How Digital Simulation of Physical Stores Helped e-Commerce Companies Replenish Stocks and Fulfil Online Orders at Scale in 2020 - Build What's Next
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How Digital Simulation of Physical Stores Helped e-Commerce Companies Replenish Stocks and Fulfil Online Orders at Scale in 2020

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Trax Retail Watch Powered by Google Cloud uses computer vision (CV) and AI to create digital simulations of the stores for e-Commerce firms to provide real-time updates on the stocks to improve in-self availability. Read how!

Editor’s note: We’re inviting partners from across our retail ecosystem to share stories, best practices, and tips and tricks on how they are helping retailers transform during a time that has seen tremendous change. The original version of this blog was published by Trax Retail in October 2021. Please enjoy this updated entry from our partner.

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Image source: Trax Retail

In 2020, we saw a massive leap in online grocery. Within a few weeks, the industry reached numbers that were unexpected for at least four more years. In a snap, what seemed like a relatively insignificant channel became one that grocery retailers simply couldn’t ignore and, what’s more, is likely to remain a norm.

Retailers trying to stay ahead of the curve have already started experimenting with methods like building warehouses and installing robots to fulfill the growing demand, but in-store picking has been and will continue to remain one of the primary methods of fulfilling online orders as it offers several advantages. First, it allows the use of existing infrastructure – large retailers already have geographically well-located outlets in major cities, which enables shorter lead time to delivery. Secondly, it allows retailers to stay flexible and move swiftly between in-store and online order fulfillment. And finally, it fits perfectly with the omnichannel approach to allow customers to shop wherever and however they want – click and collect, curbside pick-up, or inside brick-and-mortar stores.

How improving on-shelf availability helps ecommerce profitability

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Image source: Trax Retail

Despite its many advantages, in-store picking is expensive and affects profitability in an already competitive space since the cost of picking is directly tied with hourly labor fees. Moreover, with labor being a major challenge to obtain and retain, every minute spent picking counts. However, there is an easy way to keep costs down – optimizing the picking process by ensuring product availability and reducing the need for substitution.

An average of 8% of products are not available on-shelf in stores at any given time. As a result, pickers waste much of their time hunting for products that simply aren’t on the shelf or are misplaced, or spend time looking for substitutes, further increasing the time and cost for picking. In fact, grocery pickers often claim that out-of-stock (OOS) occurrences are the main reason that slows down the picking process. Without these factors, pick rates could be two times faster. Since picking accounts for 50% of the fulfillment cost, it has a substantial impact on the order’s bottom line and often makes the difference between a loss-making and a profitable basket.

Maintaining on-shelf availability for the thousands of products in every store has always been a significant problem to solve. The shift to online ordering has made the availability issue even more significant as the shelf is also now the fulfillment center for the majority of online orders. For e-commerce, out of stocks present two major issues for retailers. First, the impact of out-of-stock items is even more noticeable for online shoppers as they do not select their own substitutions. Additionally, out-of-stocks cause inefficiencies in the item fulfillment process, which is already a costly and margin-diluting practice for retailers. The good news is that through a partnership between Trax and Google Cloud, and the power of Google Cloud’s AI/ML capabilities, these challenges are addressed. The granular, real-time data at scale to enable picking efficiency and the data transparency to unlock a better shopping experience are now a reality which benefits both shoppers and store associates.

Trax and Google Cloud technology helps the bottom line

Trax and Google Cloud offer solutions that can help retailers improve on-shelf availability (OSA). Trax Retail Watch powered by Google Cloud uses computer vision (CV) and AI to create a digital version of the physical store in real-time and informs out-of-stocks so that retailers always have full visibility of items that are running low and can replenish them quickly. In turn, pickers are more likely to find everything they need quickly without facing the problem of missing products or having to look for substitutes. Trax Retail Watch also allows store associates to quickly spot any issues arising on shelves without having to physically walk down each aisle. From misplaced products to low stock, having full visibility means that shelf managers make more informed decisions, so that pickers face fewer obstacles, are aware of the true inventory, and significantly improve their pick rates. Faster picking means lower costs and ultimately, higher margins for online grocery orders.

With more e-commerce retailers crowding the online space, competition is tough. Want to know how frustrated e-commerce shoppers are about on-shelf availability? Trax uncovered this problem through an in-depth consumer study. Learn how to address shopper happiness while driving more profitable fulfillment and stay on the leaderboard with this Trax and Google Cloud whitepaper: Winning the online grocery race.

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How AI is Revolutionizing Retail: Lessons for Marketers

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How can AI help you target customers who are looking for products like yours?
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Case Study

Manipal Group: Delivering High-Quality Patient Care with Google Cloud

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Manipal Group of Hospitals deployed a mobile application that automates nurse rostering, reducing personnel requirements, costs, and stress on nurses and freeing up senior nurses for more valuable tasks.

One of India’s best-known healthcare brands, Manipal Group prides itself on clinical excellence and a patient-centric approach. From humble beginnings in 1953 as a single teaching hospital—the Kasturba Medical College—in a university town in Karnataka, India, Manipal Group has grown to a presence in seven cities in India and operations in Malaysia and Nigeria. “Our founder, Dr T. M. A. Pai, established Kasturba Medical College just six years after India gained independence,” says C. G. Muthana, Chief Operating Officer, Teaching Hospitals, Manipal Health Enterprises Pvt. Ltd, part of Manipal Group.

Manipal Health Enterprises Pvt. Ltd operates 11 corporate, or for-profit, hospitals and five teaching hospitals. “We have about 7,000 beds India-wide, and on that measure, we are the third-largest private-sector healthcare provider in India today,” says Muthana. The organization now employs about 6,000 people in its corporate hospitals and 5,000 people in its teaching hospitals.

Manipal Health Enterprises Pvt. Ltd acquires and operates world-class medical technologies in its teaching and corporate hospitals. However, with 75% of corporate hospital wards allocated to fee-paying private patients—compared to just 25% of the wards in teaching hospitals—the differences in information technology budgets are significant. “In the general wards that comprise most of the wards in teaching hospitals, patients are typically treated for free or at heavily subsidized rates,” explains Muthana. “So revenues and costs of delivery vary between hospitals, while employee costs remain similar.”

Rostering nurses a critical task

Rostering nurses to work shifts is one of the most important tasks at Manipal Group corporate and teaching hospitals. As at all hospitals, nurses administer medications, monitor patients, maintain records, manage intravenous lines, and work with doctors to heal patients. They can also provide advice and support to patients and loved ones, including teaching them how to administer medication outside a hospital setting. If too few nurses are rostered for a particular shift, the quality of patient care may suffer.

Google Cloud results

  • Enabled the hospital to correctly size its nursing workforce
  • Lowers stress on nurses by delivering more equitable rostering
  • Presents opportunity to better manage nurses’ leave and other administration tasks

However, rostering at the group’s hospitals was a time-consuming exercise. Senior nurses on each ward would have to spend up to 45 minutes per day manually amending paper-based rosters to accommodate requested changes to duty shifts for personal or other circumstances. The organization began receiving complaints from patients, doctors, and other hospital staff that, on occasion, too few nurses were rostered on for certain shifts—particularly at its flagship hospital in Bangalore. “We had based our rostering calculations on the number of beds occupied by patients and, when we investigated, we found at a macro level, we were rostering on the correct number of nurses,” says Muthana. “However, on some days, on wards optimally staffed by, say, 10 nurses per shift, we might have 14 nurses rostered on for one shift and seven rostered on for another shift. Those times we had seven, we had a clear shortage.”

In 2012, Muthana asked a consultant to develop algorithms to help automate the rostering. “Unfortunately, there were so many variables, the consultant failed to solve the problem,” he says. The Chief Operating Officer’s next step was to ask the founder and Chief Executive Officer of predictive analytics business Retigence Technologies—already working with the business on a materials management project—to develop an application to manage rostering.

Removing the daily drudgery

“Our plan with the automation project was to relieve our senior nurses of the daily drudgery of amending the rosters and to deliver rosters that were as fair as possible to all our staff,” says Muthana. “We also saw an opportunity to reduce our costs by reducing the overall number of nurses needed to look after our patients.”

Retigence Technologies’ team members then worked with the group’s nurses to capture the variables and requirements for the project. For example, a minimum number of nurses with one year experience or more needs to be rostered on for each shift. Retigence Technologies then started building an application using compute resources available through Compute Engine, a Google Cloud product. “We selected Google primarily because of its pioneering work in artificial intelligence (AI) and machine learning,” says Srinibas Behera, founder and Chief Executive Officer of Retigence Technologies.

With the nurses rostering application developed, Manipal Health Enterprises Pvt. Ltd undertook several pilots to build user acceptance. “Some of our senior nurses took time to accept the fact automation removed their control over rostering assignments, but were finally convinced by the better transparency the product offered,” says Muthana. The organization deployed the application to a smaller hospital and secured user support before rolling out the application to its Bangalore flagship.

Eliminating stress

Deploying the application has enabled Manipal Health Enterprises Pvt. Ltd to remove a buffer of about 100 nurses retained to accommodate the variations in number of nurses rostered for individual shifts. “The savings on those salaries more than paid for the cost of developing the application,” says Muthana.

The application also enabled the organization to reduce the stress on nurses—both the nurses in charge of the rosters and the nurses subject to the rosters. “Night shifts were more equitably distributed among the nurses, while we have been able to reduce the 45 minutes per day required to amend rosters to just 10 minutes,” says Muthana. “In Bangalore alone, we have 51 nurses in charge of rostering—so the combined saving there equates to nearly 30 hours per day.” This is freeing up these senior nurses to complete more important tasks.

The application was subsequently implemented at Kasturba Hospital, Manipal, again reducing the time needed to generate complete nursing rosters to less than 10 minutes.

Managing leave and training

The organization now plans to extend the application to manage leave and training for its nurses and other employees. “I would like to see every employee given an annual leave plan that is added to the roster at the start of the year,” says Muthana. “The flexibility and control afforded by the application would enable us to address challenges such as managing leave across a workforce with high attrition rates.” The organization would also be able to create a calendar to ensure nurses receive all their required training.

“We also plan to keep fine-tuning the application to deploy nurses more efficiently and continue to reduce their stress levels,” adds Muthana. “We also want to create a nursing load indicator tailored to patients’ specific circumstances. For example, a sedated patient may not require much nursing care, whereas a patient who comes in with a broken leg and may be on a ventilator may require assistance from three nurses at once.” The business plans to use Google’s AI and machine learning APIs in the future to improve the value and user experience of the product.

Trend Analysis

Digital Maturity in Higher Ed Tied to Improvements in Students’ Journey: Study

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BCG and Google's 2021 study on digital maturity in higher education reveals 'going all-in' on digital helps universities become more agile and efficient in delivering education. It meets students' preferences and fosters future disruptions.

Why Higher Ed Needs to Go All-in on Digital

In the wake of the COVID-19 pandemic, the majority of students within the 18-24-year-old demographic now expect hybrid learning environments–even once we are beyond the pandemic. And a vast number of adult learners are seeking options that accommodate their work and family lives now that it’s clear that effective learning can indeed occur virtually. Implementing cloud technologies and achieving digital maturity within higher education will enable institutions to be innovative and responsive to evolving student preferences, while being prepared for future disruptions.

Exhibit 1: BCG

The state of digital maturity

In February and March 2021, Boston Consulting Group (BCG), in partnership with Google, surveyed U.S. higher education leaders on their views of the state of digital maturity in the higher education sector. This survey found that institutional and technology leaders strongly agreed that moving legacy IT systems to the cloud, centralizing and integrating data, and increasing the use of advanced analytics is necessary to make a successful digital transformation, and ultimately achieve digital maturity.

But what is digital maturity? Digital maturity—a measure of an organization’s ability to create value through digital delivery—focuses on three areas of technological advancement that drive large-scale innovation:

  1. Using cloud infrastructure
  2. Expanding access to data
  3. Using that data to improve processes through advanced analytics, such as Artificial Intelligence and Machine Learning (AI/ML)

Although university leaders agree on prioritizing digital maturity, more than 55% said they considered their schools to be “digital performers” or “digital leaders.” However, only 25% of tech leaders at these universities stated that their schools regularly use data analytics. As with corporations and governments, higher education institutions face barriers to technological innovation, such as:

  • Competing priorities to meet step-change goals and decentralized decision making
  • Budget constraints
  • Cultural resistance to change
  • Tech staff skillset gaps

Still, leaders understand that the way to overcome institutional inertia is with a strong, goal-oriented vision of what is best for the institution overall. Although only a handful of schools have reached digital maturity as we define it, others can learn a great deal from their examples. Here are the top takeaways from higher education leaders who successfully transformed their institutions:

Digital solutions can improve the student journey in many ways

Exhibit 2: BCG

As digital capabilities hold the key to dealing effectively with declining enrollment and rising costs, higher ed leaders identified four goals that are critical to improving performance:

  1. Improve the student journey
  2. Increase operational efficiency
  3. Scale computing power in advanced research
  4. Innovate education delivery

The research found that technology investments can help enhance the student journey in the recruiting and retention of students, improving digital education delivery, government funding, and donations from alumni. Digital maturity can make institutions more agile and efficient in delivering education that aligns with the changing societal norms, evolving student preferences, and future disruptions. Survey participants shared that they plan to increase the use of the cloud by more than 50% over the next three years. By shifting legacy IT systems to the cloud, institutions can increase scalability, lower the cost of ownership, and improve operational agility, while offering a more secure, long-term data storage solution.

Cloud-native software-as-a-service (SaaS) solutions provide an excellent platform for centralizing data. However, institutions that attempt to “lift and shift” their legacy systems to the cloud may encounter challenges to achieving measurable improvements in data integration and cost reduction. Higher ed leaders must realize that centralizing data and transitioning to the cloud do not happen simultaneously.

Leaders who are able to articulate a strong vision and commitment will experience a more successful technology transformation. By linking their vision to specific needs, such as more effective recruiting, leaders will find their technology investments will have a more substantial return. University presidents should base their decisions about which systems to move, when, and how on desired performance outcomes.

Big visions become a reality with small steps. Small pilot projects are an excellent way to start the journey toward digital maturity. Small steps toward a significant transformation can reduce resistance to change, build positive momentum, and produce better student outcomes. Read the full report here. If you’d like to talk to a Google Cloud expert, get in touch

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Supercharge Marketing with Ready-Made, Centralized Smart Analytics

Your company has lots of valuable marketing data, but it’s spread across many systems and teams. That’s a problem. In fact, only 13% of organisations feel like they’re making the most out of their available customer data today.

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Find out how new GCP tools for marketers and hear directly from brands, including Rituals and Waitrose, who are using them to solve use cases like audience segmentation, purchase prediction, and measuring lifetime value.

You’ll learn how Google Cloud is helping IT and marketing teams accelerate digital transformation within their organizations, to be data-driven, and customer-centric.

You’ll walk away with an understanding of how to adopt technology that transforms the way your company delivers marketing campaigns and customer experiences.

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What are TPUs and Why Should Data Scientists Care?

When it comes to machine learning, more data means better results.

But processing more data also requires more computing power. CPUs are great for sequential arithmetic calculations. They offer low latency with this type of workload. But to speed up machine learning, models have to perform multiple calculations in parallel. And that’s where GPUs perform better.

TensorFlow Processing Units, or TPUs, represent the most advanced hardware accelerators that has been architected ground up for TensorFlow by Google Cloud. Cloud TPUs deliver accelerated performance to help businesses train deep learning models in a matter of hours instead of weeks.

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Watch John Barrus, Senior Product Manager, Google Cloud; and Zak Stone, Product Manager, Google Brain, show you benefits of using TPUs and how to get started.

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