Driving Operational Cost Savings With the Internet of Things

Facilities maintenance has long been overlooked by proponents of the internet of things. That’s changing — and the potential savings for companies that adopt data-based operations management is enormous.

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Internet of Things

IoT research and subsequent fall 2016 report, “Data Sharing and Analytics Drive Success with IoT,” looks at analytics capabilities, the impact of larger IoT projects on diseconomies of scale, and potential security issues that accompany device network growth.
More in this series

For many retailers, facilities management has become a significant part of their customers’ overall brand experience. Based on my experience and recent interviews with a number of store managers and facilities executives at major global retailers, more and more CEOs, chief operating officers, and chief marketing officers are doing spot “walk-throughs” of individual locations, paying close attention to the critical, yet unglamorous, elements of retail. Operations executives are facing scrutiny if anything in renovations, maintenance, or repairs disrupts or denigrates the overall customer experience.

Yet, COOs who typically oversee back-office functions and facilities management often receive much less investment from the boardroom to acquire new digital technologies compared to their CMO and chief technology officer counterparts. This imbalance in where new tech gets allocated continues to exist and is a blind spot for many companies. Leaders who are able to both recognize and rectify this imbalance can reap significant benefits for both customers and the business.

The Complexity of Facilities Management

Of the approximately 5 million commercial buildings in the United States, almost half are part of multilocation enterprises. Data collected from more than 200,000 facilities for over a decade suggests these types of organizations spend an aggregate $100 billion each year on repair and maintenance work predominately completed by an ad-hoc collection of independent contractors at individual locations.

Managing the entire range of multilocation facilities and equipment is a complex task: Buildings and assets are typically decentralized or franchised. To manage this network effectively, retail operations executives and facilities managers need a data-first approach to measure and optimize the overall condition of their stores in the same way marketers strategize product placement within them.

Data Provides a Performance Baseline

Data analysis from more than 200 of our customers on the maintenance spend of their 200,000 facilities over the past 15 years suggests that IoT and AI have the potential to reduce unnecessary facilities maintenance spend by as much as 20% to 25%. Effective data collection and analysis, however, has the potential to assist in the reinvention of what has traditionally been a cumbersome, paper-based process, rife with middlemen and inefficiencies.

We are seeing store operations for major retail brands being graded with key performance indicators (KPIs) that have a greater emphasis on facilities management. Historically, the major metric has been “Are you completing operations on budget?” Today, operations executives at large retailers, specialty stores, and restaurant chains state that their performance includes metrics within the facilities domain, including the percentage of time work has been done on time, by qualified staff, and with accurate billing. A data-driven approach to facilities management powers this measurement, which provides a performance baseline and a benchmark for improvement — both in cost and quality.

Two major retailers — one a leading national health care retailer with nearly 10,000 facilities across the United States, and the other a large, regional operation with hundreds of retailers in the central, western, and northwestern U.S. — have recently used AI-powered technology to maximize their facilities management operations. Each company’s operations team implemented facilities-management software that uses AI to examine thousands of discrete historical repair and maintenance work orders to guide future facilities-management decisions.

In both cases, decisions guided by the software were largely in line with work the operations teams were already doing (for the national retailer, the outcomes were different in just 1% of cases; for the regional retailer, 7%). In both instances, facilities managers continue to make the ultimate decisions on their spend, but are now supported and guided by data, empowering them to measure and justify their results, make modifications that lead to greater efficiencies, and share concrete improvements with executive teams. At the same time, this process provides front-office executives with the ability to guide consistency in decisions going forward and ensure workplace compliance and completion across the entire chain — including the ability to share “brand uptime”-focused KPIs, such as proving store cleaning has occurred in a timely fashion or ensuring specific asset maintenance has happened.

This facilities-management data has empowered each retailer to make better decisions as they acquire new real estate and test new store formats, such as walk-in clinics within other retailers or larger “neighborhood” store concepts. At the same time, each company has seen year-over-year increases in customer-satisfaction results that can be correlated to improved in-store experiences. Additionally, the software incorporates critical data from additional IoT devices as connected assets such as thermostats have been added to their infrastructures.

Facilities management, once seen as a bottom-line necessity, is being measured with top-line methodologies and influencing customer satisfaction ratings. Accordingly, there is an opportunity for COOs to justify increasing investments in technology that will empower this function to manage retail operations more efficiently.


Internet of Things

IoT research and subsequent fall 2016 report, “Data Sharing and Analytics Drive Success with IoT,” looks at analytics capabilities, the impact of larger IoT projects on diseconomies of scale, and potential security issues that accompany device network growth.
More in this series

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