A central tool for human resources management, HRIS has one limitation: it is not designed to help operational staff achieve their objectives. And yet, they need to have a global, up-to-date view of the skills available. In this context, how is it possible to align everyone's interests? And what if field data could solve this problem?
Most HRIS systems only benefit support functions
Before getting to the heart of the matter, let's set the scene. HRIS stands for Human Resources Management Information Systems. In other words, they are software packages focused on personnel administration. They are used by HR teams to perform a variety of tasks:
- Managing employment contracts
- Creating pay slips
- Tracking leave and absences
- Identify expense claims
- etc.
These are often comprehensive tools designed to improve the productivity of support functions. Data is centralized, and low value-added tasks are automated, allowing HR teams to concentrate on the human side of things. The software covers all human resources processes, while simplifying them at the same time. In this way, HRIS is first and foremost designed to improve performance.
Over and above this notion of productivity, these software packages also enable better management of talent thanks to a wide range of indicators. In financial terms, for example, you can track payroll or recruitment costs by business line. Other metrics focus more on risk factors, such as turnover, occupational illness, accident rates and absenteeism.
Finally, HRIS also meets legal constraints. Indeed, since 2018, the law on the General Data Protection Regulation (RGPD), companies are required to secure their employees' personal data. HRIS are therefore designed to meet this obligation.
While these functions are an invaluable aid for human resources professionals, the same cannot be said for operational staff.
And it makes sense. As we've seen, this tool is designed to help support functions achieve their objectives. And these objectives are not the same as those of operational staff.
HRIS insufficient to meet operational challenges
In a company, each department acts to achieve its objectives. The HR department, for example, is responsible for recruiting the best talent. For their part, operational staff do their utmost to maximize production. In theory, HRIS data would be useful to operational staff. However, this is clearly not the case.
Most of the time, this information is top-down, and by definition does not reflect reality on the ground. Support functions have a relatively biased understanding of operational expectations and challenges. This is particularly the case in the industrial sector, where it is common to hear site managers complaining about the poor understanding of their business by human resources managers. One only has to read the job offers published by HR to realize this: the skills mentioned and the job description are sometimes far removed from reality.
To meet their challenges, operational staff are looking for solutions designed specifically for them.
For example, in the field, managers want to save time to :
- Know which operator has which skills, so you can assign him to the right job
- Know if your team members are present to know if they can handle the workload
- Anticipate retirements to train new people early enough
- Participate in the recruitment of future team members
- Monitor the team's versatility rate in order to improve it.
- Supporting operators, particularly in terms of upgrading skills
For their part, operators also have their demands:
- Ensure that their skills are known and valued
- Be able to apply for training courses in line with their career plans
- Continuous training and support
Today, a good number of companies are unable to meet the operational challenges that guarantee healthy growth.
Reconciling support and operational challenges
In such a context, how can we enable as many people as possible to take advantage of field data to move in the right direction? Should we start from scratch?
Fortunately, no. Instead, all we need to do is rethink the way in which data is collected and used by the various stakeholders. In fact, the best way to guarantee data reliability is bottom-up, not top-down. In concrete terms, this means collecting data from the field and sharing it with the rest of the company.
This system benefits not only operational staff, but also support functions. For example, HR can rely on an approach centered on real, up-to-date data from the field. Decision-makers, for their part, benefit from this data to establish a finer strategic vision, and to better anticipate the future.
Data from the field is essential for any company wishing to gain in agility and versatility, two qualities that are essential in the face of accelerating digital transformation and the emergence of new professions. Moreover, the implementation of strategic workforce planning (SWP) requires the company to have access to reliable data.
The question then arises: how to retrieve and circulate data from the field? The ideal solution would probably have to meet the following criteria:
- Make it easy to centralize information
- Be usable by every team member
- Generate indicators for support functions and operational staff
With these characteristics in mind, it's easy to see why using spreadsheets is not the ideal solution. However, there are turnkey tools which make it easy to manage data in the field, and transform it into customized dashboards. In this way, the interests of support functions and operational staff are reconciled!
In a nutshell
HRIS are tools for managing various administrative tasks, such as generating pay slips, managing contracts and tracking leave. While these tools help HR departments to achieve their objectives, they do not address operational issues. In fact, data from the field often remains... in the field.
The problem? This creates a compartmentalization of information, and a vision of the company's human resources that doesn't correspond to reality. While team managers are responsible for achieving operational excellence, they can't rely on HRIS data to implement the right actions. To change this, we need to change the way data is collected and used.
