AI and Strategic Workforce Planning
Goldman Sachs estimates almost two-thirds of US occupations are exposed to automation by #AI. [i] OpenAI estimates 80% of the U.S. workforce could have at least 10% of their tasks affected by the introduction of GPTs.[ii] Accenture estimates that 40% of all working hours will be supported or augmented by language-based AI.[iii] These insights are attention-grabbing and a source of consternation amongst the working population. Morning Consult recently found that 65% of U.S. adults are concerned that AI could lead to job losses.[iv] That angst is understandable – technological advancements have historically been closely followed by evolutionary changes in certain labor domains. This feeling of uncertainty and nervousness is compounded by headlines that large organizations pause hiring activity for jobs that AI could perform.[v] Further, the pace of innovation in the AI space is astounding – not only are established players investing billions into the technology, but third-party developers are also clambering to claim their plot of land in this new world.
Practically speaking, what are the implications of this to the practice of Strategic Workforce Planning? What considerations should practitioners take as AI advances and gains mainstream levels of adoption? How should strategic workforce planners adjust their scenario planning to anticipate potential future workforce risks?
Definition. Strategic Workforce Planning is a business practice that enables data-driven workforce decision making to align workforce strategies with business strategies. It involves estimating an organization’s future workforce demand beyond the next budgetary cycle and across multiple years, and evaluates the size, nature, and sources of workforce supply that will be required to meet the estimated demand. It is a disciplined business process that informs and aligns business decisions and actions impacting the workforce with the strategic needs of the organization.[vi] In more simple terms: it is a data-driven approach to aligning an organization’s business strategy with its workforce strategy. Strategic workforce planning differs from resource management, headcount planning, and operational workforce planning in that it focuses on a longer time horizon, whereas the other three focus on the immediate or near-term time horizons for workforce needs and budgets.
Strategic Workforce Planning focuses on the long-term with a planning horizon of two or more years. Art generated by DALL-E2.
Strategic Workforce Planning uses organizational and external data to capture the current state of the workforce, forecast the workforce supply, and model “what-if” scenarios regarding future workforce demand according to anticipated business needs. Take, for example, an air conditioning manufacturer who forecasts certain maintenance revenue over the next 5 years based on its existing customers. That manufacturer may draw three different scenarios into its strategic workforce plan, which may include
1) a steady increase of customers as global temperatures continues to rise, thus increasing usage of AC units and the need for maintenance,
2) a decrease in customers due to market competition, or
3) a substantial increase in customers due to the acquisition of a competitor.
These scenarios would consider internal business priorities and strategic plans, in addition to insights from external environmental scans, and would then be used to model workforce needs over the designated time horizon (e.g., given scenario 1, in 3 years the organization might be short 200 maintenance technicians across its European market). Most forecast models are completed at the workforce segment or position cluster level, or at the position or role level for critical roles. Organizations with the means and the capability might plan even further by breaking these roles into their task components and then defining the skills required to complete those tasks.
Arguably every organization stands to benefit from a well-functioning Workforce Planning capability, but the amount of value obtainable from conducting regular Workforce Planning along a given time horizon (short, medium, or long) and to a given depth of granularity (position clusters, roles, or skills) will vary based on the organization’s business drivers, industry, culture, capabilities, and ambitions.
Implications
With this foundation in mind, let us consider the implications technological advances in AI have on the practice of Strategic Workforce Planning. There are three areas to consider: People, Process, and Technology.
People. Process. Technology.
Image generated by DALL-E2
People. Workforce planning practitioners are typically required to bring certain skills and expertise to the job. Many of the skills will continue to be needed even as generative AI matures, but additional emphasis will be placed on critical and strategic thinking, empathy, and curiosity. As large language model applications like ChatGPT continue to evolve, some analytical tasks will be augmented by AI, but the ability to think critically about the output, to ask the right questions, identify the critical problems to be solved, and “connect the dots” will be differentiators. Empathy will increase in importance because the providers, collaborators, customers, and consumers of Strategic Workforce Planning data are all people, and empathetic leaders create environments where people feel heard, valued, and understood, which leads to increased trust, collaboration, and communication between stakeholders. Curiosity will increase in importance because workforce planning practitioners must continue to learn new ways of working as AI tools and applications continue to evolve.
Process. The process of Strategic Workforce Planning starts with organizational strategy, flows into assessing the current state of the workforce, forecasting future supply, demand, and the different between the two, then formulating, executing, and measuring a workforce strategy. The process itself has existed for decades. Though practitioners used different terms to describe the process (“HR Planning,” and “Manpower Planning” to name a few) 50 years ago organizations developed sophisticated models to forecast how manpower supply might match demand[vii]. The increased sophistication and adoption of generative AI will reduce the amount of time needed to complete process steps and entire process cycles, thus allowing organizations to analyze more segments of their workforce than they previously could.
Technology. Technological advancements tend to improve or replace existing technologies, so generative AI will be used to evolve existing workforce planning tech platforms. Consider Workday as an example, which is becoming an “AI-enabled ERP” that can predict hiring and staffing needs based on month, weather, and other external inputs.[viii] This change is occurring on all levels of the workforce planning technology maturity curve – from the simple excel-based models to the more advanced cloud-based platforms that integrate FP&A and other data with workforce planning processes, models, and decisions. These advancements mean workforce planning practitioners can use predictive analytics, natural language processing, and other AI technologies to enhance the variety of talent processes that inform, and are informed by, workforce planning[ix].
Considerations
What use cases for Generative AI would benefit your organization’s business? More and more use cases are being shared daily and span across disciplines and industries. ChatGPT is being used as a life coach, a study aid, a proof-reader, a code generator, or a content drafter. Generative AI is changing the world of creative work[x] and may soon be used by every user of Microsoft Office products[xi]. While many technologies are designed for a specific use case, generative AI can be applied to a variety of use cases and is seen as a general-purpose tool that will enhance productivity across the economy. The first step in identifying how it could benefit a specific organization is gaining an understanding of what generative AI is, and what it is not, and then determining which outcomes it could add value to.
From which segments of your workforce could the organization gain the most value if roles were augmented or automated? Will a task-based approach be needed to make this determination? Which workforce segments should NOT be augmented or automated? The studies cited at the beginning of the article were conducted by breaking occupations down into their task components. Strategic Workforce Planning practitioners may benefit from doing the same for certain segments of their workforce to further understand which tasks could be augmented or automated. The output of this exercise could inform discussions on the use of generative AI tools within the organization. Not only that, but it would assist both workforce planning practitioners and other stakeholders make informed talent action plans (think build, buy, borrow) by influencing the decision to intentionally restructure the work being done. There may also be roles in the organization that should not be intentionally augmented or automated, even if it technically possible, due to certain risks, limitations, or trade-offs inherent to such augmentation or automation.
What AI skills could your organization benefit from obtaining even if there is no intention of formally automating of augmenting any roles with generative AI? Prompt Engineering was cited as an emerging skill by the World Economic Forum[xii], but a recent Harvard Business Review article, “AI Prompt Engineering Isn’t the Future,” Oguz A. Acar argues that effective problem formulation will be a more enduring skill as generative AI continues to evolve.[xiii] Why will this be important? Because generative AI is an emerging general-purpose technology, which is a technology that impacts entire economies. One such technology rose to prominence about 40 years ago: the internet. The ability of an organization’s workforce to use generative AI tools and create value for an organization, whether via productivity gains or creative outputs, will depend on everyone's ability to use the tools.
Conclusion
The practice of Strategic Workforce Planning needs to change along with the Fourth Industrial Revolution. By understanding the implications of mainstream generative AI use and by altering their existing SWP practices to take advantage of these technological advances, SWP practitioners stand to influence their organization’s workforce strategy and economic success.
#strategicworkforceplanning #workforceplanning #generativeai #aiimpact #futureofwork #ai
[i] Briggs, J., Hatzius, J., Kodnani, D., and Pierdomenico, G. “The Potential Large Effect of Artificial Intelligence on Economic Growth.” Goldman Sachs. March 26, 2023.
[ii] Eloundou, T., Manning, S., Mishkin, P., and Rock, D. “GPTs are GPTs: An early look at the labor market impact of large language models.” OpenAI. March 17, 2023.
[iii] ”Accenture Technology Vision 2023: Generative AI to Usher in a Bold New Future for Business,
Merging Physical and Digital Worlds” Accenture Newsroom. March 30, 2023
[iv] Wheeler, Jesse. “American Workers Brace for a Recession in the Near Term and the Impact of AI in the Long Term.” Morning Consult. May 31, 2023.
[v] Ford, Brody. ”IBM to Pause Hiring for Jobs That AI Could Do.” Bloomberg. May 1, 2023
[vi] Gibson, A. ”Agile Workforce Planning.” Kogan Page Limited. 2021.
[vii] Reilly, P. ”Human Resource Planning: An Introduction.” The Institute for Employee Studies. 1996.
[viii] Bersin, Josh. ”Workday’s Response to AI and Machine Learning: Moving Faster Than Ever.” JoshBersin.com. March 17, 2023.
[ix] Frackiewicz, M. ”AI in Workforce Planning.” TS2. May 16, 2023.
[x] Davenport, Thomas H. and Mittal, Nitin. ”How Generative AI is Changing Creative Work.” Harvard Business Review. November 14, 2022.
[xi] Stallbaumer, Colette. ”Introducing Microsoft 365 Copilot – A whole new way to work.” Microsoft. March 16, 2023.
[xii] Whiting, Kate. “3 new and emerging jobs you can get hired for this year.” World Economic Forum. March 2, 2023
[xiii] Acar, Oguz A. ”AI Prompt Engineering Isn’t the Future.” Harvard Business Review. June 6, 2023