How Does Analytics in Workforce Management Software Increase Revenue and Improve Performance?
Analytics allows organizations to make data-driven decisions on the planning and management of their workforce. The insights gained provide a deep understanding of how the workforce and their actions are impacting the bottom line – and from there, interventions can be introduced that will reduce costs and inefficiencies, unlocking the workforce’s true potential.
What is the Difference Between HR Analytics and WFM Analytics?
HR analytics encompasses a broad range of processes – everything from recruitment to employee wellbeing – and analytics modules may integrate with various types of workforce software.
HR analytics help to predict things such as time to hire for a vacant position; it can also optimize the effectiveness of training or assess the impact of external events (such as the pandemic) on morale, engagement, or productivity. From there, helpful initiatives can be introduced – initiatives driven by data.
On the other hand, workforce analytics looks at the non-people-focused processes. It relies heavily on data from your payroll management software, and can uncover insights about performance management, staffing allocation, labor inefficiencies, and so on.
Applying analytics to all areas of HR is valuable; however, this article will focus only on analytics as it applies to Work Force Management.
The Benefits of Analytics in WFM
The overarching benefits of workforce analytics are savings in time and money. More specifically, it allows organizations to accurately:
- Predict hiring needs
- Optimize rostering
- Predict required staffing levels at specific times
- Control payroll costs and improve cash flow forecasting
- Reduce absenteeism
- Improved employee retention
- And much more
Workforce analytics allows for a proactive instead of reactive approach to everything from troubleshooting inefficiencies to identifying areas for improvement.
It provides a broad perspective of the workforce and its current and potential problem areas, allowing for solutions to be introduced before problems escalate. Insights can be provided in real-time, allowing for a fast, agile response.
Workforce analytics assists in aligning workforce planning and management with business objectives. For example, the performance of a particular department or shift could be monitored for effectiveness; if issues are found, further probing may reveal what needs to be done about it (i.e., better training, better engagement strategies, and so on). This kind of oversight would take a long time to establish without analytics.
In turn, analytics can in itself help improve engagement and motivation by creating a culture of recognition and strengthening team spirit. When performance data is worthy of praise, the respective teams can be rewarded for their contributions.
Finally, analytics is essential when it comes to optimizing large-scale operations. Multinational organisations gather immense volumes of data in their WFM systems and analytics puts it to good use. It also empowers organisations to derive valuable insights from complex and highly varied data across regions (regarding labor laws, taxation, and so on).
The best logiciel de gestion des effectifs has integrated analytics features.
Types of Analytics Used in WFM
This form of analytics uses historical data in order to predict trends. These trends may pertain to areas such as labor market changes, employee turnover and skills shortages. Once again, this form of analytics enables a proactive approach by modelling how requirements will evolve over time.
As above, historical data is used with these models. The difference here is that recommendations for improvements are made and – in models backed by Machine Learning – the recommendations would be based on what has proven to be most effective in the past.
Diagnostic models assess workforce performance metrics in order to uncover the causes behind successes and failures. In other words, it helps to shed light on otherwise hidden workforce issues. Based on these insights, organizations can take the necessary steps to eliminate inefficiencies and improve the required areas.
Use Cases of WFM Analytics
We mentioned above that workforce analytics greatly relies on payroll data. Well, it’s important to note that analytics can achieve more than payroll reporting is capable of; while reporting is beneficial, analytics provides a multi-faceted view of the payroll function and its underlying trends in order to provide decision support. For example, it can help identify which aspects of the organization are most productive and which are having disproportional effects on indirect labor costs.
In a large organisation, absenteeism can slip under the radar. Thanks to analytics, you can find patterns pertaining to specific departments, teams, shifts, or individuals as well as the impact that missed work days are having on business objectives.
Below are some more examples of the types of insights that are possible with workforce analytics.
Minimizing Payroll Errors
Analytics minimizes payroll errors by identifying their cause, allowing companies to find ways to prevent their recurrence. Even the smallest of errors can cause compliance issues, so this is a great benefit.
If errors occur at a specific time of year such as the holidays, it suggests that the workflow or staffing numbers are sub-optimal; on the other hand, if they occur at a specific branch, it indicates the need for further training in that location.
Of course, if you use our payroll management system, there will be no errors in the first place.
Analyzing performance helps businesses to plan ahead with accuracy and make informed decisions on staffing, especially during periods when staffing levels will need adjusting.
For example, consider a scenario in which a manufacturing business is introducing a new product to their repertoire. Assuming the product is successful and demand grows, decisions will need to be made about how best to tackle the impending changes.
Would it be best to hire new staff or are the existing teams so productive that it would be more effective to offer overtime? What about a combination of both? How would the training costs of new staff factor in? Should new workers be temporary or full-time?
Analytics can provide clear answers to these questions, helping organisations make the best decisions, manage cash flow, and meet their broader objectives.
Much like the previous example, any changes in the business (whether plans for expansion or simply operational changes) can be made in the most cost-effective way possible thanks to analytics. What if a company with several branches was looking to expand the resources of one of them and needed to decide which would be the most optimal?
Analytics would reveal the most profitable decisions based on factors such as the cost of wages in each area, the tax liabilities, and so on. The same could be achieved when looking to merge branches.
These types of insights are vital at the moment due to the ongoing economic disruptions affecting various sectors.
Employee Engagement, Retention, and Compensation Management
Payroll analytics impacts broader HR strategy by helping the creation of contracts that will lead to long-term employment.
It can uncover the correlation between variables such as compensation and performance, or compensation and churn. It can also look at non-monetary factors such as flexible hours, the option to work from home, and other benefits that may cause an employee to stick around.
These insights provide a data-driven basis for avoiding the costly endeavor of losing employees and hiring replacements.
Challenges in Implementing Analytics
It’s important to use the right logiciel de gestion des effectifs if you want to start implementing analytics; no organization that uses outdated systems is going to be able to derive its benefits, and this is primarily due to the vast amount of data needed in order to gain helpful insights.
Old on-premise workforce management systems are far from optimal when it comes to storing such volumes, and they are difficult to integrate with modern analytics software. Thus, in order to start using analytics, migrating to a SaaS model should be a priority.
Data needs to be accessible in a centralized place if any analytics modules are going to be able to get accurate insights. It is not easy to get a single source of truth with data separated into silos. Once again, a cloud based WFM solution is the answer.
How to Get the Most from Workforce Analytics
A few tips for getting the best out of analytics are as follows:
- Determine the purpose for analytics – what objectives will it help your organization achieve?
- Develop a plan for which KPIs to track based on the objectives defined as per the previous point.
- Clarify which types of analysis need to be done – are you looking for correlations between two variables? Are you hoping to uncover trends? Do you require a purely diagnostic approach or will you need to use predictive and prescriptive methods as well?
- Collect data automatically using cloud based workforce management software.
Applying analytics to workforce data provides decision support in numerous scenarios. It enables a proactive approach to optimizing the workforce so that organizations can continue to minimize inefficiencies and improve performance. Some examples include accurate employee scheduling forecasts for busy seasons and discovering the connection between compensation and employee turnover.
To get the data in the first place, you need high-performance enterprise workforce management software. Manus Software Europe B.V. is Europe’s favorite provider of state-of-the-art workforce planning software, serving multinational organizations around the world for more than 30 years.
Not only do we cover all your essential WFM and payroll needs, but our workforce management solutions have built-in analytics functionality – and an API that lets you connect to external Business Intelligence tools. To discover how your WFM processes can transform, contact us today to book a demo.