2020, the US had an overall unemployment rate of 14.7%, an over 300% increase from the April 19 levels of 3.6%.  

Small and big enterprises alike are reeling under the effects of coronavirus. Without a doubt, the HCM value chain within organizations have been disrupted. 

On the bright side, the COVIDera is spurring an adoption of digital cloud technologies and forcing workforce planners to have a relook at their talent management strategies.  

In this context, HCM solutions like Workday, play a crucial role in establishing a robust, post-COVID talent management strategy. 

Through an extensive webinar, Vijay Swaminathan, CEO & Co-Founder of Draupdemonstrated for a select audience of top HR leaders how enterprises can leverage maximum value out of their Workday implementation strategy.

Vijay presents three areas for Workday implementation to achieve workforce optimization post-COVID. These can also be achieved easily using the proprietary tools bundled with Draup for Talent. 

  • Mapping Job Roles to Job Responsibilities: Break job roles down to their skills levels and build a skills library. Leverage this skills library to correctly identify and map job roles with their responsibilities. Stakeholders can also analyze job descriptions on public portals and internal JDs using Draup’s AI model to create optimum job descriptions for desired roles. 

  • Digital and neighbourhood skills scan for identified employees: Now that you have broken down job roles to a skills level, identify adjacent skills that will facilitate a job role transition in the shortest time.  For example, by breaking down a data analysts’ role to a skills level, you identify that they have proficiency in R & SAS. Based on your internal talent needs, you can see that skilling them in Python will help meet your immediate talent needs. This strategy also helps the employee in their career growth.  

  • A career maps model and aspiration simulationHaving a skills-level view of talent distribution helps you to supply optimal talent for high demand, emerging and disrupted roles. Hiring for these roles will result in cost overruns and does not always guarantee the right talent. Using AI tools to chart out employee aspirations will help HCMs to suggest an ideal career map. 

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