In today’s digital world, most enterprises are handling huge volumes of enterprise data. Sifting through it to locate the one nugget of information you need can be so onerous, many managers don’t even try.
They’re already busy coordinating hectic employee time-off requests, making last-minute schedules, sorting out performance reviews, and completing hundreds of other tasks to keep the business running day-to-day.
They simply don’t have time.
To help a company’s data work for — rather than against — them, teams are increasingly turning to artificial intelligence (AI). These systems dive into mountains of data and streamline some of the most time-consuming aspects of workforce management.
The goal is more productive, happier employees — and fewer stressed out managers.
Here’s how technology is making this happen:
1. AI helps managers assess labor demand to recommend the right number of workers.
Most managers are too busy trying to oversee the day-to-day operations of their businesses to devote adequate attention to employee scheduling. As a result, many businesses are plagued by scheduling snafus that directly impact multiple areas of the business.
If you’ve ever worked in the service industry, you know store managers typically schedule employees without much thought.
It’s often based on historical practices or the day of the week. For example, if they typically schedule five cashiers every Monday, they’ll keep scheduling five cashiers every Monday until the end of time.
But when unforeseen circumstances arise, such as a severe thunderstorm, traffic slows and the manager inevitably winds up sending employees home.
Workforce management solutions that use AI, like Ximble, help eliminate this type of situation by examining a range of data points to anticipate future demand. So if it’s Super Bowl Sunday, an AI-based workforce management app would anticipate less traffic, and in turn, schedule fewer employees from the hours of 1:00 to 4:00 PM.
In addition to major sporting events, AI takes other factors into consideration like holidays, events, and promotions, then merges them into a data model that generates a realistic prediction of demand.
Ultimately, these AI-generated recommendations give managers the predictive power to create a schedule that’s balanced, making everyone’s job easier and less stressful.
2. Less guesswork from obscure data means happier and more productive team members.
Efficient scheduling is also crucial for company morale.
A recent study showed that about 70% of staff are actively engaged. This means that 30% are not satisfied, not contributing, or worst of all, actively disengaged.
Every day, managers and planners find themselves in positions where the demands of the business and liquidity of resources make it difficult to manage a balance of efficiency of operation and employee preferences. It’s the area of employee preference and sensitivity that has been voted the biggest challenge in scheduling staff. If an employee travels 30 minutes to work with the expectation that he’s going to make several hundred dollars and work a certain number of hours, and then is sent home because there aren’t enough customers, he’s going to be annoyed.
In fact, some states have a legal requirement that employees be paid for a portion of hours they’re scheduled to work, when they’re sent home before the end of their shift. So in the scenario where the employee is asked to go home early, the business loses money in addition to letting down the employee.
On the flipside, if you’ve only scheduled a few people to work one day and your store becomes unexpectedly busy, your employees will be stressed and irritated. Employees called to come in on short-notice will also be frustrated.
AI helps predict these unexpected events before they occur so last-minute schedule changes are less likely. It helps managers make informed decisions about scheduling and labor demand, so their teams can properly plan their commutes and any activities outside of work.
Employees feel like they’re more in control of their lives — and they’re vastly happier and more productive at work.
When an intelligent model is involved, everyone wins.
3. Improved data management allows for fair decisions about employee performance.
Some areas of workforce management are, by necessity, more subjective than scheduling. Take for example, performance reviews. While employees always hope they’re being assessed fairly, there’s often a high degree of subjectivity at play.
At many companies, employees are left wondering whether they’re truly being evaluated on the quality of their work — or whether personal bias is coming into play.
But AI-generated data reviews can help eliminate subjective bias and facilitate objective decision-making.
When you call AT&T customer support, for example, they often reach out afterwards and ask you to rate your experience with the service agent on a scale of one to ten. If AT&T surveys thousands of customers each year, that’s a lot of data for a manager to parse. It’s not realistic to think they can sift through the data and make an objective decision on each employee’s performance in that scenario.
With an AI-based solution, managers can see this information with a click of a button.
AI technology can also tell a manager how likely an employee is to show up late for work and even generate a score for the employee to be used in an eventual customer evaluation.
While employee performance should still be evaluated holistically, now the manager has reliable and objective data to incorporate — helping to eliminate any perceived bias in the process.
Used as one tool of many, AI can help automate processes to allow businesses to run as smoothly as possible. For managers, this means taking out a lot of the data legwork so they can focus on running companies and helping their teams succeed.