One of my first jobs was working as a bus driver and river guide in Montana. I loaded boats, kayaks, tubes, and paddle boards on trailers and guided customers down the river to enjoy the warm mountain air, soft water currents, and remarkable wildlife. I enjoyed interacting with the customers and providing them with an enjoyable afternoon. When work on the river was slow, my co-workers and I would huddle in a boat hut to enjoy a soda, sports conversation, or even watch a few TV shows while waiting for customers to show. Although this was fine with me (who would mind being paid for chatting about sports and streaming the latest TV shows?), I was certainly not an asset to the company in those moments; in fact, none of us were. The company was losing money each hour when business was slow. And not only because there wasn’t any revenue coming in at those times, but because, on top of it, their payroll expenses were higher than they needed to be.
This is not a unique phenomenon; many companies actually have “huts”. While business may not always be booming, scheduling the right number of employees at the right time will help keep operating costs low and ultimately have an impact on overall business profitability – and avoid “the hut”. Many businesses struggle with finding that balance and are unsure of how to predict increases and decreases in customer demand. For those who are looking to improve their operations but don’t know where to begin, considering software products that apply recent advancements in technology, and specifically artificial intelligence, may be a good starting point. Today, these workforce prediction and employee scheduling products can offer surprisingly accurate and affordable options to forecast demand of service businesses.
If scheduling is planned purposefully, then employees are productive, customers are served in a timely manner, and profitability increases significantly. For businesses with unpredictable customer flow to thrive, scheduling software has become almost a necessity to keep up with the competition – particularly during the recent pandemic, when workflow became even more difficult to predict. So, when everything may seem uncertain, it’s good to at least be certain that your money is going to the right employees at the right time.
Utilizing workload prediction and employee scheduling software will additionally help your team feel valued. A balanced workload results in improved productivity, and employees will feel a sense of purpose and ownership of their tasks. Assigning workload so you have productive rather than overwhelmed employees requires a delicate balance. Demand prediction software can find that sweet spot to best serve your employees, your company, and your customers.
With demand-based schedules not only do profitability and employee engagement increase, but customers are served with more purpose and qualitatively better assistance. Without workload prediction software, customer lines frequently appear seemingly out of nowhere. So, when business suddenly increases and the right number of employees aren’t present, it creates significant frustration for customers. But if your customers feel taken care of, they will turn into happy, loyal customers who will gladly return for service at your business!
Workload demand prediction and employee scheduling utilizing applied AI has just emerged in recent years. The capability to predict demand and assign schedules that meet this demand is nearly an impossible task for a human. However, employing software to aid in the process makes this challenge manageable. So, what are you waiting for? What could be more important than getting a better grip on employee productivity, profitability, and customer satisfaction? Avoid “the hut” by starting to use workload prediction software!
Author: Mark Sherman
Mark has a passion for the hospitality industry and has just completed an internship at Weave Workforce, a technology company applying artificial intelligence to predict and harmonize employee schedules to match the fluctuating demand of service businesses. He is originally from Mesa, AZ, and is currently studying communications at Brigham Young University.
