Why This is the Time to Try Workforce Planning with AI
Workforce planning exercises can remain frustratingly imprecise, despite the People team’s best efforts.
The reason for that is that workforce planning requires bringing together different types of information from both Finance and HR: historical performance data that is measured differently from one department to another, ambiguous information on the current state of the talent market and the company’s workforce, and company-level plans that sometimes span up to five years in the future. However, by trying workforce planning with Artificial Intelligence (AI) technology, companies might be able to dramatically improve their accuracy.
How to improve workforce planning with AI
What makes a workforce planning process impactful?
Firstly, you need to go deeper into the roles needed in the organization, and translate them into skills and areas of expertise before starting to look for candidates. Meanwhile, the People organization can use its own knowledge of the talent market to find these skills outside of the industry where it usually hires. What if those two actions could be carried out by an algorithm?
Most talent tools today deal in job titles and company names, but the right AI technology can translate large databases of job titles and company names into skill families, industries, or functional expertise. It can also relate financial information and market insights to hiring needs, making workforce planning with AI far more powerful than its current alternative.
Talent data platforms enable better recruiting AI
True talent AI wasn’t possible before, because talent teams did not have reliable datasets to use. Machine Learning (ML) algorithms, especially, can only be truly successful if they can use large amounts of clean, uniform, up-to-date data to “learn”, so to speak. Otherwise, they will simply spit out inaccurate recommendations and forecasts.
Now, with the emergence of talent data platforms, AI algorithms can produce reliable results, and talent tools can interpret nuanced information, such as how skills relate to each other or to different job families, functions, or industries.
Data platforms exist in other areas of the business already. A data platform is defined as “an integrated technology solution that allows data located in databases to be governed, accessed, and delivered to users, data applications, or other technologies for strategic business purposes.”
Similarly, a talent data platform is the foundational technology of the modern talent acquisition tool stack, and acts as the single source of truth for talent-related information. Used appropriately, it becomes the central database that unifies information across solutions, and surfaces meaningful, reliable data to every other talent tool.
The talent operations function can own more of the workforce planning process
Talent teams have been professionalizing their talent operations function and bringing in practitioners who have the right tool for this kind of job.
Up until now, workforce planning was a disjointed exercise where Finance and HR tried to work together to ensure that there would be people available to execute on the companies immediate and future plans.
Most of the time, Finance would own the strategic aspect of the exercise. By looking at past performance and future strategic plans, it would estimate an approximate number of hires in each department needed to deliver on the company’s 3 year or 5 year plans. The HR organization would try to hit those numbers with the resources assigned, and the handover line between the two functions would vary depending on the company.
With talent operations teams bringing in resource planning and analytics capabilities, the people organization, and talent teams in particular, can own more of that planning process in two different ways: they can go further upstream in the process, and they can bring more granularity to it by expanding the depth of information used for forecasts.
Talent operations professionals have the analytical skills needed to accurately model how talent flows in and out of the company. With access to the right information on planned business initiatives, and some support from the Finance team, they can translate plant openings or geographical expansions into job openings and hiring forecasts. They do not need to rely entirely on the finance function to deliver that part of the workforce planning exercise.
In addition to that, talent operations teams’ analytics and reporting capabilities can quickly surface how much time was needed to hire specific types of roles, and the drivers behind the cost and speed of each type of hire. How is the market for this or that role going to evolve in the next five years? Will it be more expensive because of the location or the skill set required? Can it be fulfilled by a junior recruiter or will it need the capabilities of a more senior team member? They can answer these questions quickly and make workforce planning far more accurate.
The next step for Talent Operations: Talent Lifecycle Management
Talent AI is already opening new possibilities for organizations, by matching candidates to roles or to requirements, simplifying recruiting workflows, and most recently, inferring skills and capabilities from past companies, job titles and other data points in the candidate profile.
One immediate impact that this evolution will have on talent teams is the possibility of looking at talent as individuals with a living, evolving set of skills with dynamic levels of proficiency, as opposed to static collections of requirements that fit an existing open role. In other words, companies will soon be able to look at an individual and understand not only the skills they have today and the value they can currently bring to the business, but how they can and want to grow, and how they might grow with the business.
For this to be effective, you will need to have a single source of truth regarding the skills in your business: ideally a dynamic platform that can ensure the data remains accurate (in real time) and can be used across various HR systems. Having up-to-date skills data in one place will help you plan for the future in an efficient way.
The future of talent acquisition and management is already being heavily influenced by this shift towards Talent Lifecycle Management. With the recent upheaval of the global job market that the COVID-19 pandemic has created, talent teams are thinking in terms of hybrid working models, both full-time and part-time, contract, project-based, in-person and remotely based throughout the globe. Whether it is to improve your workforce planning or shift your perspective on internal mobility or talent attraction, AI will play a foundational role in your talent strategy in the next few years.
In an ideal process of workforce planning with AI, the human part is to decide what factors should be taken into consideration by the algorithm, and to help calibrate the software so its accuracy improves over time. Instead of relying on human memory and creativity to find the right skills in places where the competition isn’t looking, we let the machine surface suggestions, and simply decline the ones that are unsuitable. Over time, the machine will give fewer and fewer unsuitable suggestions. With even more time, AI can even learn to decide which factors should be added or removed from the decision making process.
Implementing this kind of technology and upskilling recruiters to use it takes time, however. That is why People organizations and CHROs need to start looking now into workforce planning with AI if they want to come on top during the next economic cycle.