Energy and Operational Efficiencies Retailers May Be Missing Out On
Excess energy consumption in retail can exceed 30%, which means there is a huge opportunity for savings that many retailers s have not yet fully explored.
Retailers spend nearly $20 billion annually on energy expenses, according to the U.S. Environmental Protection Agency. By saving just 15% from optimizing operations and eliminating waste, we can save $3 billion as an industry.
The SBA (Small Business Administration) says that a 10% reduction in energy costs for the average full-line discount retailer can boost net profit margins by as much as 1.55% and sales per square foot by $25.
“A retailer’s energy costs could represent 5.5% of its store’s operating costs. If the store operates at a 4% profit margin, driving a 15% reduction in energy costs would increase its profit margin to 4.75% — an 18.7% increase in store profit,” according to Adam Siegel, VP of sustainability and retail, Retail Industry Leaders Association.
Forward-thinking retail chains such as Walmart, Kohl’s, and The North Face to name a few are accepting energy as a strategic asset. And, as such, they are finding ways use energy consumption data to gain visibility into the performance of systems. By tracking, monitoring, and benchmarking every energy-consuming device within their operations, these retailers are alerted to operational efficiencies that save time and money.
Missing out on operational efficiencies means that a retail chain may be missing out on ways to deliver uncompromised products and services in a cost-effective manner. In other words, you may be paying too much or wasting too much. There could be a more cost-effective way to conduct your operations.
According to the American Society of Heating, Refrigerating and Air-Conditioning Engineers, “energy costs are typically the second-highest operating expense for a retailer.” For this reason, operational efficiency often comes when energy waste and inefficiencies are eliminated.
Operational efficiencies retailers may be missing out on
• Lighting and HVAC systems shutting down after hours. (Or, to that effect – pretty much anything that operates after hours.)
Retail chains and distribution centers often operate their energy-consuming systems such as lighting, HVAC, and refrigeration on automatic systems that are set to power down after hours.
These systems are great at controlling devices, but they often lack the ability to monitor in real-time. That is, it may be weeks before anyone notices.
*Automation settings have been overridden:
• If scheduling is not input properly
• If there is a bug in the automation system
To put an end to these kinds of operational inefficiencies requires total visibility into resource consumption. The solution is incorporating a system that not only controls the energy-consuming systems and devices throughout the retail chain, but also monitors the devices and alerts managers to inconsistencies or anomalies.
• Optimization of maintenance schedules: Use Big Data analytics and the information gathered by monitoring the energy usage profiles of devices to create a predictive maintenance program, delivering maintenance only when maintenance is truly needed.
Being able to better predict when something will fail, based on data, is a more efficient way to decide the most cost-effective time to perform maintenance work. This reduces expensive downtime and ensures that equipment receives service to avoid impending failure.
Predictive maintenance has economical, budgetary, and scheduling advantages that contribute to a more efficient operation.
• Discovering of over-consumption, idling or underconsumption: Poorly-functioning systems waste energy.
In large retail chains, there is often a visibility problem. Managers at corporate headquarters have no idea if an HVAC air handler at a faraway distribution center is over cycling and wasting energy — and money.
However, large retail chains also have an opportunity in that they can benchmark similar systems and locations against each other and automatically be alerted when something is amiss.
These alerts, when delivered in real-time present a real-time opportunity to correct inefficiencies.
Drive behavioral change
Sure, we can automate and monitor devices, track and benchmark systems, update schedules and force equipment to turn off at closing time. But people are only human, and we cannot change their wasteful behaviors, right? Wrong!
Many companies are finding innovative ways to use real-time data to instill new priorities in the corporate culture. By giving personnel access to information about how their behavior contributes to energy and operational efficiency, they empower their people to make a difference. Adding elements of gamification and celebrating employees’ successful contributions to operational efficiency can also drive behavioral change that propels profits.
* Having a data-driven dashboard for decisions.
Having a single energy management system of record for all devices, systems, and locations is an operational efficiency on its own accord. One central hub that monitors, benchmarks, alerts, and provides insights for process improvement saves management resources. By having access to this information in real-time, retail managers can react quickly and use data to drive decisions. The combination of speed and information results in the ability to minimize unnecessary cost, optimize operations, and increase profits.
How to find operational efficiencies
Certainly, if you knew that some of your locations were running cooling and heating systems concurrently, you would know how to correct the problem and save energy. The true challenge for retail chains is in the ability to detect the inefficiencies.
When we have problems with loss prevention, we install cameras to gain visibility into what is going on at each location. Similarly, to detect operational inefficiencies, we also need visibility. Naturally, this kind of visibility cannot be gained by installing cameras to watch our systems. Instead, we use the Internet-of-Things to track electrical current sensors that report on each device’s operation and efficiency.
What cameras are to loss-prevention, electrical current sensors are to energy efficiency. They provide the visibility to take quick and assertive action against those systems and inefficiencies that are stealing a company’s bottom line.
Yaniv Vardi is CEO at Panoramic Power, a provider of device level energy management solutions. Yaniv is a seasoned executive with close to two decades of leadership experience in the Enterprise Software Solution Industry.
Veteran grocery merchandiser joins Meijer
Meijer is adding a new senior leader to its merchandising organization with more than 30 years of grocery experience.
Meijer has named Tod Pepin as the retailer’s senior VP of Foods.
“We are extremely pleased to have a leader like Tod join our organization,” Peter Whitsett, executive VP of merchandising for the Grand Rapids, Michigan-based supercenter chain, said. “His successful career within a family-owned business will make him a great cultural fit at Meijer, while his years of experience in key categories such as grocery and fresh will allow him to make a positive impact very quickly within our organization.”
Pepin comes to Meijer after nearly 30 years at family-owned Hanneford Bros. Supermarkets. Pepin began his career at Hanneford as a store team member and held a variety of roles in store operations, supply chain, and merchandising, culminating with his role as senior VP of merchandising.
Most recently, Pepin held the role of senior VP of merchandising governance, Private Brands and Business Planning for Delhaize America.
U.S. leads the world in retail shrink
Dishonest employees and shoplifters pushed shrink rates to record levels and earned the United States the distinction of leading the world in the least desirable of retail metrics.
According to retailers surveyed for the Global Retail Theft Barometer, shrink rose in the U.S. from 1.28% of sales in 2013-2014 to 1.97% during 2014-2015. Globally, this compares to 1.42% , a figure also up from the previous .94% average of all common retailers surveyed the previous year.
Retailers expressed that a range of factors, including a challenging retail environment, caused them to implement austerity measures resulting in a reduction of loss prevention investments. This, combined with areas of high unemployment and limited tools to monitor internal theft and inventory discrepancies, all contributed to an increase in their shrink.
According to the report, the annual cost of shrink to U.S. shoppers, as absorbed or passed on from retailers, averaged $615 per household. The study, underwritten by an independent grant from Checkpoint Systems Inc., was carried out during 2014-2015 by The Smart Cube and Ernie Deyle, a retail loss prevention analyst. It was based upon in-depth phone and written survey interviews conducted in 24 countries among more than 200 retailers representing nearly $1 trillion in sales during 2014-2015.
“This is our fourteenth year of supporting what continues to be the industry’s only global statistical research,” said Per Levin, president of merchandise availability solutions, Checkpoint Systems. “To combat increased shrink, retailers are adopting strategies to approach losses from a wider perspective from all levels within the organization and work with their supplier and solutions partners. With the right technologies, people and processes, they can achieve improved merchandise availability, which directly impacts shoppers’ satisfaction and retailers’ profitability.”
Seasonally, U.S. respondents said that 46% of their yearly losses occurred in winter, nearly twice as much as the next season, autumn, at 24%. Spring (18%) and summer (12%) followed. In fact, while shoplifting is the biggest cause of retail shrink in 18 of the 24 countries surveyed, in the U.S., employee theft ranked first at 45%, with shoplifting next at 36%.
Shoplifting continues to plague the retail industry due to escalating problem of organized retail crime, easy sales of stolen merchandise through online sites, reduced investments in loss prevention tools and resources, and the general perception of shoplifting as a "low-risk/non-offensive” crime.
Shoplifters and dishonest employees in the U.S. primarily targeted small and easy-to-conceal items such as liquor, mobile accessories, batteries, fashion accessories and razor blades, as well as high-value items with high resale value, such as tablets. When sorted by retail vertical, the most stolen items included footwear, batteries, mobile device accessories, wines and liquor, and razor blades.
According to Deyle: “This year’s results highlight the persistent factors that impact shrink and ultimately reduce retailers’ profitability. Even if retailers are paying more attention to all aspects of the problem, without a strong investment in loss prevention tactics, tools and resources, they won’t get the results they’d expect. Our hope is that this report helps the industry better understand all the complexities of the shrink problem as well as the most cost-effective ways of addressing it.”