When examining career paths within a company (or more broadly within an organisation), one can adopt either a global approach or an individual approach. In the first case, one would focus on Strategic Workforce Planning (i.e., the forward-looking management of jobs and skills, for which the French Ministry of Labour provides an interesting definition here). In the second case, one would examine career development at the level of a specific individual or position. Far from being opposed, the two approaches are complementary. Whilst Strategic Workforce Planning provides a multi-year framework enabling anticipation of profound changes linked notably to the workforce’s age pyramid or ongoing technological transformations, the subject of individual career development enables precise responses to be given to an employee regarding their professional development prospects within the company or to identify within the organisation the profiles most likely to occupy key positions eventually.
Strategic Workforce Planning enables reflection on the framework within which career progressions occur, without dwelling on individual situations. It relies on an initial mapping of jobs and skills within the organisation. It also requires specifying targets for position volumes or skill profiles to be achieved within a few years. It is also necessary to be able to define the system’s “dynamics” by describing internal development possibilities, quantifying recruitment capacities, and modelling outgoing flows (retirement departure rules, staff turnover rates…). Based on these elements, the objective is to determine the optimal trajectory to reach the target, in terms of annual staff training and recruitment volumes by skill profile, and to identify any structural modifications required to achieve it (e.g., increased training capacity, strengthened recruitment teams).
The subject of individual career development enables zooming in on specific cases by responding to questions such as: what career progression should be proposed to an employee? How should one respond to the expectations of a collaborator wishing to enrich their career path with new skills and new challenges? How can talent be retained within the company and progressed to the organisation’s key positions? Conversely, how can profiles within the company that are likely to occupy a key position requiring filling be identified?
To address these two subjects effectively, a high-performance information system is essential. A detailed census of all skills required by the organisation’s positions and the skills possessed by each member of staff is necessary. This is the fundamental data from which work can be done. Yet this information is not always present reliably and comprehensively in companies’ HRIS. Beyond the static mapping of the organisation’s skills, it is also necessary to define the pathways for moving from one position to another and the conditions required for their achievement (e.g., training to acquire a missing skill, required seniority in a key skill). For companies with multiple sites, it may also be necessary to account for geographic considerations. For Strategic Workforce Planning, which workflows are feasible across the company’s sites? For individual career development, what level of mobility is an employee prepared to accept?
What can Artificial Intelligence and Operations Research bring to the field of Strategic Workforce Planning and individual career development? In an organisation comprising several hundred, or even several thousand, employees, the human capacity to process the enormous volume of data required to address these two subjects no longer suffices. However, Artificial Intelligence and Operations Research algorithms can handle this complexity.
Regarding Strategic Workforce Planning, the algorithms will rely on a representation as temporal graphs of the possible progressions within the company, with each node representing a skill profile and its characteristics at a given moment, and each arc representing a pathway between two skill profiles. The objective will then be to calculate the flows transiting each arc to reach the target whilst accounting for capacity constraints and unavoidable outgoing flows. It will then be possible to determine the recruitment volumes by required skill profile over the years, as well as the annual training volumes to be provided. It will also be possible to visualise the transformation of the workforce’s age pyramid over time, by working in “what if” mode, different hypotheses can be tested to ultimately determine the optimal trajectory and dimension the organisation’s recruitment and training capacities.
For the subject of individual career development, a rule-based expert system will be able to identify the most relevant candidates for a key position that has become vacant. This expert system can draw on required skills, required seniority, and geographic distance to provide a score for each candidate, thereby facilitating HR teams’ identification and selection. Conversely, the same expert system can determine the list of positions an employee seeking to advance within the company can occupy, potentially at the cost of training or complementary experience. By relying on a graph structure, it would also be possible to determine the career path(s) to be pursued within the organisation to be eligible for a key position. Machine Learning (link: https://www.eurodecision.eu/algorithms/machine-learning) can also be used to analyse existing career paths and deduce key skills and recommended pathways for a specific collaborator.
The people who comprise an organisation’s personnel are the essential resource for its success. It is therefore vital to be concerned with both the framework within which career progressions occur, through Strategic Workforce Planning, and with tools to respond appropriately to individual cases. Artificial Intelligence and Operations Research can address these challenges.