A lot of people still have an old fashioned view on scheduling. Labour is expensive is a true statement in many countries. But making an optimal schedule is not simply about doing the same things with fewer people. Sometimes is about getting more out of the people we already have.
During one of our projects we have implemented a scheduling tool for a customer with more than 5000 retail stores worldwide spread over 43 countries throughout Europe, Latin America, Middle East and Asia. The entire business case was built out of benefits other than labour cost reduction.
The business case of the project was built on three major goals.
Firstly, the goal was to standardize the scheduling process. Having one standard solution globally is in fact very interesting. Think about the numerous reports which can be used for management; where one can look at a store, a region, a country, a brand and so on.
As a second goal it was set to increase the productivity of the employees. So indeed better using the resources we already have today.
And lastly the aim of the project was to increase the conversion. Conversion is a term often used in retail that measures how much of the traffic (people entering a store) results in an actual sale.
The insights during implementation
First of all, implementing a scheduling tool leads to resistance. Even when the management was convinced labour cost reduction was not a goal and this was clearly communicated. At lower levels in the organisation the fear existed that the tool could reveal inefficiencies and could ultimately lead to job losses. So a first lesson learned is to never forget about the aspect of change.
The second group of insights came from working together with the store managers whom had to validate the schedules. Scheduling with a tool versus gut feeling and Excel has been eye opening both in terms of forecast and in terms of schedule. Some stores turned out to be overstaffed or understaffed – not always in line with the experience or gut feeling of the manager. The same goes for busy times of the week or even the day. Based on the historical POS (point of sales) data the tool makes a forecast of how busy it will be in a store. This is a statistical approach versus a human approach. Humans tend to overestimate the risk that a certain Saturday will be busy or underestimate the amount of traffic on a Monday morning. This is because our memory focuses on the extremes and because we make assumptions based on our own behaviour.
Also in terms of actual schedule the tool comes up with combinations – all within the boundaries of opening hours & labour agreements – after many many iterations. It is but normal that a human head cannot beat a computer so sometimes the store managers were surprised by the outcome and that they never thought of a certain solution themselves.
A third insight is more involvement from upper management. In the past the schedule was considered a store responsibility. Now as it is much easier to report on the schedule from any store, any job, any employee, any time the management has quick & useful insight in metrics such as coverage and effectiveness. It is not only a matter of controlling the store managers and holding them accountable, but also about joint discussions about how to improve the metrics. Management is actually using the tool which is rare in itself. Schedules from other stores can be seen and knowledge shared.
Realising the business case
Of course the involvement of management is not only about the tool, but even more so about the numbers. We are indeed seeing increased conversion rates – in line with what was expected in the business case. At this point in time it is too soon to analyse whether the increased conversion rates are thanks to improved scheduling or thanks to other factors. For this we need to analyse a longer time horizon. But surely having the right number of people when it is busy in the store will likely improve the sales figures indeed with the same staff – so the expectations are high!