How does the TimeSkipper platform help chains and points of sale prepare for seasons, open a new store or Drive-in, gain market share from a competitor that has closed for a certain period of time, prepare a budget, or adjust hours to a store’s workload?
The essence of a store’s activity is to offer the customer a high-quality buying experience, welcome and service. To achieve this, it is absolutely necessary to ensure the optimal organisation of a team’s work. By this we mean the capacity to coordinate the various tasks which evolve according to the volume of parcels or customers anticipated (customers passing through the checkout, services and sales advice as appropriate) as well as recurring management tasks (orders, store management, etc.).
This is why it is essential to not only anticipate and simulate the workload, but also to manage it at D-1 and in real time.
Firstly, you need to know how to calculate the quantity of future work from the data linked to the number and type of tasks and, secondly, how to determine the size of the teams to cover this workload. It means always having the right number of staff, in the right place, and at the right time, in order to deliver good customer service based on fluctuations in the activity, while maintaining the store’s profitability.
And that is the difficult part!
In view of the organisation and teams in place, how do you allocate the right number of people to a reduction or increase in volumes? How do you decide whether to reassign the tasks when a reduction or increase in workload is anticipated? At what point do you decide to hire or not replace staff? How do you assess whether or not it is appropriate to postpone tasks?
A real issue, the answer to which can be found in forecasting, simulating and managing the workload in store.
REMEMBER
Five business scenarios which rely on forecasting the workload:
– Anticipating seasonal effects: to effectively cover the additional workload and anticipate end-of-season decreases so as to maintain profitability.
– Exploiting opportunities related to the temporary closure of a competitor: in order to build new customer loyalty and gain market share, by ensuring a high quality of service.
– Opening or enlarging a store: to estimate the right number of working hours to cover the activity of the new store or of the additional surface area, taking into account the gradual increase in workload and by controlling costs.
– Establishing a Drive-in: to estimate the number of orders and calculate the preparation time, in order to allocate a sufficient number of employees to them.
– Preparing a budget: to calculate the number of hours needed to generate the turnover forecast and deduce the number of staff to allocate to this.
Workload management tool: as the workload/capacity equation is continually changing, the management tool allows for the optimal and fair allocation of resources to the activity in real time.
Synergy between simulation and management of the activity: the simulation and management of the activity enables continuous improvement ensuring performance quality in store and ensuring a workload forecast that is increasingly reliable.
I-1. Anticipating seasonal effects through forecasting the workload
Let’s take the example of a DIY store. During high season, the point of sale welcomes more customers to the sales area, offers more products (garden furniture, barbecues, etc.) and the teams are required to manage additional activities such as organising seasonal sections. In the case of a food store located in a tourist area, high season means planning for additional activity of the teams, linked to the increase in permanent product volumes and the inclusion of seasonal lines. In all cases, the workload increases.
The TimeSkipper solution makes it possible to assess during the period the change in future product volumes linked to the increase in turnover, or the change in selling hours. From the organisation of the teams in place and by taking into account their holiday, the tool generates task schedules by week, by day and by individual. It then needs to be established at what point – i.e. which week, which day and for how long – it is necessary to cover an additional workload. The result is the ability to assign the right number of staff to cover the additional workload.
Thus, two phases of the seasonal effect are determined:
1-Forecasting the increase in workload in order to identify at what point additional staff are needed to maintain the quality of the welcome, service and running of the store. For the upcoming season, this involves adding X people per day, depending on hours, in order to optimise employees’ working time, taking into account their holiday, and best serve customers.
2- Forecasting the reduction in workload in order to identify when to part with those on temporary contracts in a way that does not jeopardise profitability for the end of season.
I-2. Simulating the workload to help build the loyalty of new customers related to the temporary closure of a competitor
If a competitor’s store within a catchment area has to close for a certain period of time, due to works for example, it is crucial to anticipate the transfer of customers in order to seize the opportunity to gain market share. To that end, organisation must be perfect to attract and then build the loyalty of potential customers. One action to anticipate may involve increasing the number of hours allocated to welcoming and advising customers to ensure an optimal service.
In this case, from the data available, the TimeSkipper platform integrates assumptions on changes in the number of additional customers and sales and then analyses the impact on the business. Therefore, by simulating the workload, we can determine which types of tasks and which additional activities need to be carried out to make the store more attractive, build the loyalty of new customers and of course, gain market share.
I-3. Simulating the workload involved in opening or enlarging a store
In the case of enlarging or opening a store, the forecast is made based on several areas:
- Calculating the additional volume of activity generated by enlarging the point of sale
- Adjusting the number of and reallocating staff according to their skills
- Forecasting recruitment with ad hoc skills to cover the additional workload.
To simulate needs for when a new store opens, a comparable store in terms of surface area and type of customer needs to be identified within the chain. This point of sale is the organisational pivot on which the TimeSkipper solution is based to simulate activity for the new store.
In other words, depending on the number of employees and on what each of them does during the day in the reference store, the tool is able to determine the right number of working hours and skills necessary to cover the new store’s activity as and when the workload increases.
This simulation can determine the number of staff with which to start the activity and, as needed, the number of people to hire to cope with the increase in workload … ensuring the welcome, quality and services without staff costs necessarily rocketing from the start.
I-4. Predicting the workload volume to anticipate the opening of a Drive-in
The question to ask is as follows: “Based on the number of orders expected, what is the work volume generated, how should staff be allocated to prepare the orders anticipated, and is there room for manoeuvre?”
Although it is important to predict the actual volume of work, it is just as important to allow for some flexibility in order to be able to react swiftly in case of spikes in orders and therefore an increased workload for preparation activities.
The TimeSkipper solution calculates and predicts the work volume before comparing the workload with the teams’ projected hours day by day. The objective being to ensure that there is sufficient preparation capacity to satisfy customers and to be able to offer other slots if necessary.
I-5. Correctly simulating the workload for a meaningful budget forecast
Faced with a target turnover, the major challenge is being able to calculate the number of work hours needed to achieve it.
When preparing the budget, TimeSkipper’s strength is being able to anticipate the workload of each individual by day and by week, with the team in place and organisation already modelled as well as future developments.
Thus, it is possible to determine exactly how many people must be allocated by activity, section, etc. by modelling the organisation of the future store.
I-6. Adapting the teams’ hours to the workload
We can go further and provide both an operational and legal dimension to the simulation, by predicting the working hours based on the workload calculated.
Within an off-the-peg clothes store for example, there are various types of tasks to be planned, knowing that they all contribute to an impeccable customer experience. Whether it involves welcoming customers on their arrival or advising them, filling the shelves with products, being available for customers in the changing rooms or finalising the purchase at the checkout, it is essential to have a good view of where sales assistants are, in order to allocate them to the various areas when necessary, and to keep them occupied the rest of the time.
As the workload forecast is also refined beforehand by simulating various scenarios, it is possible to adjust the working hours in advance. Thus, the store is able to give the best welcome and sales advice to customers, the encounter goes smoothly, and the conversion rate improves.
Simulating the workload therefore makes it possible to plan and determine the size of teams in order to cover the activity.
But what about the day-to-day management of operations?
II- Transition in management mode of the workload at D-1 and in real time
Managing the workload opens the door to an operational perspective on a day-to-day basis, within which the workload/capacity equation is continuously changing. The constant fluctuation in volumes, unexpected absences, the uncertainty of some factors such as the weather mean that the data from the field is continually changing.
The management tool therefore enables the day-to-day management of the activity:
- at D-1 the workload is divided evenly and fairly across the teams that are present;
- on the day itself, the allocation of resources is adapted in real time to changes in the workload (peaks or reductions in activity) and unforeseeable events, based on the latest information integrated.
From an operational point of view, this ability to react by making, for example, certain employees available for the areas that need them, checking the proper performance of all the tasks according to data updates, or optimising the work rate at the last minute, greatly increases efficiency and prevents the loss of money.
III – Simulating the workload and managing the activity: a synergy against a backdrop of continuous improvement
With the workload management tool, the teams’ activity can be recorded from day to day. Its analysis and return in the form of dashboards is a mine of quantitative and qualitative information which did not exist before. In addition, it can calculate the value of savings linked to the hours gained.
The data in these reports is a solid base for more aggregated forecasts, which feed the simulation tool. The simulation tool then calculates a new workload based on assumptions of changes in activity. On this basis, the teams’ size is determined taking into account legal and staff constraints.
Finally, the hours and the number of employees are again sent to the activity management tool with greater precision. And so on … the perfect example of ultra-effective synergy!
Finally, to manage means having accurate data that is as close to reality as possible and developing the ability to forecast. Mutually enriching the other through the simulation tool, the forecast and management of the workload provides the ability to allocate the right people to the right place, at the right time with enough staff. To that end, they are essential organisational pillars for retail chains, but also the best vehicles to guarantee quality and customer satisfaction … as well as to maintain the profitability of points of sale.
With their expected knowhow on machine learning and the development of advanced algorithms for external data, the TimeSkipper teams support you in implementing their platform and your continuous improvement strategy: your decisions are forecast and appropriately adjusted, and the efficiency and quality of your organisation improves.