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Zero Downtime: How Edge Computing and Predictive Maintenance Cuts Down Overhead and Boosts Customer Satisfaction

The foundation for retail and restaurant operations is built on customer satisfaction. But it’s hard to keep customers smiling if the payment terminal is out of order or the digital menu board is blank. Reacting to store maintenance issues diverts staff from serving customers and is often more expensive and time-consuming than expected. However, adopting a “zero downtime” mindset can transform your operations and boost customer satisfaction (and loyalty).

How Predictive Maintenance Transforms Retail and Restaurant Operations

Downtime By The Numbers

In the restaurant segment, maintenance costs are approximately 1.5% of sales, according to the National Restaurant Association. General maintenance expenses are typically 2 – 6% of the overall budget in the retail arena, QSRWeb reported. Overall, retailers spend an average of $5.02 per square foot on store maintenance, including HVAC, according to the Professional Retail Store Maintenance Association

Physical assets represent a significant number on the balance sheet in low-margin businesses like retail and food service. To ensure those assets are earning the best possible return, it’s critical that equipment and services are supporting revenue and the customer experience.

However, given the challenges of labor, rising costs, and increasingly complex technology, many retail operations — including quick-serve restaurants (QSRs) — only react to maintenance problems when they happen, which leads to revenue wasted on avoidable malfunctions.

Reactive Maintenance: An Unsustainable Solution

Reactive maintenance refers to maintenance that is completed as a reaction to a major system or operational breakdown. It’s usually a result of deferred expenditures on regularly scheduled services and ignoring minor issues with the hope that they will go away.

Unfortunately, minor problems often turn into major system failures.

To compound this, facilities management is often decentralized, so there may not be an enterprise-level maintenance strategy, leaving local management to react to outages and breakdowns on the spot rather than proactively working to avoid them. In these instances, expedited customer support and repairs drive up costs and could leave the location without critical services or equipment.

The True Cost of Reactive Maintenance

The desire to cut back on expenses (even critical routine maintenance expenses) is understandable: “Customer volume is often down during trying economic times, so owners and operators have a natural tendency to look for ways to make a little bit go a long way,” Eric Lane, Director of Operations for the School of Hotel, Restaurant and Tourism Management at the University of Denver’s Daniels College of Business, said in QSR Magazine. “But this means they’re often too quick to cut back on preventative maintenance and safety concerns in their efforts for a better bottom line.”

Studies show that every dollar “saved” by deferring maintenance leads to $4 in direct costs on future repairs or replacement. Overall, the total costs can reach as much as 15 times the amount that would have been spent on regular maintenance.

A “Zero Downtime” Strategy

Adopting a proactive maintenance strategy that strives for zero downtime (or as close to zero as possible) can dramatically impact how much time and how many resources are spent on addressing avoidable operational problems. According to the Aberdeen Group, companies that implement a predictive maintenance model:

  • “reduce unplanned downtime by 3.5%,”
  • “reduce maintenance costs by 13%,”
  • and “increase return on assets by 24%.”

So, how can retailers and restaurants easily and efficiently adopt such a strategy? Simple: By incorporating a highly-targeted predictive maintenance solution. The result? Reduced downtime, lowered costs, and satisfied customers. 

Overcoming Downtime With Edge Technology

Edge computing offers a simple solution to modernizing predictive maintenance when included in a zero-downtime strategy, leveraging real-time data from connected devices and IoT sensors to predict when an asset will need intervention in advance of a failure. Even better, Edge computing and connected device-enabled predictive maintenance are achievable with the equipment retailers already have onsite. This approach frees up workers who can then focus on better serving customers and improving the overall customer experience. 

A comprehensive solution can help prioritize response and integrate with a ticket system to facilitate service. Incoming alerts can be triaged in real-time with the appropriate service level. Some problems will be addressed remotely, while others may require a service call, but machine learning will refine the automated monitoring and alert process to optimize the system’s efficiency.

How Maven Wave / Atos Can Help

A zero-downtime maintenance strategy that leverages modern, high-availability Edge technology and IoT-enabled predictive maintenance drives better use of resources by removing troubleshooting and repair from the onsite staff’s responsibility. With service attention occurring exactly when it’s needed, retail and restaurant management don’t have to stress over unexpected (and costly) downtime.

Maven Wave / Atos works with agile retailers by developing cloud-based solutions that help them operate in efficient, sustainable ways. We have worked with retail, QSR, and entertainment companies (i.e., theme parks) in reducing downtime, improving operating efficiencies, and reducing costs using Edge-based solutions that operate with speed and precision.

If you’re interested in learning more about these use cases (or how your organization can adopt a predictive maintenance solution to transform your operations), contact us to schedule a time to meet with our experts.


*This post was co-authored by Manish Verma, Vice President and Client Executive Partner in Retail, Travel & Hospitality at Atos

About the Author

Kylie McKee
Kylie McKee is a Content Marketing Strategist at Maven Wave with more than eight years of tech industry experience and five years of content marketing experience. Prior to joining the Maven Wave team, Kylie worked as a Content Marketing Specialist for WebPT, Inc. and earned an Associate in Applied Science in Motion Picture, Television, and New Media Production with a CCL in Screenwriting from Scottsdale Community College.
February 28th, 2022

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