HR needs reporting format

Opinion
HR needs reporting format

ONE of the critical functions of any board is ensuring the organisation's human resources (HR) is put to good use. To enable the board to execute this task effectively, they need information on how human resource activities impact business performance. 

This task is even more difficult because most of the board HR committees are chaired by people without HR experience. This is not a significant challenge as long as the committee members have the right information to make informed decisions.

Today's major challenge is that the human resource function is one of the most under-reported functions in most organisations. As a result, most of the scandals bedevilling organisations tend to start in the human resources department.

Most board members have no idea what happens in human resources.

In most cases, they only wake up after a scandal in the human resources department. This should not occur if the board is supplied with the key indicators from human resources. Most reports supplied to boards have tended to be narratives not supported by any factual information in most cases.  Trends are changing. Human resource management and reporting need to be data-driven.

I know a few progressive organisations that have started well on this journey. Those that have started have moved from opinion-driven reporting systems to data-driven systems.

The only challenge with where they are is that the information is still descriptive, with no significant insights coming from the data even as they move into data-driven areas.

I want to classify the level of reporting at the board level into four categories. Level one is opinion-driven (primitive stage), level two is the descriptive stage, level three is the predictive stage and level four is the prescriptive stage.

At level one, the information provided is mainly opinion-driven. Reports at this stage are narrative and full of the opinions provided by the human resources department staff on several issues.

The assumption at this stage is that the people in human resources know what they are doing and act in the company's best interest. We know this is not ordinarily correct, as most senior managers in HR and other departments make decisions driven by their interests. There are chances that the board may make serious human resources errors if they base their reports on the above.

In stage two, you will mainly find descriptive reports. Typical board reports cover the number of people on sick leave, the number of people on leave, headcount and number of disciplinary cases handled, the number of people trained, etc.

This is all good, but no insights come out of such reporting. It is almost like information for noting when it is supposed to assist the board in making decisions.

To enhance the reports at this stage, there is a need to go deeper than just providing the figures. For example, instead of reporting on the number of people on sick leave, annual leave, and study leave, you could indicate the cost the company is incurring because this is paid leave.

You could also add the costs of covering up for the individuals on leave and loss of productivity. Every data you find in the human resources department can be turned into insights to help the board make better decisions.

Instead of reporting staff costs to revenue on a global level, you need to break staff costs to revenue by level and executive staff costs as a percentage of the overall wage bill. If you have industry benchmarks for the same indicators, it is even better.

The predictive analytics stage brings even better insight for the business. While the data comes from the human resources department, the impact is always measured in business performance. Many companies are struggling, for example, with workforce planning. They do not know how many employees (establishment provision) they need for a particular period nor the headcount costs for the future.

If they do, many of these companies guess these figures and usually discover later, for example, that they are over- or understaffed. Many of the retrenchment exercises we are seeing could have been avoided if companies had done proper workforce planning using statistical models.

Still, in the predictive stage, the human resources department can predict the employees likely to be top performers before hiring. The board would be delighted to have such information, especially for senior and critical roles in the organisation.

A Flight Risk Calculator can predict, which employees will likely leave the organisation and when. This will enable the organisation to arrest the situation before the competent employees leave. Flight risk can also be calculated for new employees as they enter the organisation. I have given a few examples, but there are so many areas where predictive analytics (using statistical models) can add value to the business.

There are many other HR solutions based on your company’s data that you can start implementing. Leading international companies, such as Google, have spent years methodically building Human Resources Management Systems, which paved the way to their incredible success.

Companies of different sizes operating in different industries can benefit from extensive data analysis. If you have not thought about building a comprehensive database for your company, it is high time you do.

Subjective (guesswork) decision-making is dangerous. Many companies are struggling because of it. Leading companies globally have embraced a data-driven approach to human resources management because of its immense benefits. It is high time Zimbabwean companies adopt evidence-based management.

The prescriptive stage is the pinnacle of human resources reporting. At this stage, you can tell which human resources policies or interventions will bring immense value to the business before implementation.

  • Nguwi is an occupational psychologist, data scientist, speaker and managing consultant at Industrial Psychology Consultants (Pvt) Ltd, a management and human resources consulting firm. — https://www.thehumancapitalhub.com or e-mail: [email protected].

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