This week we worked on various aspects of making Talent Intelligence impactful to an Enterprise. At Draup, we firmly believe all the complex analyses we conduct should drive more reskilling and more talented and qualified individuals to your enterprise.   Sometimes, we forget this grounding view.  Yes, the great presentations and dashboards are great, but we will always strive for stories where we make an impact/assisting in making the impact.  We have a great case study this week to share, and hopefully, you will find this useful

As we all know, 2021 has started with a significant emphasis on hiring across locations and industries.  The war for talent has become real.  In markets where the technology product players and VCs operate, we find the Hiring Difficulty getting higher for all Digital Talent. (Software, Core Engineering functions like Electrical Engineering and Data Engineering and many other similar categories)  Corporate functions talent is also at a premium with heavy premium associated with Finance, HR, Digital Marketing, Legal and Compliance, Sustainability roles.  This is not very surprising given what is happening

• Global VC funds invested is well over 300 Billion in 2020 (Despite COVID-19, this is record growth)
• Private Equity Companies raised well over 530 Billion in 2020
• Enterprises increased their R&D funds by well over 1.5 Trillion dollars (Approximate Estimate- estimates in this category often vary a bit depending upon what is called R&D)

All this means the war for talent is only going to get tough.  While our analysis can bring in all the data you need, we want to emphasize in this email the Agile process and Lean Management principles that will be useful for Recruitment.  Along with this, Enterprises also need to realize that Recruiting is also a bit abstract, and qualitative aspects matter more.  There is a famous case study documented by Safi Bahcall – An American Physicist. Amgen and Biogen both tried to hire University of Chicago Professor Eugene Goldwasser.  Goldwasser was key in taking one of their drugs to the next level as he held the key to a winning protein. The purified protein developed by Goldwasser contained the code to making the drug.  Both the companies fought hard for Goldwasser and his protein. Goldwasser decided to join Amgen and decided to give Amgen the protein vial rather than its main competitor, Biogen. The only differentiating reason between Amgen and Biogen?- Biogen’s CEO had refused to pick up the check for dinner one night.  The drug that was subsequently developed erythropoietin, or EPO for short, turned out to be far, far more successful than anyone imagined.

Last month we experimented with a large telecom and 5G provider.  Our experiments resulted in closing 500 positions in less than 17 days for a mix of software and network-related roles.  This was a great collective achievement by the team.  Any output like this, the team gets more credit than the data supplier.  As a result, what I am writing is only a collective story, and our part is a small part of that

Let us look at the steps taken in this experiment.  At the outset, we decided to do certain things differently

As significant changes have happened in Telecom within 5G, conducted a 30-minute workshop on what 5G is all about.  Practical examples around how a factory floor will be different with and without 5G.  Nearby concepts like IoT were also explained.  This provided lot of talking points to the Recruiters.

At the end of the day, people want to join other successful people.  But many companies give attention to only top leaders. (even when we talk about Tesla, people mostly know Elon Musk – but Peter Rawlinson, who also played a major role and now started Lucid, a Tesla Rival).  We mapped the key middle-level leaders and resources and highlighted the projects (in an objective way).  This project library is very crucial.  For example, a Bank may be working on a very cool Computer Vision project that recruiters may not know while hiring for ML talent

The days of targeting one candidate for one Role are changing.  Technologies are converging, and people want to move fast.  A great QA automation engineer is no longer a candidate for QA.  They are your prime targets for Development.

Long-term success in Recruitment is actually not in identifying the most successful candidate.  It has to do with how you file all the good candidates may not be suitable at that time and for a given job.  This is actually a concept we borrowed from Inventory Management.  In the Factory Floors of General Motors, I have often seen when a part is rejected; its attributes are documented and stored to become useful in the Future.

As described in the last email, Battlecards have to be drawn out very specific to Roles and companies. This is an extreme time saver in many of the screening phases. As I have already written about this, I am not going to the full depth of this, but if you need Battle Cards, please reach out to us. 

Estimates such as Time to Close can show high-level hiring difficulty trends for a role.  But sometimes, these estimates can slowly inflate.  Let us say there are three major steps. (for argument).  Planning and Searching for Candidates (T1), Screening (T2), Selecting (T3).  Each step has a range (say 15 to 25 days for planning and Screening, 5 to 10 days for Screening, and say 10 to 14 for Interviews).  Constrained Optimization Principles discovered that the total time of T1+T2+T3 is far more spread out than the individual tasks.  So each task inflates even beyond the originally planned variability.  In the time buffer concept, you plan for exactly ½ of your estimate and put the rest in a buffer.  If you typically budget 7 days for Screening, you plan for 3.5 days and put the rest in Buffer (you use the Buffer only if you need to) and migrate to the next task.  Here is a schematic representation of this.  This can be a useful technique for many other activities as well.  You may be practicing this differently.  The point is to bring process efficiency.