As the excitement of the New Year settles and the real work begins, we’re witnessing three major themes emerging among leaders at WFP and TA. Firstly, there’s an intensified focus on understanding the productivity impact across various roles. This goes beyond simple output measurements, delving into how changes in one area can influence the entire organizational fabric. Leaders are trying to understand the futuristic impact Generative AI and Automation will bring to the roles they are hiring.
Secondly, the question of when to reprioritize internal skill development is gaining prominence, particularly in scenarios where a general scarcity of skills hampers hiring. It’s a strategic decision about the right timing and approach to invest in upskilling the existing workforce to fill these skill gaps.
Thirdly, there’s a heightened interest in grasping the nuances of skills interaction across job roles. This involves identifying the necessary skills for each role and understanding how these skills interplay and affect each other within the organization’s overall structure.
These themes now take precedence in strategic discussions, eclipsing previously dominant issues such as the debate between remote and onsite work modalities or the preference between traditional four-year degrees and professional certifications. This shift signals a more profound engagement with the complexities of workforce management and a readiness to adapt to the changing dynamics of the workplace as Generative AI takes hold in Enterprises.
To shed some light on these important aspects, we are compiling some datasets to offer a directional perspective on what might be anticipated across these themes.
In software development, our discussions indicate that companies are projecting a productivity impact in the range of 5% to 8%. It’s worth noting that these figures are relatively conservative compared to the higher numbers often reported from Copilot implementations and similar tools.
When it comes to business and corporate roles, the expectation shifts to a productivity gain of about 10% to 12%. However, it’s important to recognize that these figures are derived from a limited pool of around ten interviews and may not represent a substantial statistical sample.
WFP will tremendously benefit in researching and documenting such assumptions
A key point of caution here is the risk of overestimating potential improvements without having a solid, well-defined plan for achieving these gains. While the preliminary data provides useful insights, it’s crucial to approach these numbers with a balanced perspective and not to assume overly optimistic outcomes without substantial evidence and planning. We will be providing more clarity/additional data as we learn more.
Why is this important for TA?
The Role of WFP and TA becomes critical in enabling enterprises to reach these productivity assumptions. Draup wants to design a framework that will be very helpful in capturing some nuanced TA workloads that can help organizations in their productivity journey. This could help TA evolve as a potential advisor to the enterprise on ground-level challenges toward realizing the required productivity.
Let us say that we are hiring for a Financial Analyst Role. (as an example). The following planning table will help actions TA may take during the hiring process to help in the company’s future productivity goals, thereby playing a transformative role.
A sample table to illustrate the point: the table is not complete but sufficient to give you the perspective. (Specifically, focus on Column 3 – TA Workloads for Enterprise Productivity Goal)
As you could, documenting such productivity-focused workloads would be transformative. Kindly let us know if you would like to discuss this approach further.