Measuring the distribution and availability of products is the foundation of successful in-store execution. Knowledge is power, but how do we translate this knowledge into quick improvements when and where necessary?
To guarantee optimal in-store execution, field teams are often deployed at points of sale to perform a wide range of activities aimed at improving brand or category performance. The main question is: ‘How can these teams be deployed most effectively?’. There is a lot of room for improving current approaches using two elements: data and flexibility.
Unfortunately, these elements are only rarely utilised. Stores are typically segmented based on criteria such as turnover, store size, and location, and field-team visits are scheduled accordingly. Often, the easiest long-term solution is to create a permanent, cyclical schedule in which field teams are deployed at regular intervals throughout the year. Stores are visited not out of necessity but simply because they are on the schedule, which can result in visits that make little to no impact on store performance.
Just visiting stores should not be your goal. Instead, the goal should be working with stores to maximise the performance of a brand or category. Thus, the most efficient approach is to visit locations where improvement is possible and/or necessary. To determine which store visits will be most effective, both up-to-date information on store execution and good data are crucial.
By combining actual store sales and out-of-stock and distribution data, it is possible to determine expected sales. Comparing expected and actual sales provides insight into ‘lost sales’, also known as Lost Sales Value. Combining these figures with internal logistical data gives an overview of out-of-stock costs and other potentially associated issues, such as discrepancies between store and distribution-center stock. In short, these data points provide a clear view of the potential store-level profit and suggest action points: the data tells you where to go, what to do and what the likely gain from the visit will be.
Flexible data needs a flexible workforce
If this dynamic data becomes the guiding principle for store visits, the workforce should also be dynamic, that is, flexible. A flexible workforce makes it possible to delegate tasks to those employees best suited to accomplishing them.
Depending on the task, you can either send your own field employee or go for another solution, such as flexible resourcing or remote advising via a call center. This guarantees a better allocation of your resources and ensures that you deploy your own people for the tasks that best suit their skillsets, thereby increasing job satisfaction and reducing staff turnover.
The transition to data-driven decisions and flexible resources is a strategic choice that suits the present work climate. Good employees are scarce and therefore expensive, and the demand for flexible work options is growing among both companies and employees. With an ever-expanding range of solutions and increased availability of good data, you have all the ingredients you need to make this strategic choice now.
By Martijn Nijhuis, Cofounder and Ambassador at Roamler.