How Will AI Change Workforce Management Software in the Future?

Trends / 28 Mar 2023

A survey by Microsoft indicates that 71% of European companies consider artificial intelligence (AI) an important topic on the executive management level. In addition, 89% of respondents expect AI to bring about business benefits through optimizing operations.

The rise of AI has opened up new opportunities for streamlining a range of HR processes. From talent management to compensation management to WFM, AI can manage complex operations in ways that were once impossible. But what does the future hold?

This article will review some of the ways in which AI is already in use, as well as some applications that are likely to grow in future.

Common Applications of AI in Enterprise Workforce Management Systems

Automated Employee Scheduling

Creating accurate employee schedules is a critical part of any organization’s success, but it can often be time-consuming. However, with AI-powered workforce management solutions, this task becomes much more manageable.

AI can automate the scheduling process by taking into account employee preferences, qualifications, and availability to create optimal schedules. This not only reduces the time and effort required for managers to manually create schedules but also ensures that employees are assigned based on their skills and experience.

Furthermore, AI can help overcome the challenge of calculating accurate resource requirements. With the ability to analyze vast amounts of data, it can accurately forecast future demand and create flexible schedules for employees. This allows managers to improve the allocation and utilization of resources, reducing the risk of burnout, wasted work hours, or delays in completing tasks.

Workforce management solutions leveraging AI can also evaluate the effect of unplanned time off on the schedule. This allows managers to create contingency plans and ensure that work is distributed evenly across employees, leading to a more balanced workload and reduced stress levels.

Data-Driven Decision-Making

The best workforce management software enables data-driven decision-making. With the help of AI, managers can make informed decisions based on data insights into workforce trends, performance metrics, and other key data points.

Machine learning algorithms are used to analyze how users, especially managers, handle different tasks, and once strong patterns are identified, they can be automated. For instance, if the AI system detects that a manager has performed an action 20 times, it will prompt the manager to automate the action from then on.

One of the benefits of using AI for data-driven decision-making is that it allows managers to listen to what their data is telling them. AI can alert managers to employee patterns that could highlight anything from a flight risk to an employee’s potential for promotion. Weekly reports generated by AI can also help managers understand the impact of edits they’ve made to the schedule.

Predictive Analytics

Predictive analytics is becoming increasingly important in workforce software, as discussed in a previous article. To recap, by analyzing historical workforce data, AI can predict future staffing needs, allowing organizations to proactively adjust their workforce schedules and plan for future demands. This can help prevent overstaffing, understaffing, and missed opportunities.

For instance, AI can analyze a variety of data streams relevant to your business, such as public holidays, weather patterns, and big events taking place in the vicinity of your outlets in order to create more accurate forecasts. This can help organizations make better decisions on staffing levels, schedule optimization, and resource allocation.

AI can also help businesses take advantage of unusual data streams that may have previously gone unnoticed. For example, data from Google searches can provide valuable insights into employee health trends.

Search trends for keywords such as ‘colds’ and ‘influenza’ have been shown to correlate with the number of sick days taken in certain months; by analyzing this kind of data, AI can anticipate staffing levels throughout the year and allow managers to plan accordingly in response.

AI-Powered Payroll Processing Software

Payroll processing is a complex task that requires a great deal of attention to detail. The manual processing of payroll can be time-consuming and prone to errors, leading to costly mistakes – and this is where AI-based automation solutions can be a game-changer.

By adopting an AI-based payroll management system, organizations can process payroll accurately and much faster. This leads to on-time and error-free payment, which means happy employees. The complex payment requirements of employees, particularly in hybrid, remote, and flexible work environments, can be managed more efficiently using AI-based payroll processing.

AI-based solutions can also help organizations maintain payroll compliance, which is essential for any organization to avoid penalties and litigation. Navigating payroll laws manually can be challenging; however, AI-powered payroll management solutions can easily apply all required rules during payroll calculations, ensuring the necessary tax rates and other items are taken into account. This makes payroll compliance vastly easier for organizations, freeing up time and resources to focus on other important business tasks.

Growing Areas of AI in WFM

Facial Recognition for Attendance Tracking

Some WFM systems use fingerprint scanning when employees clock-in and clock-out. Another option which is not widely used yet is facial recognition. By integrating this technology with time clocks, organizations can rest assured that employees won’t be able to clock in or out on behalf of their colleagues. These systems send automatic alerts to management if there is a discrepancy between the image stored for the employee and the appearance of the individual in front of the camera.

AI Powered Chatbots for Information Sharing

Chatbots are a form of conversational interface that can simulate human conversation. These bots are designed to understand natural language, which means employees can interact with them as they would with a human colleague.

Chatbots can be used to share all kinds of information, from company policies and procedures to employee benefits and work schedules. This makes it easy for employees to ask questions, seek guidance, or access information without having to go through the time-consuming process of manually searching for it or contacting certain personnel.

One of the key benefits of using chatbots for information sharing is that they can provide personalized responses to employees. Chatbots can use machine learning algorithms to analyze employee interactions and learn from them. This allows them to provide customized responses based on an employee’s past interactions, preferences, and work history.

Moreover, chatbots can also be used to automate the onboarding process for new employees. They can provide new employees with all the necessary information about their roles and responsibilities, the company culture, and more.

Combining AI with the Internet of Things

The Internet of Things (IoT) refers to the network of internet-connected devices that are equipped with sensors and software in order to exchange information and perform various tasks. By leveraging IoT technology, organizations have been able to address challenges related to communication, resource management, productivity, and employee satisfaction.

One example of how AI and IoT could transform workforce management is in the retail industry. By leveraging IoT sensors and devices, such as smart shelves, beacons, and cameras, real-time data could be collected on inventory levels, customer behavior, and store traffic. This data could then be analyzed by AI algorithms to provide insights that can help retailers optimize their workforce.

For example, when inventory levels are low, this would allow store managers to schedule staff to restock shelves during off-peak hours. This data could also be used to analyze customer behavior to optimize staffing levels, helping retailers avoid overstaffing during slow periods and understaffing during busy periods.

Real-Time Productivity Monitoring

The ability to monitor employee performance and engagement in real-time is a powerful tool for managers seeking to optimize employee productivity. However, manually monitoring and evaluating these factors can be a time-consuming and challenging task, particularly in larger organizations.

Thankfully, AI-powered solutions can monitor performance in real-time and alert managers about areas for improvement or the need for corrective action in the moment.

For example, if the software identifies a sudden drop in engagement levels among a particular team or department, managers can take immediate action to address the issue, such as offering additional support or resources, adjusting workloads, or providing training and development opportunities.

Personalization and Skills Assessment

AI has transformed the way employee experience is personalized in the workplace. With the help of AI-powered workforce management solutions, employers can offer tailor-made training, coaching, and career development opportunities to individual employees based on their needs and goals. This not only improves their job satisfaction and engagement but also boosts productivity.

With traditional methods of employee management, there are often difficulties in determining the best way to utilize the time and skillsets of multi-skilled employees.

However, predictive analytics powered by AI can analyze employee data and figure out the most efficient way to allocate their time across different workstreams and skill demands. This reduces the chances of miscalculations based on human appraisal of capability and gut decisions.

Skill usage assessment tools in AI-based workforce management solutions can generate the most optimal schedule for individual employees across various workstreams. These tools can also predict future skill requirements, allowing employers to offer relevant training and development programs to employees in order to upskill and keep up with changing industry demands.

By personalizing employee experiences and utilizing their skills optimally, employers can not only attract and retain top talent but also ensure their business remains competitive in the long run.

Revolutionizing Performance Management

AI-based solutions will become incredibly useful when it comes to evaluating employee performance. By analyzing vast datasets, it can provide accurate and unbiased evaluations of performance which are based purely on objective data, making them fair and impartial.

Both managers and employees prefer fair evaluations, as they enable employees to be recognized for their hard work and achievements, while also providing managers with a clearer and more transparent insight into their workforce. This leads to a more just evaluation process, which ultimately leads to higher levels of employee engagement and satisfaction.

Conclusion

In conclusion, the rise of AI is opening up new opportunities for workforce management that were once impossible. It can revolutionize the way workforce management systems operate in future by providing real-time decision support that ultimately improves productivity and profitability.

Currently, AI may be integrated with a workforce management solution through automated scheduling, predictive analytics for various purposes, and payroll management. In future, we are likely to see AI combined with the IoT in order to leverage sensor data that could help optimize demand forecasting. Other growing applications include facial recognition for attendance management, the use of advanced chatbots for information sharing, and various performance management applications.

MANUS WFM is the most experienced provider of enterprise workforce management software in Europe. To discover how our workforce management system can transform your operations, contact us today to book a demo.

How Does Analytics in Workforce Management Software Increase Revenue and Improve Performance?

WFM / 14 Mar 2023

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 workforce management software has integrated analytics features.

Types of Analytics Used in WFM

Predictive Analytics

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.

Prescriptive Analytics

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 Analytics

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.

Accurate Forecasting

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.

Managing Change

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

Legacy Systems

It’s important to use the right workforce management software 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 Silos

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.

Conclusion

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.