While the shift to digital business and the cloud has been well under way for some years now, organizations today have a new sense of urgency due to COVID-19. Delivering digital transformation is no longer a ‘nice to have’ option, rather, it is an operational imperative. Taking advantage of the infrastructure, platform and solution gains that cloud and microservices architecture provide is a must for brands today. 

At Google Cloud, we understand the pressures and challenges organizations of all sizes, across all industries are facing. The pandemic has dramatically impacted global commerce at-large, exposing (for many organizations across multiple sectors) gaps in omnichannel capabilities, business continuity and forecasting plans, not to mention spots in supply chain agility, resilience and responsiveness. 

A rapidly evolving consumer-driven commerce landscape has put innovation squarely in the spotlight for supply chain teams all over the world, with the effects of the global pandemic making it increasingly difficult for manufacturers, wholesalers, third party logistics providers and retailers (in particular) to weather the perfect storm of fast-moving consumer trends and a need for ‘always on’ digital innovation. 

These same effects have driven increasing interest and uptake of technology like the Manhattan Active® suite of solutions, as well as our own cloud platform; both of which afford organizations the levels of agility, flexibility and scalability needed to insulate their people, processes and long-term business strategies against unforeseen future obstacles such as global pandemics or international trade disputes.

An excellent example of this agility, flexibility and scalability in action is PVH’s response to the global pandemic. One of the most admired fashion and lifestyle companies with such iconic brands as Calvin Klein, TOMMY HILFIGER, Van Heusen, and IZOD, PVH was forced to temporarily close its physical stores and, as a result, experienced a sudden massive increase in online sales. The retailer was able to quickly pivot by adjusting its business rules in Manhattan Distributed Order Management (part of Manhattan Active Omni) to expose store inventory to online consumers and reroute its fulfillment processes. Thanks to Manhattan’s solution delivered through Google Cloud, in a matter of days, PVH was able to leverage both its distribution centers and vast store network to fulfill its online orders.

“The events of 2020 have accelerated retail and ecommerce operations forward,” said David Herridge, executive vice president of Global Value Chain Technologies for PVH. “With quick, creative thinking and the right partner, we were able to pivot operations, satisfy our customers and prepare for the future.”

Manhattan’s products have been recognized for their ability to solve real-world challenges through innovation, and used by many of the world’s top brands to solve some of their most complex commerce and supply chain challenges: the latest recognition is Manhattan’s position as sole leader in the 2021 Forrester Wave™ for Order Management Solutions. 

Since December 2018, Google Cloud has been collaborating closely with the team at Manhattan and its ‘always on’, versionless approach to innovation. And, during the last two and a half years, Manhattan has significantly accelerated its cloud-first solutions and market adoption, resulting in tremendous growth in its overall cloud business efforts. 

By building cloud native solutions on Google Cloud, the teams at Manhattan continue to deliver the high-performance, elastic, high-redundancy, secure solutions their customers rely on. Moreover, it means both Google Cloud and Manhattan continue to innovate and push the boundaries of what is possible in terms of the supply chain and omnichannel innovations that underpin global commerce – innovation that is needed more now than maybe ever before.

Our commitment to distributed cloud solutions and ongoing innovation, not to mention the fact Google Cloud operates a net carbon-neutral cloud, means that the working partnership between both industry leading teams continues to be a perfect match of brand values; not just from a technology perspective, but also a long-term sustainability and environmental one too.

More information on the partnership can be found here.

About three years ago, JCB, one of the biggest Japanese payment companies, launched a project to develop new high-value services with agility. We set up a policy of starting small from scratch without using the existing system, which we call the concept of “Dejima”, where we focused on improving various aspects such as team structure, risk management, and application and platform development process.

Until now, large Japanese enterprises have built decision-making systems focused on eliminating unnecessary business processes and efficiently increasing quarterly profits. As a result, we are seeing more organizational structures that make it difficult to take on new challenges or experiments with trial and error. We wanted to breathe a new life into this situation, and that is how the concept of Dejima came up. In the Edo period, Japan closed its national border to other countries under its national isolation policy. At the time, Dejima was the only area where special rules were applied and allowed people from different cultures to come and go, and trade. This special rule generated the culture of inclusion and led to Dejima’s prosperity. Like Dejima, we believe that creating an organization that is independent from other business practices can be effective in enabling digital transformation for the organization. 

We have been able to make this transformation with the direct help of the Google Cloud and its products such as Google Kubernetes Engine (GKE), Cloud Spanner and Anthos Service Mesh, applying domain-driven design and microservice architecture. We named this the “JCB Digital Enablement Platform (JDEP),” which now hosts multiple business critical production services.

A key benefit of GKE is that the team can easily add resources and release them when they are finished, allowing them to be flexible to accommodate busy periods and off-seasons. Meanwhile, Anthos Service Mesh helps us manage complex environments easily. With containerization and managed services, we are prepared for the future for when more services go into production, as it would be easy to maintain and provide version upgrade support. At the same time, Cloud Spanner ensures that we maintain a 99.99% availability at all times.

Our initial motivation for introducing SRE practices was to break proverbial walls between business, development and operations, which was a success. Now we are focused on ensuring its reliability and maintaining customer satisfaction with our SRE practices.

To ensure the success of SRE practices that we implemented, there were a few categories we needed to address, from defining the organizational culture and practices to ensuring the policies attached to the new models created were practical enough to be implemented on the ground level. This is so that the Dejima concept remains sustainable for the long run.  

Instilling a culture of measurement 

Here, “appropriate” reliability is the key. According to the conventional way of thinking at JCB, “service failure must not occur” and “SLA should be maintained as high as possible.” We started by discussing what was the “appropriate reliability” that our customers really needed, but it was not as easy as we thought because the level of reliability for user satisfaction differed from application to application. 

Eventually, the business, development and operations teams formulated specific SLIs and SLOs together, something we would never have been able to do if we discussed separately. This is because the business is required to compromise on lower service levels, since our reliability standard used to be too high. The collaboration of development and operations teams is necessary to understand how our system works upon our users’ interactions.

After Google Cloud helped us run a series of workshops where all teams participated, we saw change within the organization. The business team started evangelizing SRE to other members in the business department, and the development and operations teams started collaborating autonomously. We felt like we were working at Google speed, accomplishing so much in a short amount of time. 

Understanding SRE as an entire company is necessary to progress. We are now working on creating internal training materials to spread the SRE concept throughout the company.

Eliminating ambiguity

With the cooperation of Google Cloud, we have created a Team Charter that defines the team’s mission, values and engagement models. We also created policy documents that include Incident Response Policy, Postmortem Policy, On-call Policy, Toil Policy and Error Budget Policy, to eliminate ambiguity in day-to-day operations.

For example, when an incident occurs, we can identify exactly the level of importance, the roles that are assigned to each person, and in what order they need to follow. When to do a postmortem, who owns it? What to do if the error budget is exhausted? How do other teams reach out to SRE when they have problems? The written policy documents will dramatically improve efficiency and motivate teams to adopt a culture of learning from failures.

The format for such policies are written in Google’s SRE book, but when we adopt it, it needs to take into account the circumstances specific to our company. Simply copying an existing policy won’t work, which is why it’s important to formulate a policy that fits the situation each team is in.

Reformalizing teams

Based on these policies, JCB’s SRE team has two sub-teams. One is called Sheriff which works as the platform SRE, and provides infrastructure services for the application team. The other is called the Diplomat which works as the embedded SRE, and participates in the application team to lead productionisation. There is also a team called Architecture that is separate from the SRE teams whose role is to consult SRE on system design and review architecture.

The SRE team was a single role when it was first launched, but now has two sub-teams. This is because as the number of application teams increases, the number of support tasks for the teams also increases, which can result in a shortage of resources to work on overall improvement. Securing people who are not interrupted from day-to-day support tasks and focusing on the main task improves efficiency.

Whereas both sub-teams share the on-call duty, some engineers are not allowed to do it by contract as they are not allowed to get paged. For those who cannot participate in on-call duties, we created what’s called a Toil Shift, which allows them to focus on resolving tickets in our backlogs instead.

This works well so far, but we will keep evolving as our business grows.

Startups need to move quickly and focus their limited resources on areas where they can differentiate. If infrastructure isn’t your differentiator, don’t put a lot of energy into your infrastructure when someone else can do it for you. What’s more, time-to-market matters to startups more now than ever. Successful early stage companies know this, and leverage existing tools, libraries, frameworks and innovations whenever possible.  

Next week Google Cloud will be featured at TechCrunch Disrupt, the iconic annual event where “founders and investors shaping the future of disruptive technology” come together to share stories, network, and learn from each other. Google Cloud will host a session and Google Cloud engineers will be available in a virtual booth to answer startup questions. 

The session, “Demo Derby – How startups are disrupting the status quo with innovative data analytics, AI and modern app development” will be a fun, fast-paced set of presentations showing short demos of startups and startup projects built with Google Cloud. 

Demo Derby Presenters

• Andrea Le Vot, Chief Data Protection Officer with startup BlueZoo will deliver a demo showing how they are revolutionizing the property insurance industry with AI and Cloud – and doing so while actually protecting people’s privacy.
• Dale Markowitz and Zack Akil, Applied AI Engineers, will show how easy it is to use AI for everything from video search to editing to automated translation.
• Vidya Nagarajan, Group Product Manager from Google Cloud will deliver a fast paced demo that shows how startups can drive developer productivity with serverless innovations.

“Disrupt is iconic for its engagement with founders, investors, and the broad community of early stage companies,” said Andrea Le Vot, Chief Data Protection Officer at BlueZoo. “We are thrilled to share our insights with others in our community, and to show how we have partnered with Google Cloud to innovate faster than most of the larger, well funded insurance companies in our market.”

The series of snippet sized demos will be followed by a roundtable discussion with the demo developers focused on lessons learned, best practices, how to reduce time-to-market, and how to focus on where you can most effectively differentiate.

The session will air on Day One of the event: Tuesday September 21, 2021 at 1pm PT and will be available on demand after the event for all Disrupt attendees.

Verve Group is an ecosystem of demand and supply technologies fusing data, media, and technology to deliver results and growth to both advertisers and publishers – no matter the screen or location, no matter who, what, or where a customer is. Classifying massive amounts of this unstructured data at scale is the first step in helping to surface relevant, high-quality content to users—and that’s where natural language processing (NLP) comes in.

Verve Group uses the NLP API from Google Cloud’s Vertex AI to fetch data for their internal content classification quality verification and as an additional source for building categorization models. By leveraging the NLP API’s Content Classification models, which are now generally available and offer Google’s latest large language model (LLM) technology, Verve Group powers classification through an updated and expanded training data set with over 1,000 labels and support for 11 languages (Chinese, French, German, Italian, Japanese, Korean, Portuguese, Russia, Spanish, and Dutch join previously-available English). 

Verve Group has been using Google Cloud’s NLP API since day one, because of both the ease of implementation and the quality compared to competing NLP products. With documentation that is “comprehensive and self-explanatory,” the NLP API “allows for fast adoption and implementation, from test models all the way to production,” said Rami Alanko, GM of Verve Group.

Leveraging the NLP API has facilitated Verve Group’s fast go-to-market motions by enabling its customers to quickly discover and classify new content. “Operating on a global level with tens of different regions and languages, we have still been able to maintain high quality for our product and high retention rates with our clients,” Rami shared. “In a recent client case, we achieved 82% improvement in CTR when optimized with content quality measurements enabled by the API. In another client case, we drove brand safety risk down to 0.16% from 4% thanks to classification quality. Along with the new functionalities of the Google NLP, I can only see this trend continuing to strengthen.”

Verve Group is excited to further expand their NLP use cases by leveraging the new Content Classification models, which have already helped them expand their classification inventory, improve the quality and performance of their quality verification for customers, and unlock new use cases for NLP. “Our classification model accuracy improved 41% using Google NLP as a verification partner,” said Rami.  

Additionally, Verve Group is now using the API for metadata analysis on a  large image database. “We browse the database and run the image metadata via our classification. This flow enables us to classify images reliably aligned with our standard classification.  We pretty much use the same data flow for our runtime in-app textual content analysis, therefore allowing for close to real-time consumer engagement,” Rami added.

To learn more about how companies are leveraging NLP API from Google Cloud Vertex AI, click here, and to learn more about Google Cloud’s work with foundation models and generative AI, read The Prompt on Transform with Google Cloud.

In recent years, the grocery industry has had to shift to facilitate a wider variety of checkout journeys for customers. This has meant ensuring a richer transaction mix, including mobile shopping, online shopping, in-store checkout, cashierless checkout or any combination thereof like buy online, pickup in store (BOPIS).  

What’s more, in the past year and a half alone grocers have had to enable consumers new ways to shop for essentials. This has included needing to rapidly integrate or build on-demand delivery apps, offer curbside pickup with near-instant fulfillment as well as support touchless and cashless checkout experiences. Searches on Google Maps for retailers in the US with curbside pickup options have increased by 9000% since March 2020, and we believe these trends from 2020 will continue to define the future of grocery shopping.

The future of grocery will require agility and openness

Firstly, the need to rapidly adapt to changing consumer habits will be the new normal. Grocers will increasingly look to digitally transform legacy retail systems and modernize point of sale (POS) platforms to deliver and scale omnichannel experiences as quickly as possible. This necessitates a more agile and open architectural approach to technology – one built on microservices and leverages APIs so that new applications and experiences can be built, integrated and delivered faster.

Automation and data-driven retailing will be table stakes

In order for retailers to blend what they’re offering in the store with digital experiences more efficiently, they will also need to automate more. For example, with automation and business intelligence, grocers can take labor that might have been tied up with tender operations and checkout and redistribute those resources to restocking shelves, curbside pick-up or improving customer experiences. 

Automation and access to real-time in-store inventory & supply chain data can also help grocers avoid the supply chain challenges seen in the early days of COVID-19. Grocers will need to find ways to leverage automation to ingest, organize, and analyze data from physical store networks, digital channels, distribution centers to better forecast demand and manage future fluctuations.

How NCR and Google Cloud are helping grocers adapt to disruption with operational agility

Helping grocers improve operational agility to address changing consumer shopping habits and to thrive during times of disruption is something that NCR and Google Cloud have teamed up to do. NCR has over 135 years of experience in retail, having invented the cash register and are continuing to help grocers innovate. NCR Emerald builds upon the company’s leadership in POS software and has turned it into a unified platform that helps grocers operate the entire store from front to back. The solution supports cashier-led checkout, self-checkout, integrated payments, merchandising, and enables regional managers and corporate employees access to the analytics and tools needed to optimize loyalty programs and promotions.

NCR has invested in a comprehensive, agile, and API-led retail architecture that lets grocers continually innovate and design new experiences as customers and the industry evolve. By running Emerald on Google Cloud, NCR can offer the solution on a subscription basis, helping grocers lower upfront capital expenditures and ensuring scalability. What’s more, NCR can tap into Google Cloud’s strength in data, analytics, and openness to deliver three key imperatives. Let’s take a look at each of these below.

Run the way grocers need to while leveraging Google Cloud as a single source of logic

Traditionally the POS system lived in the store. If disaster strikes, people still need access to food and essentials so the grocery store still needs to operate. It hardly gets more mission-critical than that. NCR Emerald is built on microservices, leveraging Kubernetes for front-of-house compute, and VMs (See graphic 1 below). This makes it easy to support lightweight clients accessible by store employees via any range of mobile devices, computer terminals, self-service kiosks, peripheral devices like receipt printers as well as legacy applications.

What’s unique is that because Emerald runs on Google Cloud, it supports all those in-store and digital touchpoints mentioned above, but also allows grocers to run lean. Emerald leverages Google Cloud as a single source of truth and operates a lot of what it does out of logic. Every sales transaction coming from every channel, including e-commerce, can be logged via NCR’s Hosted Service and centralized in BigQuery and Bigtable as a transaction data master. This enables the grocer to manage any transactional use case very consistently, whether it e supporting customers who want to purchase in one store and return in another, offering digital receipts or the ability to exchange online purchases in store. Emerald on Google Cloud can help retailers extend capabilities through the power of the cloud but not need to live exclusively in the cloud. In other words, the solution allows grocers the ability to run the way they need to.

Enable data-driven and real-time decision making for grocers

Store managers, regional managers, category managers, and others all require different cuts of the data to do their jobs effectively. However, data silos persist and how data is formatted and arranged can still remain pretty static. Therefore allowing users with different roles the ability to view and analyze that data quickly and in different ways continues to be a challenge. 

As mentioned above, Emerald leverages Google Cloud data management solutions as the central repository for transactional, behavioral, and merchandising data. Every transaction from every store and every channel can be stored via NCR Hosted Service on BigQuery and Bigtable. NCR Analytics then harnesses the advanced analytical and data visualization capabilities of Looker to help grocers get a consolidated view of their business across all channels and then allow employees to slice and dice the data they way they need to. NCR Analytics also leverages the power of Google Cloud AI and machine learning to add another level of intelligence to the retailer’s data. For example, store managers can visualize how well they’re using their real estate and see how productive lanes 1-3 are compared with 7-10 or compare self-service versus manned lanes. By mapping to the retailer’s own catalog, they can also break down category-level performance and trends.

NCR Analytics takes advantage of Google Cloud’s data pipeline to reduce processing time, with scaling and resource management provided out of the box. By letting the cloud store and process the data, NCR is providing the ability for retailers to analyze their data in near real-time across all platforms – a real game changer in the grocery business.

Open APIs let grocers continually enrich the retail experience

Finally, Emerald is built on an API-first architecture managed through Apigee. It uses the power of Apigee as an open API platform to expose how Emerald can work with other NCR applications like loyalty and promotions, and third party applications like mobile ordering and order delivery to enrich the grocery experience for employees and customers. Every API that Emerald uses is available on Apigee, allowing them to share code samples and giving developers the ability to run scripts. This approach can allow retailers the ability to innovate in a fraction of the time and cost, speeding up 3rd party integrations up front and as businesses grow. 

Take, for example, Northgate Market, a chain of 40 stores in California, that were able to transform its digital operations and enable experiences that set it apart from competitors – quickly and simply with Emerald. It took less than 6 months to go from contract to live deployment in the first store. Since then, Northgate Market has been able to extend their intelligence by leveraging the power of Looker and NCR Analytics.

Learn more about how NCR has been able to leverage an open, cloud-enabled architecture to help customers innovate across the retail, hospitality, and banking industries on the webinar “Role of APIs in Digital Transformation”. You can also learn more about how Northgate uses e-commerce to transform customer experience and gain consumer insights.