Are you using big data to plan your staff rota?

30 May 2018

With average labour costs across the restaurant and pub sector accounting for 28.8% of revenues1, making more accurate predictions about staff resourcing requirements can make a big difference to the bottom line.

Additionally, the average length of employee service in the sector is reported to be 392 days1 and with training and onboarding likely taking days or weeks, retaining high-quality staff over the long-term is critical for hospitality outlets’ success.

But how can data analytics be used to better forecast resourcing and demand for your restaurant?

Reactive to proactive

Historically, staff schedules were determined when the employee started a role, and the overall staff rota is often the same week in week out, apart from notable exceptions during Christmas and holiday seasons when peak demand forces a change in schedules.

This has led to staff forecasting being a reactive activity. At the end of the week or day, a report is compiled and managers make decisions for the following week about how many employees they might need to cover shifts.

Yet, for companies with big overtime wage bills, reviewing your overtime position at the end of the week is often too late – the decision needs to happen when overtime is actually occurring in order to have an impact on overtime costs.

Relying on real-time access to data gives managers the ability to see on a Wednesday that they are already on track to go over their overtime budget, and thus make changes on Thursday, Friday and Saturday to reduce the impact by scaling back hours or moving staff around. It’s about transitioning towards a more proactive monitoring of staff schedules, and also layering that information over with info related to external trends; such as industry events or weather forecasts.

Organisations are now starting to use big data to look at how busy they were this time last year, analyse whether they had too many or too few staff to cover the demand and make more accurate decisions about how many staff they are likely to need in the future. They are using tools, such as Verteda’s workforce management software, Vantage, to receive alerts when overtime budgets are about to overrun or report on staff schedules in real-time.

Making data flexible and accessible

Managers, today, want access to data in a flexible way, receiving updates on their phone or tablet, with visual data representations of their staff, wage costs and predicted customer demand so that they can make more accurate decisions in real-time about how they manage and resource their shifts for the day.

They want to receive updates about whether a staff member has flagged that they can’t come into work through push notifications, and be able to search via an intuitive app-like interface for other potential staff members who have the right skills, have flagged that they are interested in taking on more work, and are located nearby to come in at short notice. The alternative is struggling short-staffed through a shift or looking through staff records one by one to find someone who could fit the bill. With data and mobile devices, this is the type of info we need at our fingertips to make decisions when it matters.

And that’s the point, this sector is fairly unique in that decisions need to be made on the fly. If you can see customers queueing out the door because you released a new menu offer half an hour ago, then you need to be able to quickly bring in more staff to cope with the increased demand. Likewise, if it looks like it’s going to be an unusually quiet day, then you need to be able to quickly change shifts around to ensure staff aren’t hanging around bored and costing you money.

This provides a better service to the customer and also helps to reduce staff churn as they are brought in to work when they are needed and kept up to date in real-time about demand and potential for extra shifts.

The case for annualised hours

One thing I’m seeing more of in the industry which could be a way to better handle staff resourcing and demand is annualised hours for staff. Instead of committing to a 40 hour week, some staff are instead taking on a core set of hours across a year, for example, 1500 core hours, with another 400 flexible hours should demand require it.

This means that some staff might only work 20 hours a week during quiet periods, but then work 6 shifts during busy periods. To ensure they don’t face penalties when it comes to trying to get a mortgage by not having a regular work schedule, they receive a set salary each month (say based on 30 hours a week work), but their work pattern might vary within that month.

Staff get the benefit of a better work-life balance by spending time at home when they might not have much to do at work, and employers get the flexibility to bring staff in during busy periods without the cost of having staff in the workplace when they don’t have enough work to do. It’s also more secure than a zero-hours contract for staff.

Moving towards a data-led resourcing environment

In the past, managers have relied on anecdotal or purely historical evidence to figure out future staff schedules, i.e. it will be busier over Christmas so we’ll have 1.5 x normal resource for 6 weeks over the Christmas period. Now, they can use data to make more informed decisions based on combined historical and real-time insights, and use technology to engage more fluidly with staff about schedules and work updates.


Find out more about Verteda’s workforce management and staff scheduling solution, Vantage.