Summertime is a good time to think about the future: Either we’ve accomplished what needed to be done before the holidays and we’ve had plenty of time to come up with new and creative ideas, or we still have a large stack of files and we’re forced to face reality:

  • They have to be done before September ends
  • It would be nice to be more proactive and prepare for next year

Either way, concerning talent management, it would be ideal to work towards improving the supply of Talents based on business objectives and the vagaries of the business environment.

Unfortunately, this can turn out to be quite complex.

A logic often associated with ERP (Enterprise Resource Planning)

Historically, resource planning and the synchronisation of business cycles that serve as the foundation of the Supply Chain are provided by Enterprise Resource Planning (ERP) software. Traditionally, these programmes excel in processing long series, continuous processes and generally any well-defined process.

ERP logic faces certain challenges when a company organises its activities around projects or short series, such as those involved in industrial nearshoring or on-demand production. Indeed, the creativity and the adaptability required in this context is harder to manage within the ERP as required logical sequences, products or services might not be pre-configured within the ERP. In this case, the ERP must be reprogrammed and readapted in order for it to be as powerful for each project or short series as it is for more established contexts.

This challenge is usually managed by implementing synchronisation interfaces and solvers between ERP and expert tools used alongside, such as CAD, PLM or architecture software.

HR data are distributed far beyond HRIS

When it comes to talent management, complexity is taken to the next level. First of all, the data, variables and logics of adjoining talents are generally distributed in a multitude of software, which creates just as many potential blanks and breaks in the chain when placed in a planning logic.

In terms of recruiting, it is not uncommon to see candidates being managed with a recruiting software. Some mobile talents are managed in the information system of third party companies (employment agencies, recruiting companies, subcontracting), while others are stored as social media contacts.

If we look at talent management as a whole, employees are often managed from a career and HR development point of view in talent-management software. Core HR and compensation can often be found in ERP. Employees’ activities and competencies are indicated in separate HRIS software, such as project or collaborative work management tools, but also in a less or non-structured manner on the company’s social media.

In terms of global talent management, planning to ensure the availability of good skills at a timely and optimal manner must appeal to multiple and heterogeneous sources of information, which represents an information system-related challenge.

5 Complexity factors beyond HRIS issues

Must everything be managed using only one system? Must the interconnection of different information sources be managed? This article is not meant to answer these questions. There are now solutions to these technical aspects thanks to cloud and semantic related technologies. In fact, the true complexity of planned talent management lies in the five other forms of restrictions:

  1. Competency lifecycle: The advances in technology have caused new competency needs to emerge, making other competencies obsolete. This phenomenon is not limited to technical domains. It is clearly visible in the field of mainstream software, including the most popular ones, where often users are not able to assimilate the latest advances as quickly as they come. This can even lead to a reduction in productivity and rejections. Windows 8 is a perfect example of this, where users, the majority of who did not take advantage of the innovations, were disoriented during the system upgrade. The provisional management of talents therefore requires an active oversight on competencies, their lifecycle, emergence and the different ways of acquiring them. Observing competency lifecyles and their emergence can be partially automated thanks to semantic technology. Everything else requires field research.
  2. The company’s strategy: The company’s strategy has a clear impact on the planned management of competencies. In this way, each orientation corresponds to a series of specific competency needs that may not be available to the company when needed. Likewise, the chosen strategy affects the way in which the provisional management of competencies must be taken on. A strategy governed by costs will for instance have very different consequences on talent management than one founded on innovation.
  3. Everyday urgencies: The planned management of competencies cannot anticipate all the vagaries of the business environment. Nevertheless, it must devise up coping mechanisms and consider multiple factors, such as turnover rates, the relationship between supply and demand, the social climate, and the recruiting timeline per profile.
  4. Free will: Due to its human dimension, resolving Talent Resource Planning problems is more complex than for other resource management challenges. Indeed, it is risky to count on a person’s availability without knowing their opinion on the matter, which is what makes planned talent management quite unique. This factor is all the more important as the profiles are rare.
  5. The increasing diversity of work types: As employment contracts evolve, new more independent forms of work are developing and should continue to develop. On the one hand, digital technology reduces the cost of transaction, as theorised by Oliver Williamson, and thus reduces the economic utility of business firms in their design of the 19th and 20th century. On the other hand, job security was swept away at the turn of the 21st century; the “social contract” no longer holds true, and it is only natural that individuals wish to gain some freedom.

Moreover, in an economy where innovation and the ability to adapt are strong qualities, a new focus may be placed on freelance or temporary profiles, which are naturally more prone to change.

In most cases, the various job forms can be combined to cater to the need in competencies and optimise the choices in this domain. For example, planned talent management constitutes an important factor when opening a site under a restricted budget and limited timeline.

As a conclusion, it appears that if implementation of “Talent Resource Planning” is not an absolute necessity, this discipline seems able to yield major progress for the company and provides solutions to several current issues in Talent Management.

Therefore, it is most likely that companies are already working on the issue, and many more will follow in their steps to the point of creating a competitive lever.

Nevertheless, we are dealing with a particularly complex issue. Current technology, particularly semantics and artificial intelligence, make the issues put forward by Talent Resource Planning easier to understand. Through semantics, it is thus possible to carry out a real-time analysis of supply and demand and be automatically informed of changes in the competencies market. In the case of multi-agent issues, it is also possible to be aided by artificial intelligence. AI would allow for an optimal combination of recruited talents under different job forms to for instance, open a store or factory, considering costs, deadlines, availability and recruiter opinions. It would also allow for a model of the distribution of staff in a network of leisure centres, taking into account the constraints as well as the collective and individual goals.

We are however still beginning the operational processing of such issues. This processing requires expert resources as well as careful management, and above all, it is important not to underestimate the scope.


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