NCR's Emerald Leverages Google Cloud to Help Grocers Boost Operational Agility - Build What's Next
Blog

NCR’s Emerald Leverages Google Cloud to Help Grocers Boost Operational Agility

8245

Of your peers have already read this article.

3:00 Minutes

The most insightful time you'll spend today!

NCR and Google Cloud team up to transform grocers' legacy retail systems and drive operational agility to cater to their consumers' evolved shopping habits. The NCR Emerald platform leverages Google Cloud's scalability and helps grocers curb Capex.

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 emerald.jpg

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.

ncr retail solution.jpg

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.

looker dashboard.jpg

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.

E-book

Google Research: Cutting-edge of Marketing Trends

DOWNLOAD E-BOOK

3481

Of your peers have already downloaded this article

15:15 Minutes

The most insightful time you'll spend today!

Today’s business leaders face more challenges than ever, in a world that is evolving rapidly, that is hyper-connected, and that is data-driven.

As the pace of change intensifies, marketers have come under immense pressure to demonstrate value and to lead their organizations through this new landscape.

This is particularly pronounced in Asia, home to many of the world’s fastest-growing economies. Innovations in e-commerce, online payments, and communications are driving new business models and shifts in consumer behavior both here and around the globe.

Now, more than ever, strong consumer insights are essential in order to succeed. We are surrounded by signals that can help decode how behavior will change in the coming years.

Marketers who invest in detecting and developing these signals will stay ahead of the curve. In today’s world, opportunity and growth lie at the intersection of data and foresight.

This thought-leadership study showcases newly-breaking trends, examples of what companies are doing now, stories of how emergent leaders are pushing the boundaries, and what the future could hold.

The study covers:

  • Cutting-edge trends including Shoppingmas, Retailarity, Leisuressence, Part-time Preneurs, and Mindful Impact
  • The implications for CMOs and businesses
  • How to use data and machine learning to prepare

Download Now: A Peek Into Your Consumer’s Future

Blog

OCR Engine Upgrade: Document AI Introduces 3 New Capabilities

2491

Of your peers have already read this article.

2:30 Minutes

The most insightful time you'll spend today!

Document AI has announced the addition of three new capabilities to its OCR engine, significantly improving its performance and accuracy. In this blog post, we'll explore these exciting new features and how they'll benefit users of the OCR engine.

Documents are indispensable parts of our professional and personal lives. They give us crucial insights that help us become more efficient, that organize and optimize information, and that even help us to stay competitive. But as documents become increasingly complex, and as the variety of document types continues to expand, it has become increasingly challenging for people and businesses to sift through the ocean of bits and bytes in order to extract actionable insights.

This is where Google Cloud’s Document AI comes in. It is a unified, AI-powered suite for understanding and organizing documents. Document AI consists of Document AI Workbench (state-of-the-art custom ML platform), Document AI Warehouse (managed service with document storage and analytics capabilities), and a rich set of pre-trained document processors. Underpinning these services is the ability to extract text accurately from various types of documents with a world-class Document Optical Character Recognition (OCR) engine.


Google Cloud’s Document AI OCR takes an unstructured document as input and extracts text and layout (e.g., paragraphs, lines, etc.) from the document. Covering over 200 languages, Document AI OCR is powered by state-of-the-art machine learning models developed by Google Cloud and Google Research teams.

Today, we are pleased to announce three new OCR features in Public Preview that can further enhance your document processing workflows.

1. Assess page-level quality of documents with Intelligent Document Quality (IDQ)

With Document AI OCR, Google Cloud customers and partners can programmatically extract key document characteristics – word frequency distributions, relative positioning of line items, dominant language of the input document, etc. – as critical inputs to their downstream business logic. Today, we are adding another important document assessment signal to this toolbox: Intelligent Document Quality (IDQ) scores.

IDQ provides page-level quality metrics in the following eight dimensions:

  1. Blurriness
  2. Level of optical noise
  3. Darkness
  4. Faintness
  5. Presence of smaller-than-usual fonts
  6. Document getting cut off
  7. Text spans getting cut off
  8. Glares due to lighting conditions

Being able to discern the optical quality of documents helps assess which documents must be processed differently based on their quality, making the overall document processing pipeline more efficient. For example, Gary Lewis, Managing Director of lending and deposit solutions at Jack Henry, noted, “Google’s Document AI technology, enriched with Intelligent Document Quality (IDQ) signals, will help businesses to automate the data capture of invoices and payments when sending to our factoring customers for purchasing. This creates internal efficiencies, reduces risk for the factor/lender, and gets financing into the hands of cash-constrained businesses quickly.”

Overall, document quality metrics pave the way for more intelligent routing of documents for downstream analytics. The reference workflow below uses document quality scores to split and classify documents before sending them to either the pre-built Form Parser (in the case of high document quality) or a Custom Document Extractor trained specifically on lower-quality datasets.

2. Process digital PDF documents with confidence with built-in digital PDF support

The PDF format is popular in various business applications such as procurement (invoices, purchase orders), lending (W-2 forms, paystubs), and contracts (leasing or mortgage agreements). PDF documents can be image-based (e.g., a scanned driver’s license) or digital, where you can hover over, highlight, and copy/paste embedded text in a PDF document the same way as you interact with a text file such as Google Doc or Microsoft Word.

We are happy to announce digital PDF support in Document AI OCR. The digital PDF feature extracts text and symbols exactly as they appear in the source documents, therefore making our OCR engine highly performant in complex visual scenarios such as rotated texts, extreme font sizes and/or styles, or partially hidden text.

Discussing the importance and prevalence of PDF documents in banking and finance (e.g., bank statements, mortgage agreements, etc.), Ritesh Biswas, Director, Google Cloud Practice at PwC, said, “The Document AI OCR solution from Google Cloud, especially its support for digital PDF input formats, has enabled PwC to bring digital transformation to the global financial services industry.”

3. “Freeze” model characteristics with OCR versioning

As a fully managed cloud-based service, Document AI OCR regularly upgrades the underlying AI/ML models to maintain its world-class accuracy across over 200 languages and scripts. These model upgrades, while providing new features and enhancements, may occasionally lead to changes in OCR behavior compared to an earlier version.

Today, we are launching OCR versioning, which enables users to pin to a historical OCR model behavior. The “frozen” model versions, in turn, give our customers and partners peace of mind, ensuring consistent OCR behavior. For industries with rigorous compliance requirements, this update also helps maintain the same model version, thus minimizing the need and effort to recertify stacks between releases. According to Jaga Kathirvel, Senior Principal Architect at Mr. Cooper, “Having consistent OCR behavior is mission-critical to our business workflows. We value Google Cloud’s OCR versioning capability that enables our products to pin to a specific OCR version for an extended period of time.”

With OCR versioning, you have the full flexibility to select the versioning option that best fits your business needs.

Getting Started on Document AI OCR

Learn more about the new OCR features and tutorials in the Document AI Documentation or try it directly in your browser (no coding required). For more details on what’s new with Document AI, don’t forget to check out our breakout session from Google Cloud Next 2022.

2395

Of your peers have already watched this video.

1:40 Minutes

The most insightful time you'll spend today!

Case Study

Ulta Beauty: Transforming the Beauty Industry with Digital Technology and Google Cloud

As the largest U.S. beauty retailer with more than 1,200 stores across all 50 states, guests flock to Ulta Beauty for its impressive selection of beauty favorites. Ulta Beauty revolutionized the shopping experience by bringing all things beauty, all in one place. It’s enhancing the beauty experience again with technology to personalize product recommendations and try on makeup virtually. Using Google Cloud, Ulta Beauty unified its data strategy to better curate and analyze data to provide industry-leading guest experiences.

Visit cloud.google.com for more!

Blog

How AI and Analytics in EdTech are Living Upto the Hype

4865

Of your peers have already read this article.

1:30 Minutes

The most insightful time you'll spend today!

EdTech platforms saw a staggering growth in 2020, driving their markers to compete on content, personalization and security for continued adoption. With AI and analytics, they can transform online learning, and boost its accessibility and experience.

Over the last year, COVID-19 presented unforeseen challenges for practically every type of business and organization—including schools, colleges, and universities. For educational institutions, the pandemic was an unapologetic agent of acceleration, shifting one billion learners from in-person to online learning within two months. 

The rapid transition to online learning exposed many schools’ lack of readiness for the new online learning environment. It also widened the learning equity gap for students, with fewer than 40% of students from low-income families having access to the tools required for remote learning.

For those who do have online access, today’s students expect everything from engaging and collaborative digital learning experiences to skills-based training for their roles in the future workforce. Expectations are also high for 24×7 multi-channel tech support across all learning devices, applications, and platforms.  

In these remarkable times, education technology companies have an important role to play in supporting academic institutions and students. Indeed, this is already happening, as the EdTech (Educational Technology) market is nearly tripling, with total global expenditures expected to reach $404 billion by 2025. However, the success of these EdTech companies depends on their performance in a number of areas, including:

  • Content and products: How quickly can they generate new content and react to learner needs with new products to additional markets for broader adoption?
  • Personalization: How effectively can they leverage artificial intelligence (AI) to provide a personalized experience to all types of learners?
  • Trust and security: How trusted and secure are their services when educational organizations are suffering the highest number of data breaches since 2005?

Here are a few examples of how EdTech companies are successfully using AI and analytics to capture this opportunity and transform their businesses:

  • Build better products: iSchoolConnect is an online platform that lets students explore schools, courses, and countries where they might study, and makes higher education admissions accessible to students around the globe. The company leverages AI services to help educational institutions optimize their academic operations by accelerating admission processing by greater than 90%, while saving significant costs.
  • Launch in new markets faster: Classroom creativity tools provider Book Creator uses AI APIs to enhance accessibility and improve the learner experience. “The broad suite of intelligent APIs enables us to deliver richer experiences, faster and more easily, without having to be experts in machine learning, drawing recognition, map embeds, or other areas,” says VP of engineering Thom Leggett.
  • Scale businesses securely: Using DevOps and CDN [content delivery network] services, Chrome browser recording extension creator Screencastify was able to support eight times growth in users overnight amid the COVID-19 pandemic, while maintaining consistent total cost of ownership. These technologies helped the company rapidly scale operations in response to the overnight increase in demand from consumers and assure student data privacy and security on a budget. “We know this is just the beginning, as more educators rely on technology to deliver richer, more interactive curricula to students,” says CEO James Francis. 
  • Provide personalized learning and support: Smart analytics and AI can provide personalized support and recommendations for students, forecast demand, and predict shifts in learners’ preferences. Online learning platform Mindvalley uses cloud-based tools to understand and make decisions based on user activity and leverage machine learning to predict behavior. 

Google Cloud is partnering with many of these leading EdTech companies, as well as industry-leading consortiums like Ed-Fi and Unizin, to standardize educational common data models and best practices for more agile and cost-effective integration of EdTech into existing environments.

The education landscape is changing rapidly, and EdTech has a major role to play as institutions adapt to the massive shift in learners’ preferences and expectations. We’re committed to empowering EdTech companies with the tools and services they need to help expand learning for everyone, anywhere. 

Watch our Spotlight session with EdTechX to learn more.

3015

Of your peers have already watched this video.

18:00 Minutes

The most insightful time you'll spend today!

Explainer

Driving Business Transformation in Financial Services Using Google Cloud and AI/ML

These are challenging times with financial services institutions navigating the pandemic.

Interest rates are an all-time low, and customer expectations are changing with the shift to digital. For example, digital banking has increased from 63 in 2019 to 72 percent today. Then regulatory requirements are evolving and compliance costs are increasing. Also, the financial services industry as a whole is facing new and creative types of fraud.

In this video, Tom Shane, Product Manager – Google Cloud and Michael Baldwin, Head of Product – Financial Services, Google Cloud – Google Cloud, uncover three areas where they see AI helping to unlock business transformation in financial services.

Find out how AI can help reimagine the customer experience, how financial institutions are looking for ways to use data and analytics to transform how they detect and manage risk, and how financial institutions are asking Google Cloud experts for a best-in-class AI platforms so that they can build their own AI-powered solutions to solve their most critical business problems.

More Relevant Stories for Your Company

How-to

How Machine Learning Can Cut Support Ticket Resolution Time By Over 80%

Sure, machine learning is becoming a business imperative, but how does it work in practice—and what are the benefits for IT managers? That’s the subject of a new step-by-step guide to solving business and IT problems with artificial intelligence and ML, based on insights gathered by IDG Research Services. Its

Blog

Google Cloud’s Recommendation AI Helps Bazaarvoice with 60 Percent increase in CTR

Not long ago, building AI into recommendation engines was a daunting, expensive task that could take years to get off the ground. But as Bazaarvoice has shown, with the help of cloud services, the time from AI investment to business outcomes is shorter than ever.  Bazaarvoice is the leading provider

Case Study

How 20th Century Fox Uses Machine Learning to Gauge the Financial Performance of a Movie

Success in the movie industry relies on a studio’s ability to attract moviegoers—but that’s sometimes easier said than done. Moviegoers are a diverse group, with a wide variety of interests and preferences. Historically, movie studios have relied heavily on experience when deciding to invest in a particular script—but this can

Case Study

Google Cloud Platform Gives Us 5x the Processing Power to Analyze Physician Performance at 75% Lower Cost

Patients about to undergo a healthcare procedure understandably want the best medical professionals they can get. But how can they know which doctors have had the most experience and the best outcomes with that particular procedure? How can they make an informed decision about which doctor to select when the

SHOW MORE STORIES