This week, I was fortunate to have some quality discussions on Productivity.  We are also able to develop some initial inquiry models on Productivity.  In one of the conversations with a workforce planning leader, it dawned on me that even though we attribute Productivity to the Industrial Revolution, it is an age-old concept.  Human Beings have always strived to do more.   The quote “Better a little which is well done, than a great deal imperfectly” is attributed to Plato.  This interesting saying encapsulates a principle highly relevant to discussions of Productivity and quality of work.  It suggests that it is more valuable to produce a smaller amount of work of high quality than to produce a large quantity of work that is flawed or incomplete.  In the context of Productivity, Plato’s quote serves as a reminder of the importance of focusing on the quality of one’s work rather than just the quantity.  It encourages taking the time to do things right rather than rushing to complete as many tasks as possible without regard for how well they are done.  This approach is also echoed in many modern productivity philosophies, emphasizing the value of craftsmanship, attention to detail, and deep work.

Why are Workforce Planning Leaders thinking about Productivity?

There are many reasons for this, but the primary reason is Generative AI and its expected impact.   Gen AI Productivity discussions can get the seat for WFP leaders with the C-suite.  This is an active discussion with CHROs, CFOs, and CEOs.  External consultants often dominate such discussions, but the trend is changing.  Productivity has given an avenue to give quality conversations with the C-Suite for HR Leaders.  The C-suite has recognized that a meaningful impact on Productivity cannot happen without the support of HR leaders.

Why should TA Leaders think about Productivity?

It is also important for Talent Acquisition because the Talent they hire should be “ready and able” for the incredible productivity journey that is ahead of them.  As a result, we have to look for foundational and digital skills that are productivity-oriented.

Take, for example, a role like Market Research Analyst.  Digital platforms like Zappi offer time savings in organizing workflows.  Zappi offers an AI-driven platform for automating market research workflows.  Platforms like Domo offer powerful data visualization.  As a result, testing the candidates towards these new skills/platforms will be how we can ensure the right “Future Talent” walks into the enterprise.

One approach that may be helpful: (you can do this yourself, or we can help)

The objective here is to develop a General AI Productivity model by Draup.  The method involves segmenting roles into major workloads, mapping each workload to a General AI/Automation platform, and then aggregating the impacts promised by these platforms.

Here are some examples that we worked out.  These are still being developed and shown for initial analysis.