Using Analytics to Optimize Operational Efficiency
Over the past few years, retailers have taken on operational optimization initiatives across their network of stores with the goal of reducing costs by squeezing labor budgets. This often leads to poor customer service and demotivated store employees. Instead, the focus should be on making stores more efficient by taking a holistic view of the enterprise and finding the correct balance between the twin objectives of retail profit and customer satisfaction.
Store Operation Issues
The list of unexpected events that can negatively impact the best-laid retail plans is endless. They can range from unexpected customer traffic due to an external event to product recalls on a popular product. These surprise events diminish store productivity leading to poor customer experience and low store associate productivity.
Unplanned events need to be dealt with in real time. But unfortunately, many incidents and surprises require the store manager to interact with a transactional “system of record” which is accessed on a back office computer. This often requires the best store resources to leave the sales floor. The store associates need a system that can be accessed from the sales floor, has concise information, and is actionable and easy to understand. A mobile interface that displays exceptions and key performance metrics, coupled with recommended best practice actions, helps store managers and associates make quick and profitable decisions and enhance the customer experience.
Usage of Analytics
An ideal system uses all the data from the store’s technology ecosystem, analyzes it, and provides in-the-moment coaching to drive best-practice actions. Retailers should ensure that the following aspects are carefully considered:
- Predictive Analysis: The solution should capture micro data across systems and perform predictive analytics to ensure the right planning of end-to-end store operations. For example, to optimize store labor efficiency, the solution captures store personnel data, including their in-store and omni-channel tasks and activities. This data is then further processed through predictive analytics, leading to a more optimized labor schedule.
- Streaming Analytics: This new age solution helps analyze streaming data from the Internet of Things (IoT) in real time and assists store personnel to take immediate action in case of unexpected events. The solution notifies associates in real time, if a key promotional item is selling out at a fast pace and requires immediate replenishment.
- Real Time Alerts and Actions: The solution must provide real-time store execution on mobile devices with the ability to receive alerts and assign best practice actions and update store-facing systems, even those systems that are not inherently mobile-enabled.
- Intelligent Interface & Role-Based Task Management: The solution should offer a simple way to manage store labor and activities along with exceptions to monitor and control the day-to-day functioning of the store. This feature helps drive consistent store execution of corporate initiatives such as sales promotions while ensuring store employees respond the right way to surprises.
- Mobility: With today’s omni-channel penetration into brick and mortar stores, the out-of-the box solution must have a smart mobility element. The mobile-based solution should be a mandate so that managers are not chained to a desk in the back office, but rather out on the store floor helping customers.
Reflexis enables retailers to execute strategy flawlessly and uncover profit. The Reflexis platform includes real-time store execution, task management, compliance, time and attendance, and labor scheduling. Learn more at http://reflexisnew.wpengine.com/
From understanding customers to providing a cohesive experience across channels, retail leaders choose Cognizant to help them work better and work differently. Cognizant’s Retail practice helps retailers turn today’s pain points into new business opportunities. Learn more at https://www.cognizant.com/retail