Customer satisfaction is one of the most important aspects of any business. Before digital technology entered the scene, customers, in general, were passive consumers, they just bought the product or service. In today's digital world, there are more and more prosumers, active customers that contribute to the production or customization of products or services. Social media has triggered this new approach to how customers interact with companies.
This new reality brings positive and negative effects. When something goes wrong, it can go viral; the same occurs when it goes well. So what does predictive maintenance (PdM) have to do with customer satisfaction and the prosumer? To learn more about predictive maintenance and its importance in the retail industry, continue reading. We'll explain the difference between reactive, preventive, and predictive maintenance and provide examples of the benefits and challenges of predictive maintenance in the retail industry.
Many of you are familiar with reactive and preventive maintenance, but predictive maintenance is a new approach enabling businesses to act on maintenance issues before they occur. You might perceive no difference between preventive and predictive maintenance. Let's look in more detail:
Implementing technology into workflows merging the digital and physical is known as Industry 4.0 and the fourth industrial revolution. In the retail industry online purchasing is the most well-known digital transformation, providing selling capacity 24/7 worldwide. Other significant developments coming from Industry 4.0 reshaping how retailers service products are:
All these new technologies are helping to enrich the customer buying experience and reducing business costs, actioning sustainable processes, and cost-efficiency. But what happens if these solutions aren't working for a determined period? Prosumers will start informing about it via their social media profiles and create a situation where the potential of the retail business' reputation is at risk.
One vital element in digital transformation makes predictive maintenance crucial for the retail industry. The fourth industrial revolution is data-driven throughout the business data management is the key to unlocking the immense potential digital implementation has for retail. Therefore, a digital management solution must offer real-time data assurance and data to information refinement on-premises.
Achieving data control opens vast opportunities and makes predictive maintenance a reality. Consequently, breakdowns are reduced drastically. Predictive maintenance and its importance in retail encompass the whole process, as the retail industry isn't just about selling the product presented in a store or an online shop. Yes, it is the end goal, but there is a vast and complex network continuously moving into digital before reaching the shelves.
When we look at the whole process in the retail industry, various steps are taken before a product reaches the shelves. If we are, talking about food for a supermarket, the starting line begins at the farm; once the product is ready, the supply chain kicks in. Transportation, storage, stocking, and quality assurance are vital for the products to reach the customer in optimum conditions.
Currently, digital adoption is becoming essential for products to be serviced to customers when and where they demand. In addition, prosumers are knowledgeable and will research before purchasing a product or service. In the case of food, digital adoption provides various benefits in terms of information. Embedded systems, sensors, and devices used throughout the cultivation and supply chain ignite a wealth of information for the end user.
Detailed information on product production, precise product location, and time to market; information is ready to access via a simple application, ensuring customers' explicit information. For example, the traceability of coffee beans ensures specific geological and geospatial quality markers. Predictive maintenance helps to maintain this network at optimum levels, reducing costs and finally building trust between retail and prosumers.
Another example where digital adoption is providing benefits for the retail industry is in clothing. The advances VR and AG have, offer customers the possibility of wearing different types of clothing virtually. In addition, retail commerce is growing into digital twins creating VR copies of their shops for customers to roam from the comfort of their homes. The market size of these breakthroughs, known as extended reality (XR) include, augmented reality (AR), virtual reality (VR), and mixed reality (MR), reaching $29.26 billion in 2022. The tendency of the XR market indicates it will reach $100 billion by 2026.
Predictive maintenance is essential to take advantage of the technologies transforming how the retail industry interacts with customers and offers prosumers tailored services and products. To understand the magnitude, let's detail what is, predictive maintenance.
We described the difference between the reactive, preventive, and predictive maintenance options. Predictive maintenance works via monitoring equipment with embedded technology and connectivity. Its exponential growth will continue as AI advances, and the capacity to integrate it into embedded systems is ever-evolving. Another vital groundbreaking breakthrough is Embedded AI on-premises, a solution enabling data storage, processing, analysis, and delivery at the source.
Applying this tech to predictive maintenance ensures data reaches decision-makers in real-time, increasing accuracy. Therefore, services requiring real-time, e.g., VR and AR, must ensure maintenance's bulletproof. As such, monitoring VR and AR equipment with embedded AI alerts decision-makers to actuate, and in some cases, autonomous repairs are possible. In other words, it's a proactive maintenance technique that uses real-time asset data (collected through sensors), historical performance data, and advanced analytics to forecast when asset failure will occur.
There are condition-monitoring technologies to capture the data required to make educated decisions, including:
Adding AI to the equation provides systems the power to analyze equipment conditions in real-time and compare them with gathered historical data. This process guarantees minimum downtime and increases machinery, equipment, and service lifespan. Consequently, customer satisfaction grows as retail' stores workflow is constant and costs are reduced because machinery and equipment maintenance is optimized.
So how does this new approach to maintenance via real-time digital asset monitoring benefit retail in physical and online stores? Here are some of the advantages your retail business and your customers will enjoy:
There are certain issues for PdM in Industry 4.0 to reach its full potential, and these come via the capacity to manage the data generated by condition monitoring. As we have presented, predictive maintenance in the retail industry requires real-time data. Current data management solutions offer centralized services to manage data, i.e., cloud service providers. This means that data generated at the source must travel to server centers to be stored, processed, analyzed, and delivered back to the source.
Centralized data management solutions create risks and vulnerabilities unacceptable for the retail industry to enter Industry 4.0. The challenges that must be tackled for digital transformation to reach its full potential are the following:
If we perceive data traffic as vehicles, we can better understand the problems of latency and bandwidth bottlenecks centralized solutions produce. As data has to travel to server centers, the trip from the source to the data center and back again results in the impossibility to ensure real-time data. Looking at it from the retail perspective, say you have a product produced at a factory once finalized, it has to be moved to another location to be examined, tested, and certified before returning to the factory to be shipped. Implementing this process indicates that products can't be assured to be shipped in real-time as the traveling process comes with risks.
The truck that takes the product to another location takes time; it can also be subject to a puncture or an accident. There might be traffic congestion because of an accident or simply because there are too many vehicles on the road and the infrastructure can't handle the number of cars. The same thing happens with data there's the physical issue; the data center might be thousands of miles away, and the path to reach it isn't a straightforward highway. There are intersections (routers) and data congestions (bandwidth bottlenecks) impeding data to reach the source in real-time. Therefore, wouldn't it be better to offer a solution that kept the data at the source without the need to travel to a remote server farm? We will answer this question further down the road.
Continuing with the example of vehicles being data, moving a truck is not environmentally friendly, it should be reduced as much as possible. Data has the same problem; energy is required, and once it arrives at the data center, even more, is needed. The amount of data being processed, stored, analyzed, and delivered back to the source creates temperature rises in these server farms. To cool the servers in these centers and to do it 24/7, fossil fuels are the only energy supply able to ensure the cooling of these massive data farms. As a result, the current ICT carbon footprint is expected to surpass aviation and shipping's CO2 emissions.
Another significant fact to consider is the programming language used to store, process, analyze, and deliver data generated by the retail industry. There are two programming languages, interpreted and compiled. Studies indicate that interpreted languages are more energy consumers than compiled languages. Going back to the truck, delivering a product using a truck that emits high percentages of CO2 should be avoided at all costs, and use a more efficient truck, if possible an electric truck. Current cloud service providers use interpreted programming languages as they are easier to learn and have mass adoption. This isn't good for the environment, and sustainable computing isn't put into practice.
The internet isn't a safe place. When it was designed, security was an afterthought as the idea of billions of users accessing the net was unimaginable. Therefore, when data travels to data centers the risks and vulnerabilities can be compared to when adventurers began the long and dangerous path from the east of North America to the west or as it was known the Wild West. The Wild Wild West (WWW) in the digital world is the World Wide Web (WWW), where safety is loosely gripped, and cyberattacks are common practice. It is even worse as one point of attack leads to the whole network being taken over.
Imagine if a train was hijacked when going to the Wild West, if it was a digital train the whole network would be hijacked. The only solution would be to pay the ransom to the hijackers to liberate all trains. This is constantly happening in the centralized web-based internet, and the retail industry is submerged in the WWW. It isn't difficult to find examples of cyberattacks in retail. Write in your favorite search engine, “cyberattacks in the retail industry”. To shortcut the answer, here are some retailers that suffered a data breach:
Closely linked to the issues already mentioned, cost-effective data management resides in the need to use solutions on-premises. If the retail industry continues through the centralized data management path to enter Industry 4.0, in the long run, the costs will become budget-breaking. We have to remember that with all the new technologies added to the customer experience data will keep steadily increasing. Therefore, taking the example of a product being data, the number of trucks required to move the product to another site to be analyzed, stored, processed, and delivered, will continue to rise.
To put into perspective how much data is generated and how much data will be generated, here are some daily figures:
By 2025 some estimates predict 463 exabytes will be created globally, this is a lot of data or lots of trucks driving to and fro. The congestion, carbon footprint, risks, vulnerabilities, hijacked trucks, and punctures will rise exponentially. So how can the retail industry leaders overcome these problems? To answer this question, we will respond to the question we presented earlier:
To provide a solution for predictive maintenance to reach its full potential in the coming data-driven fourth industrial revolution; data has to be kept at the source. The benefits of keeping data on-premises are obvious, therefore we need technological innovations designed to offer this service. One of these breakthroughs is edge computing:
Edge computing is offered by major big tech companies serviced as an extension of server centers. Thus, centralized computing is still the base of data management. Consequently, latency and bandwidth bottlenecks, environmentally friendly ecosystems, cybersecurity and data privacy, and cost-effective data management issues aren't fully mitigated.
For a truly well-thought-after edge computing solution to mitigate the problems, there are various technological innovations required:
Internet of Everything Corporation (IoE Corp) has designed a technology solution to overcome the issues presented above. The Eden system gives predictive maintenance the tools required for it to offer the retail industry all its benefits. IoE Corp's Eden is a decentralized software platform using blockchain technology to secure data privacy and ensure cybersecurity via manifests. It uses a knowledge-based AI to be implemented into embedded systems and is quantum-safe and secured using polymorphic encryption keys.
To learn more about IoE Corp's Eden system, read What is Eden? If you'd like to benefit from our groundbreaking solutions to become an industry leader and pioneer Industry 4.0, apply to our Planet Partner Program. We are onboarding new partners with a like-minded vision and mission: to accelerate the promise of technology being a real asset to enhance living standards and help reach the UN's SDGs. Are you ready to embrace the paradigm shift Industry 4.0 brings? Apply to IoE Corp's Planet Partner Program.