Shift management is the future of hiring, and this is down to several factors. The emphasis on work-life balance by Millennials and Gen Z workers, who made up roughly 52% of the UK workforce in 2022, as seen by a report from Statista, is one of such determinants. Even if you’re likely to scoff at the figure, the knowledge that the figure is going to increase in the coming years should give you pause. Additionally, these generations are more inclined to switch jobs for opportunities, prioritising schedule flexibility, and better payment. Unsurprisingly, shift management/scheduling software, designed to provide flexible working hours suitable for employers and employees, has surged recently, with its market size valued at 100 Billion US Dollars as of 2023.
Despite its popularity and incredible market share, there continue to be problems with many shift management software in the market, and this has led to much inconvenience and loss for employers and a lack of employment opportunities and pay for willing workers who rely on the apps. This article presents some common issues with the shift management apps in the market, the role of AI and Machine Learning (ML) in fixing them, and how these changes benefit all users of shift management software.
Common Deficiencies of Shift Management Applications
Shift management and its applications are beneficial to users, whether they are employers or employees. Without proper shift planning, many businesses end up with scheduling conflicts that reduce productivity and lead to issues like overstaffing or understaffing a shift, inability to track their employees’ working hours, and additional expenses due to such inabilities. Employees, in their own vein, also suffer because they become more likely to be overworked and underpaid.
Many employers have attempted to solve shift planning problems manually, some even using lengthy spreadsheets to track employee schedules. However, this can quickly get tedious, especially in a growing organisation. Shift management software addresses these issues in a way that is convenient for everyone involved. Sadly, this is not always the case; while there are numerous shift planning apps in the market, many of them tend to have the following issues:
Little to No Customisation
Due to the evolution of the workplace in modern times, it is common to see organisations with a remote or even hybrid workforce, some of which are across multiple time zones. Yet, many shift management software is generic and lacks the features to adapt to these organisations’ unique needs. When applications are rigid or too standardised to fit only one form of the workforce, it can lead to frustration, inefficiencies, and a poor user experience. Hence, it is always beneficial when flexible applications recognize the evolving workforce during software design.
Poor Integration Capabilities
Shift management software must integrate with other systems in an organisation to be truly effective. For example, an organisation may need an application to work with their payroll, billing, time, and CRM & HRIS systems. Integration issues can even become more problematic if the organisation uses outdated systems, leading to mishaps and delays when the corporation tries to work with the software. While it may take extra effort, software developers must ensure that their shift management applications work well with the existing systems of most organisations.
Cost of Subscription
Many workplace scheduling software are expensive to use, and that can be tracked down to the habit of developers overloading their applications with many features. There is an instinct of ‘The more, the merrier’ with many software engineers not considering that many of the features are either unnecessary or overly complicated. However, when the software only possesses features that address the pain points of its core audience, such as shift planning, forecasting, scheduling, and automation, it becomes much more relevant and affordable.
Recent Trends in Shift Management Software
Fortunately, several new trends have emerged in the shift management software market to address issues that have plagued these applications for some while. Some of the new trends in recent apps include:
Support for Flexible Schedules
Since work-life balance is becoming increasingly important, many users (employees and employers) will seek shift management software that supports work flexibility. Some of these features include:
- Shift Swapping allows one to swap shifts with another co-worker when faced with an unexpected situation.
- Self-scheduling allows employees to schedule themselves within the parameters that the employers set.
The good thing about these features is that they not only benefit the employees by giving them more control of their time but also benefit the employers who get workers who are more motivated and productive in the shifts they do come in.
Improved Communication Features
Clear and constant communication between employer/supervisor and employees is vital for effective shift coordination in shift management. Such communication also has the added advantage of increasing employee productivity by as much as 25%, according to a McKinsey Report. One major feature includes In-App Messaging, which allows employers and employees to easily contact each other through the app without having to go through the hassle of looking up emails and phone numbers.
Artificial Intelligence and Machine Learning
Shift management software has incorporated new technology as a way to give users more resources and flexibility in scheduling. One of the most important technologies used is artificial intelligence and machine learning in streamlining and automating the scheduling process in these applications.
The Role of Machine Learning and Artificial Intelligence in Shift Management
Artificial Intelligence and Machine Learning have been around for a while, though their usage has recently expanded; that expansion has been extended into how shift management software is now being designed. The entire aim of AI and ML incorporation is to optimise organisation scheduling further. With AI and ML incorporation, shift management applications can do the following:
Predicting Staffing Needs
Many shift management software that utilise AI and ML often possess advanced algorithms that analyse and, in time, accurately predict staffing or staff needs. This analysis includes important variables such as historical data, seasonal fluctuations, and past staffing patterns. This new ability drastically reduces the problem of overstaffing and understaffing by enabling the employer to anticipate staffing requirements at all points. Armed with this knowledge, they can efficiently allocate resources and save costs; this would have been significantly more difficult in a manual system.
Smart Scheduling
Labour costs can cause considerable expense for businesses, and poor scheduling systems can exacerbate this. Poor scheduling can lead to overtime payments and clashes with labour regulations, which can drive up company costs. AI models can often analyse intricate data like employee skills, availability, and labour laws and use that information to schedule employees to reduce overtime costs, schedule conflicts, and improve labour compliance.
Intelligent Matching
Employers have observed employees do their best work when work schedules align with their preferences and life commitments. As the algorithm consistently learns about employee preferences and behaviour over an extended time, it becomes adept at matching them appropriately. This benefits employers who experience less turnover because of a more productive and satisfied workforce that feels like their needs are being met by their employers.
Streamlined Schedule Updates and Modifications
Incorporating Artificial Intelligence into shift management software has increased the ability to automate processes. With AI-powered platforms, employees can simply update their colleagues and employers on changes in the schedule, such as cancellations, modifications, or swaps. This ease of notification can lead to smooth coordination in the business.
Continuous Learning of Patterns
One of the most important aspects of machine learning is the potential for continuous improvement. This means that the software’s algorithm would always constantly learn from new data and adapt to the changes in business patterns and employee behaviour. Additionally, ML systems become more accurate over time and more skilled in meeting business and employee needs.
What This Means for the Shift Management Software Market in Coming Years
The continuous development and incorporation of AI and Machine Learning in shift management software will make it more important in management in the coming years. With these AI-powered software, employers and supervisors rely more on them to become better managers of their workforce. Using the unique capabilities of these apps, such as the analytics of employee history, trends, and even weather forecasts in employee vicinity, they will more accurately predict potential staff deficiencies. This new prediction power grant supervisors an increased agility in management, as it enables them to react faster and better to changes in scheduling
On the other hand, employees will get more flexibility with a tool that constantly learns, adapts, and anticipates their needs. This will go a long way in reducing friction between them and their bosses and making collaboration with colleagues and supervisors easier.
Shift management software will also set the tone of communication in the workforce in the future. Many apps have already incorporated in-messaging which has greatly facilitated the accessibility of workers, colleagues, and their employers. With new additions like generative AI, now seen in models such as GPT, exchange of information between employees, fellow workmates, and their employers will become even more efficient. Those who struggle for words will have what they need suggested for them, breaking down another communication barrier that has plagued organisations for years.
Conclusion
Not many people will argue that AI and Machine Learning is the future, though what that future will be is in a state of dispute. Still, it is undeniable that their incorporation into shift management software has altered the landscape of what was previously expected of them.
AI and ML models’ algorithms take in vast amounts of data which make them highly predictive of variables like employee history, trends, and preferences. All of which make them important to the employee who seeks job flexibility and the employer who wants adequate staff presence in all shifts. As they become better, the AI software market will continue to surge (as it has already shown signs of doing) while these applications will become more indispensable in organisations.
Author Bio:
Sylvia Nkeiruka-Anthony Ezennaya is a leading voice in the digital technology space. Her company, Rubis Services, specialises in bringing about unique innovations in the homecare and personal care sectors across Africa.
She is currently building a waitlist for her innovative shift management Application via https://www.tickettailor.com/events/shiftmaster1/1301892
