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The HR Board Report

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Memory Nguwi

One of the critical functions of any board is to make sure 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 made even more difficult because most of the Board HR Committees are chaired by people with no HR experience.

This is not a significant challenge as long as the committee members are provided with the right information to make informed decisions.

Today’s primary 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 some form of scandal in the human resources department. This should not happen if the Board is supplied with the key indicators from the human resources.

Most of the reports supplied to boards have tended to be narratives not supported by any factual information.  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 even as they move into data-driven areas, with no major insights coming from the data.

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 a 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. 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 normally 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 mainly find descriptive reports.

Typical Board reports cover things like 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 are driven from such reporting. It is almost like information for noting when it is supposed to assist the Board to make a decision.

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’s even better.

The predictive analytics stage brings even better insight for business and not for human resources. 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 neither know how many employees (establishment provision) they need for a particular period nor the what cost. 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 who are likely to be top performers before they are hired. The Board would be delighted to have such information, especially for senior and critical roles in the organisation.

The Flight Risk Calculator can predict which employees are likely to 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 have subsequently 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 given any thought to building a comprehensive database for your company, it is high time you do. Subjective (guesswork) decision making is dangerous. 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 they are implemented.

Memory Nguwi is an Occupational Psychologist, Data Scientist, Speaker, & Managing Consultant- Industrial Psychology Consultants (Pvt) Ltd, a management and human resources consulting firm. https://www.thehumancapitalhub.com email: mnguwi@ipcconsultants.com  or visit our website at www.ipcconsultants.com

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