The Summer Shutdown – How Advanced Analytics Can Revolutionise Your Store Operations

One of the many good things to come from The Industrial Revolution of the 1820s is the long holidays taken by much of mainland Europe during August each year. Known as the Summer Shutdown, this period of three or four weeks resulted from the historical need to keep factory assembly lines running at full capacity, despite employee holidays. Sending everyone on holiday at the same time made great sense, as it allowed for a full shut down for maintenance and upgrades.

The Summer Shutdown is a tradition that is an essential part of European family life, especially in France, Scandinavia, the Netherlands and Germany, where families take the chance to spend quality time together. But what about the effect on retailers? How do they prepare for the inevitable change in demand and the operational capacity challenges that this three-week break poses?

Meeting the Summer Demand

Meeting demand is complex at the best of times, but during the Summer Shutdown it becomes even more challenging. While many offices enjoy time off to go on holiday, retailers are still expected to provide for the tourist season (albeit with reduced opening hours in many cases). Store managers can often struggle to execute their operational tasks due to a depleted workforce and logistical issues surrounding the delivery and availability of stock.

It might be expected that retail demand would fall during these Summer weeks as holidaymakers head off overseas. In fact, it often remains even. Staycations are becoming ever more popular for those of us living in Europe. Figures from the World Economic Forum show that around 90% of tourist accommodation nights in Europe were people from EU countries and further studies show that 40% of us prefer to stay home during our Summer break.

A recent survey from the Institute of Grocery Distribution (IGD) has indicated that food shopping habits also change during the Summer. People tend to do a larger weekly shop with more regular top-ups. Plus 47% of customers prefer to eat healthier during the Summer months – requiring access to fresh foods. For the grocery sector, the Summer can be a period of increased activity.

Finally, a study by the British Retail Consortium (BRC) and the MET Office (UK) found that changes in temperature are a good indicator of non-food sales growth. In fact, non-food sales are reduced by 1.1% for every 1 degree increase in temperature. However, this is not a permanent impact and will often be balanced by extra spending as it gets cooler.

Capacity Planning Using Analytics

So, for retailers wishing to navigate operational issues during the Summer Shutdown, preparation is key. Advanced predictive analytics tools are some of the best new assets available to the retail sector. They offer the ability to use available store data to predict future outcomes and make strategic decisions based on that information.

Coming under the umbrella term of Artificial Intelligence, predictive analytics uses existing internal data, together with available external data to reliably create outcomes. Information is simply fed into an algorithm that has been designed around the question that needs to be answered. In this case it might be “how will my profit be impacted by reduced staffing levels”. Data on expected weather, tourist numbers, staff gaps and opening hours may be added to previous year’s data to create a prediction of future profit levels. This allows the store manager to make strategic changes to reduce this impact. Best of all, the changes can be tested to see the impact before implementation.

When used in combination with a robust workforce management and task management solution, advanced analytics can be especially powerful. It can easily draw on data that might previously have been stored on several spreadsheets. This information is then reported in a simple and easily understood way. For operations managers, trying to understand the impact of the Summer Shutdown, this can be both time-saving and stress-reducing.

The retail landscape is one that is constantly changing. Predicting and acting on those changes is key to maintaining store operations and ultimately creating more profitable stores.