For a look ahead at the trends that will animate the retail industry this year, let’s take a look back at the 2022 National Retail Federation (NRF) “Big Show” in NYC.

Attendees at January’s event were treated to tangible examples of how retail challenges are being solved today, including new solutions to help them parse customer expectations and buying patterns, adapt stores into omni-channel experience hubs, and improve data visibility and actionability.

NRF 2022 also took the “omni-channel everything” theme of last year’s show to the logical next level: Enabling the best hybrid experiences. The message came through loud and clear of the importance of integration and interoperability in this new hybrid world – making everything work well together.

The need for modern digital infrastructure to enable this blending of physical and digital retail smoothly is paramount. To that end, technology vendors demonstrated how digital transformation initiatives, such as contactless and real time IoT and mobile applications, need to be built on cloud, edge, and secure connectivity to allow retailers to achieve the modern seamless hybrid retail that today’s consumer wants.

Other prominent themes and technologies highlighted at NRF included: extending engagement in the metaverse, sustainability, physical and digital security, and the agility and adaptability imperative.

The Metaverse and Hybrid (Omni-channel) Experiences

Today, the metaverse is an extension of our lives, enhanced by technology, which exists as a series of virtual worlds. In the future, the metaverse will be an interconnected, endless world where digital and physical lives fully converge. Imagine waiting for an appointment at a real booth on the NRF show floor while your avatar roams a fully fleshed-out digital NRF, meeting other virtual attendees, stopping for coffee at the digital Starbucks, and paying for a coffee that an in-the-flesh Starbucks employee brings to them. Digital and physical selves merge seamlessly in the metaverse, as the worlds draw closer together.

In the metaverse, brands have a digital presence, too. Nike filed seven trademarks late last year, including those for “Nike,” “Just Do It,” and its swoosh logo, and posted openings for virtual designer roles, indicating its intent to make and sell virtual branded sneakers and apparel. It subsequently purchased RTFKT Studios, a company that already makes and sells NFTs and digital sneakers. (In one collaboration with teenage artist FEWOCiOUS, the company sold 600 pair/NFTs of sneakers in just six minutes to the tune of more than $3.1 million.)

The metaverse also opens possibilities for gathering data about consumers and product demand. Imagine a sneaker drop in the virtual world. Certain styles of new kicks sell like gangbusters, giving the brand insight into what might sell IRL, intelligence that leads to trend-right production and less inventory headed for markdown or landfills. The metaverse can be a vehicle for more sustainable operations.

The metaverse further bridges the narrowing gap between digital worlds and physical worlds. Most consumers aren’t outfitting an avatar, but they are moving between online and offline and expect retailers to accommodate those hybrid omni-channel journeys seamlessly. Those demands have accelerated around last-mile delivery and experiences such as buying online and picking up in store (BOPIS) or at curbside, shopping in store and returning merchandise online, adding items to a BOPIS purchase when at the store, or communicating a substitution to the third-party grocery delivery service

Hybrid experiences open opportunities to please the consumer in new ways, but they also add expense and complexity. The need to meet this demand while enabling profitability was a major theme behind many of the technologies discussed at NRF. These included artificial intelligence (AI) for recommending the right product, return logistics software for defining and guiding product-specific reverse logistics workflows, order orchestration and fulfillment applications for omni-channel shopping, and last-mile delivery visibility for optimizing customer experience, to name a few. Also on display were task management applications help to improve and optimize in-store employee engagement, as well as touch-free applications to allow for faster payments and customer self-service checkout. RFID continues to improve inventory accuracy and inventory locating on the shelf, throughout the store, and the supply chain.

Sustainability

NRF 2022 saw a strong focus on sustainability. An NRF/IBV study released at the show highlighted the significant embrace of sustainable shopping by consumers. According to the survey, 62% of shoppers are “willing to change their purchasing habits to reduce environmental impacts.” About half indicated a willingness to pay a premium – on average a 70% premium – for sustainable products and brands.

Retailers are working to improve sustainability and reduce carbon footprint across operations by using sustainable sourcing through the supply chain, the store, and even returns. Tech vendors unveiled a variety of solutions enabled by cloud/edge, AI, computer vision, and IoT/RFID to allow retailers to effectively measure and record their environmental efforts, with the goal of reducing their impact.

Several cloud and digital infrastructure providers showcased sustainability clouds and other technology aimed at asset management with the goal of reducing energy consumption, water usage, waste. Examples included using IoT sensors to reduce water usage, optimizing re-use of store assets, and dashboards that allow retailers to accurately monitor and measure carbon output. However, such sustainability solutions can be most successful when running on the next-generation digital infrastructure that helps retailers better compete and differentiate in today’s omni-channel world.

Physical and Digital Security

According to a 2021 NRF survey, 57% of U.S. retailers reported the pandemic led to an increase in organized retail crime, while 50% reported an increase in shoplifting. When IDC’s Future Enterprise Resiliency & Spending Survey, Wave 10 (November 2021) asked retailers which digital infrastructure investments would provide the greatest strategic advantage in 2022, their #1 response was “cybersecurity and recovery investments.”

A wide range of technology vendors acknowledged retailer concerns with regards to security, fraud, and loss prevention:

• Networking, connectivity, and edge vendors highlighted multilayer security solutions that promise to protect data from a range of IoT applications that utilize customer and associate data. Many offer security consulting services to address varied threats including ransomware, retail crime, and loss prevention.
• Security and e-commerce security vendors showcased solutions to prevent fraud and abuse in e-commerce applications as well as omni-channel applications such as BOPIS and curbside pickup, using AI-based analysis for identifying “bad”/risky customers and mitigating risk.
• Cloud vendors highlighted how retail clouds provide consistent, reliable identity management and data security.
• POS/payments/store technology vendors emphasized their ability to handle payments securely from any platform with multifactor tokenization, improved identity techniques such as biometrics and voice authentication, as well as AI-enabled and computer vision solutions for loss prevention at checkout and at the door.

The Agility and Adaptability Imperative

On display at the show were multiple flavors of the digital infrastructure technology that retailers need to achieve agile, personalized, data-driven, integrated seamless operations across the many channels of today’s retail landscape. The emphasis was apt. More than half of retailers plan to boost investment in business agility and operational agility over the next 12 months, according to IDC’s Future Enterprise Resiliency & Spending Survey, Wave 10 (November 2021).

Technology vendors highlighted their connectivity investments to enable business and operational agility and their technology investments for better ease of integration, scalability, and the ability to more easily swap out or mix and match applications with integrated platforms, open systems, hybrid cloud, and retail industry clouds.

Vendors also showed off infrastructure to better harness data while enabling its visibility, maximizing its value, and providing the data-driven personalization essential for competitive advantage and differentiation. Highlights included fast, secure connectivity, 5G and Wifi-6, and edge- and cloud-enabled data and AI platforms to generate real-time insights – all designed to enable today’s omni-channel retail.

Advice for the technology buyer

Retailers should consider these key themes from NRF 2022 when making technology investment decisions for 2022 and beyond. To avoid lagging behind those retailers already moving toward thriving into the future, take action to:

• Enable the seamless, contactless omni-channel approach that today’s consumers want and expect.
• Replace legacy infrastructure that was not built to handle the modern retail environment that requires the agility and adaptability to seamlessly connect rapidly increasing volumes of data securely and more quickly than ever.

Whether sustainability, adaptability, the metaverse, or security are top concerns, addressing business needs holistically and strategically should be job #1.

Continue the conversation by downloading our Transforming retail and CPG markets whitepaper today.

The typical smart factory is said to produce around 5 petabytes of data per week. That’s equivalent to 5 million gigabytes, or roughly 20,000 smartphones.

Managing such vast amounts of data in one facility, let alone a global organization, would be challenging enough. Doing so on the factory floor, in near-real-time, to drive insights, enhancements, and particularly safety, is a big dream for leading manufacturers. And for many, it’s becoming a reality, thanks to the possibilities unlocked with edge computing.

Edge computing brings computation, connectivity, and data closer to where the information is generated, enabling better data control, faster insights, and actions. Taking advantage of edge computing requires the hardware and software to collect, process, and analyze data locally to enable better decisions and improve operations.

At Hannover Messe 2022, Intel and Google Cloud will demonstrate a new technology implementation that combines the latest generation of Intel processors with Google Cloud’s data and AI expertise to optimize production operations from edge to cloud. This proof-of-concept project is powered by the Edge Insights for Industrial platform (EII), an industry-specific platform from Intel; and a pair of Google Cloud solutions: Anthos, Google Cloud’s managed applications platform, and the newly-launched Manufacturing Data Engine.

Edge computing exploits the untapped gold mine of data sitting on-site and is expected to grow rapidly. The Linux Foundation’s “2021 State of the Edge” predicts that by 2025, edge-related devices will produce roughly 90 zettabytes of data. Edge computing can help provide greater data privacy and security, and can accomodate the reduced bandwidth needs between local storage and the cloud.

Imagine a world in which the power of big data and AI-driven data analytics is available at the point where the data is gathered to inform, make, and implement decisions in near real-time.

This could be anywhere on the factory floor, from a welding station to a painting operation or more. Data would be collected by monitoring robotic welders, for example, and analyzed by industrial PCs (IPCs) located at the factory edge. These edge IPCs would detect when the welders are starting to go off spec, predicting increased defect rates even before they appear, and adding preventive maintenance to correct the errors without any direct intervention. Real time, predictive analytics using AI could substantially prevent defects before they happen. Or the same IPCs could use digital cameras for visual inspection to monitor and identify defects in real-time, allowing them to be addressed quickly.

Edge computing has powerful potential applications in assisting with data gathering, processing, storage and analysis in many manufacturing sectors, including automotive, semiconductor and electronics manufacturing, and consumer packaged goods. Whether modeling and analysis is done and stored locally or in the cloud, or is predictive, simultaneous, or lagged, technology providers are aligning to meet these needs. This is the new world of edge computing.

The joint Intel and Google Cloud proof of concept aims to extend the Google Cloud capabilities and solutions to the edge. Intel’s full breadth of industrial solutions, hardware and software, are coming together in this edge-ready solution, encompassing Google Cloud industry-leading tools. The concept shortens the time to insights, streamlining data analytics and AI at the edge.

The Intel-Google Cloud proof of concept demonstrates how manufacturers can gather and analyze data from over 250 factory devices using Manufacturing Connect from Google Cloud, providing a powerful platform to run data ingestion and AI analytics at the edge.

In this demonstration in Hannover, Intel and Google Cloud show how manufacturers can capture time-series data from robotic welders to inspect welding quality and show how predictive analytics can benefit the factory operators. In addition, the video and image data is captured from a factory camera to show how visual inspection can highlight anomalies on plastic chips with model scoring. The demo also features zero-touch device onboarding using FIDO Device Onboard (FDO) to illustrate the ease with which additional computers could be added to the existing Anthos cluster.

By combining Google Cloud’s expertise in data, AI/ML and Intel’s Edge Insight’s for Industrial platform that was optimized to run on Google Anthos, manufacturers can run and manage their containerized applications at the edge, in on-premise data center, or in public clouds using an efficient and secure connection to the Manufacturing Data Engine from Google Cloud. It forges a complete edge-to-cloud solution.

Simplified device onboarding is available using Fido Device Onboard (FDO)—an open IoT protocol that brings fast, secure, and scalable zero-touch onboarding of new IoT devices to the edge. FDO allows factories to easily deploy automation and intelligence in their environment without introducing complexity into their OT infrastructure.

The Intel-Google Cloud implementation can analyze that data using localized Intel or third-party AI and machine learning algorithms. Applications can be layered on the Intel hardware and Anthos ecosystem, allowing customized data monitoring and ingestion, data management and storage, modeling, and analytics. This joint PoC facilitates and support improved decision making and operations, whether automated or triggered by the engineers on the front lines.

Intel collaborates with a vibrant ecosystem of leading hardware partners to develop solutions for the industrial market by using the latest generation of Intel processors. These processors can run data intensive workloads at the edge with ease.

Putting data and AI directly into the hands of manufacturing engineers can improve quality inspection loops, customer satisfaction, and ultimately the bottom line.

The new manufacturing solutions will be demonstrated in person for the first time at Hannover Messe 2022, May 30–June 2, 2022. Visit us at Stand E68, Hall 004, or schedule a meeting for an onsite demonstration with our experts.

Founded in 2006, PaGaLGuY started as a forum that enabled students, typically aged between 20 and 30 to discuss and seek advice on academic issues. By 2011, PaGaLGuY had increased its traffic to about 250,000 page views per month. The business is now one of India’s largest education networks and provides an app that users can download to their Android and iOS devices.

Over the past six years, PaGaLGuY has extended its service to include video advice from experts on education topics and grown the number of views of its pages to 1.5 million per day. As Head of Technology for the business, Sandeep Kalidindi has played a key role in ensuring PaGaLGuY is as engaging as possible to users. “Because the product is advertising based, the greater the user engagement, the greater the advertising revenue,” Kalidindi explains.

Google Cloud Platform Results

• Supported growth to 1.5 million page views per day and demand spikes that see requests increase from about 90 per second to about 1,200 per second
• Reduced API latency from about 1 second to about 40 milliseconds
• Reduced system administration time from three to four days per week to 30 minutes every two weeks

In 2015, PaGaLGuY’s senior management team decided to deliver an even more relevant experience for users of the education network. “The core thing we had to do was personalise the experience for each and every student that visited PaGaLGuY,” Kalidindi says. “So we had to capture each student’s data to customise what they see when they open the site.”

The business also found traffic to the network was straining its infrastructure. During demand peaks, created by exams involving as many as 5 million students, PaGaLGuY would be inaccessible for periods of 30 minutes to one hour. Furthermore, average API latency had climbed to an unacceptable 1 second, compromising performance.

PaGaLGuY needed to access extensive compute resources to undertake its planned change. Had the business relied on a physical technology architecture to undertake the transformation, it would have had to purchase capacity equivalent to 16 new servers. “There was no way with a small team we could grow to that extent in a short time,” Kalidindi says. “This was the right moment for us to explore cloud services.”

The business established two primary requirements the selected cloud service needed to meet. First, PaGaLGuY had to be able to scale the platform with costs rising only in proportion to the increase in resources consumed. Accordingly, the business would have to minimise the number of employees required to manage the cloud environment. Second, the platform had to give PaGaLGuY easy access to student data and the ability to undertake prompt, granular analysis.

PaGaLGuY reviewed available public cloud services and determined that Google Cloud Platform (GCP) was the best fit for its business. “Google Cloud Platform was considerably more mature than the alternatives, with a high degree of automation and a suite of managed services,” Kalidindi says. PaGaLGuY management then discussed with Google how to optimise cost, performance and availability of its personalised education network on GCP.

With assistance from Google and business transformation specialists Searce, PaGaLGuY was able to deliver the platform into production on GCP in 10 months. “Searce was very proactive in ensuring the environment met our needs and allowing us to gain priority access to Google services in development,” Kalidindi says. “Their team was integral to the success of the migration.”

PaGaLGuY has been running in production in GCP for two years. The education network’s GCP architecture comprises a scalable back-end built on Google App Engine; a managed environment for its containerised applications in Google Kubernetes Engine; messaging-oriented middleware through Google Cloud Pub/Sub; a relational database in Google Cloud SQL; a managed data analytics warehouse running in Google BigQuery; stream and batch data processing through Google Cloud Dataflow; and object storage in Google Cloud Storage.

PaGaLGuY has leveraged GCP services to break down its platform application from a monolithic build to a series of microservices running in Google App Engine that enable independent deployment cycles, minimise test and quality assurance overheads and provide clearer monitoring and logging.

Running on GCP has enabled PaGaLGuY to add new personalisation features and grow fourfold without having to add any new engineers or administrators to accommodate the increased traffic. The business has also used the platform to seamlessly collect and aggregate students’ data for analysis, reporting and delivering a more targeted user experience. Furthermore, PaGaLGuY has been able to provide its management team with direct access to Google BigQuery to scrutinise data rather than require them to wait at least a day to view reports created by the product or technology teams.

Support demand peaks of 1,200 requests per second

“Thanks to Google Cloud Platform, we can easily support demand peaks that see requests per second rise from an average 90 per second to about 1,200 per second for as long as 45 minutes,” Kalidindi says. Due to GCP’s scalability, PaGaLGuY can ensure its education network remains available and performance remains consistent during those periods.

Latency cut to 40 milliseconds

The business has also reduced average API latency from 1 second to about 40 milliseconds. Furthermore, using GCP has enabled PaGaLGuY to automate most of its processes and reduce system administration requirements from three to four days a week across its team members to about half an hour per week.

The performance of GCP has transformed PaGaLGuY’s culture and processes. “Once our team was exposed to Google Cloud Platform and understood the superiority of the platform, our mindset changed from ‘let us do everything on our own’ to ‘let us do what we do best’ and delegate the remainder,” Kalidindi says. The quality of the service provided by GCP means PaGaLGuY effectively considers the cloud provider as part of its team. “We are always eager to see what new services are being launched and are extremely excited about what Google Cloud Platform can provide as part of its roadmap.” he concludes.