How to Make Smarter, Data-Driven Decisions With Workforce Management Analytics

According to the Economist, “the world’s most valuable resource” is now data – but is your business taking advantage of this? 

Companies have a wealth of data already available to support them in making smarter decisions on everything from rostering to budgeting. Yet knowing how to collect and correctly interpret that data can be challenging. 

Let’s look at the workforce and HR data that you should be analysing and how to make use of it.

How Data Can Help You Make Better Business Decisions

The data’s in: data really does help you make better decisions.

Data-driven companies are significantly more profitable and productive. They increase their revenues, reduce their costs and make objectively better decisions. 

These companies can predict upcoming changes, detect issues earlier on and spot areas for growth. They are more responsive because they pick up on the first signals – instead of waiting until their competitors have already acted.

Not all data is helpful, however. If you analyse old or patchy data, you will not have the whole picture – and you will make poor decisions as a result. 

Useful data is accurate, current and complete. It is accessible, which means it is easy to collect and interpret. And finally, it is actionable, i.e., it gives you clarity over which actions to take.

Fortunately, most businesses already have accurate, current and complete data available to them. As for accessibility and actionability, that comes down to processes and analytics systems.

The Workforce & HR Data That You Should Be Collecting

Every time an employee clocks in for a shift, you have new data. Every time someone is absent, late, or works overtime, you have more data. This data may not, on a per-item basis, reveal much. However, when you look at all the data, a useful picture should emerge.

The most important data will vary according to the company. At a minimum, however, you should collect:

Projected vs actual labour costs – how much did you think you were going to spend on labour and how much did you actually spend?

Projected labour demand vs actual labour demand – how many staff members did you think you needed and how many did you actually need?

Rostered vs clocked hours – are clocked hours more or less than those rostered, and if so, what is the pattern and the reason behind it?

No-shows – how many workers are absent, how many of these are unauthorised, and how does the data change according to the staff role and shift details?

Late starts – what percentage of staff members start late, how late are they, and is there a pattern to this?

Worker engagement – how engaged are your staff and how does this fluctuate?

You should be able to analyse this information on a per-shift and per-hour basis, but you also need to be able to take a step back and see the weekly, monthly, seasonal and annual trends.

How to Use Workforce Management Analytics for Smarter Decision-Making

Collecting data is the easy part. Interpreting it and taking action, however, is important. Unfortunately, it is also where many businesses stumble.

To move from collecting data to objective decision-making, follow this six-step process:

1. Identify the Most Relevant Data

Start by deciding what you want to know, and then identify which data is relevant. For example, you may want to know how worker engagement correlates with correctly projecting labour demand.

2. Create Reports that Facilitate At-a-Glance Understanding

Data is useless if it is too complicated to interpret. Unwieldy spreadsheets, large tables and numbers without context will make your data unusable. Instead, use a workforce analytics system to produce well-presented, easy-to-interpret reports.

3. Analyse and Interpret the Data and Reports

Look at the data with an open mind, and be prepared to be proven wrong. It is easy to cherry-pick information that confirms what you already expect to find, so seek out other people’s opinions too. Visualising data can help prevent confirmation bias, so make sure your reports contain charts.

4. Create Hypotheses Based on the Data and External Events

Based on the data available, you can make reasonable hypotheses about what will happen in specific situations. For example, when storms are forecasted, restaurants can look at the reports to see not only how this has affected labour demand in the past but also what percentage of the workforce tends to arrive late or not at all.

5. Put the Data into Action

Now it is time to use the data to make strategic decisions: in stormy weather, do you recommend that staff set off 10 minutes earlier? Roster them to start 10 minutes earlier? Or only roster staff that live nearby? Whatever decision you make, it is time to put it into action.

6. Continue Collecting, Analysing and Refining Your Understanding

The more data you have and the more hypotheses you test, the better your understanding of your workforce and labour demands will become.

Data is a valuable tool. It enables you to make informed, smart decisions. You will be better able to predict worker demand; spot issues early on for smoother day-to-day operations; and improve worker satisfaction, customer service, and your company’s bottom line.

Humanforce is a workforce management system that not only helps you compliantly roster staff but also tracks and analyses workforce data. It measures and compares clocked hours, rostered hours, no-shows, late starts, overtime, shift costs and more.

What’s more, the Advanced Workforce Analytics for Humanforce Cloud provide deeper insight into your workforce data. These dashboards help you pick out the information that matters, simultaneously giving you at-a-glance insights and all the finer details you need. Pre-configured reports are available and ready to go across these key areas: Employee Health, Payroll Success, Rostering, Approved Hours, Employee Clocking and Shift Offers.