The Christmas holiday rush is a critical period for retailers to boost sales, reach profit targets and establish an upwards trajectory for the next 12 months. This year could be one of the best years yet for retailers and its important to make the most of it.
Here in Australia, the interest rate cut and the lower Australian dollar means that Aussie consumers have more disposable income and purchasing online has gotten more expensive. Couple that with last year’s GST imposition on online purchases and the appetite for brick & mortar shopping this Christmas should be at an all-time high.
Physical retailers still maintain a very important competitive advantage over online retailers – the presence of staff and the ability to create amazing experiences for their customers. Like any opportunity in retail, the first point of action lies with your people.
The quality and quantity of staff are essential in creating an excellent customer experience and fostering a positive environment where customers are excited to purchase. The former can be done through high-quality training and well-executed recruitment. The latter is achieved by having the right people in the right place at the right time, leveraging data and insights.
Many retailers use a rule of thumb or store managers to work out how to roster for the Christmas season. This can be dangerous because it results in either over-coverage or under-coverage. Over-coverage leads to unnecessary labour costs, fortunately, the cost of over-coverage is generally limited to the cost of the additional labour.
The bigger opportunity for retailers this Christmas period is in under-coverage. Not having the right people in the right place at the right time leads to poor customer experience, revenue walking out the door and staff that are run off their feet. The total cost of which is a lot more than over-coverage.
Let’s compare the costs of under and over-coverage of two store scenarios, over an 8-hour open period.
Based on our experience of helping retailers address over and under coverage we will take a conservative estimate that the store loses 6 transactions an hour (per employee under) from under-coverage as customers grow frustrated at the lack of customer service, long queue times, stressed staff.
Over twelve months, it isn’t hard to see how undercoverage could cost more than half a million dollars in additional revenue per store that could be gained through addressing undercoverage. For a company with thirty stores, this could lead to potential additional revenue of up to fifteen million dollars.
Unfortunately, there is no golden bullet here. But there are ways you can measure & address over & under-coverage with impressive accuracy. The advancements in algorithms, artificial intelligence and machine learning development for workforce management and optimisation have helped make this possible. Specifically the accuracy and more importantly, scalability of demand forecasting techniques (how many sales will you make) and speed and inclusiveness of algorithms to create the right shift patterns to match people to demand in the most cost-effective and lucrative manner.
Heuristics are a good way to quickly see results in demand forecasting and shift creation, but there are some other downsides as well. It will, for example, not scale well and you'll probably end up with modern whack-a-mole to get the heuristic to give accurate results. Learn more about the technical specifics and what the solution can be.
Are you using rule of thumb rostering techniques to roster for Christmas? This can be dangerous because it results in either over-coverage or under-coverage - leading to unnecessary labour costs, poor customer experience, revenue walking out the door and staff that are run off their feet. Learn more about what you could potentially be losing and gaining.
Each one of your stores, restaurants and/or locations has its own context: different demand drivers, local events and seasonal effects. And they all need their own forecasting method to give you the most accurate results. Hyperlocal forecasting allows you to do that. Read more about the why, how and what of hyperlocal forecasting.