Cloud streaming

The journey to cloud transformation is often underestimated. Starting with the cloud is the kernel of what we’re doing but it’s much more resonant. Embarking on a cloud journey will have a ripple effect across an organization and one of the best examples of this is Netflix.

Netflix started as a physical media distribution company, emailing DVDs and Blu-rays to clients, but quickly moved to streaming services with a platform on AWS, entering the market very early on. The magic of the story is the courage they then had to pivot away from their business model to take on the behemoth of Hollywood and create their own content.

Why is that so special? Well for one it takes a lot of bravery to change your business model, twice, to create two market disruptions: the first being the impact streaming had on the distribution of media – the blockbusters of the world and cinema exhibition of films – and then Hollywood itself, and second, changing the paradigm of how films and TV series are made, released, and shared with audiences.

Netflix’s jump wasn’t made in one giant leap but rather, in a series of iterative, bold decisions that combined good vision with strategy to make it a success. The greatest learning though was Netflix’s response to the market – they realized that you can resist change as an organization and keep things boxed in, but you won’t be able to see a new reality of the wider digital benefits out there.

Adoption trends for 2023

As we look forward to what this year holds, it’s time to think about key trends and predictions for what lies ahead.

According to Gartner, 95% of new digital workloads will serve on cloud-native platforms by 2025. While that’s still two years away, there are visible trends emerging now in terms of how cloud is being talked about:

• Sustainability is an increasingly important subject in the world of compute, as it should be. We’ve now heard net zero commitments from each of the big cloud providers and can expect that they’ll expand on these commitments over the next six months. What’s interesting is that cloud providers are giving some power back to organizations to make decisions about what powers their processing – meaning they’ll soon be able to elect whether to use carbon neutral or net zero processing power in the not-so-distant future. 
• Modernization is kicking off in earnest – early adoption was often driven by IT organizations but looking at what’s going on in vertical sectors there are more and more interesting things that can be done with IoT and platforms-as-a-service that can profoundly change how businesses function. Terms like industry cloud will become part of our dialogue as Cloud becomes the default choice across verticals.
• Platforms are everywhere. How you think about your cloud environments now will be platform centric. Gartner often talk about ‘Cloud Infrastructure and Platform Services’ or ‘CIPS’ – bringing together multiple parts that pull together highly operating offerings.
• Death of lift and shift has been overly exaggerated. This was a version of a migration where applications moved from running in a data center to running in the cloud. We’re still seeing lots of organizations wanting to take that path and our reality is cloud native, where we operate from, and believe that shift and lift still has a place, it just depends on how you do it.
• Cost is everything. Tying into conversations with our first guest, CxO Advisor, Daniel Hartert, we discuss why cost is at the baseline of every business case for the cloud. This has to be factored in terms of business value. Root to benefit realization has to be clear and something that we don’t yet, as an industry, have a full grasp on.
• The talent crisis continues. There are only so many experienced people to go around. We must open up ways to train and re-skill talent, as well as increase diversity and inclusion – a topic that has been on the agenda for a while now but is critically important to broadening our thinking on the future of the cloud.

Navigating crises

Speaking of current crises – part of our discussion with Daniel touched on the changing nature of the market and the challenges CxOs face in driving value from the cloud.

Given current economic challenges, cloud investment is one area that can’t afford to drop. We have to manage the way through the anticipated global recession in a creative and innovative way that provides access to things we haven’t experienced in the past. Cybersecurity, as one example, is a huge area for growth – but this largely operates in the cloud, and is more secure in the cloud than on-prem. The security environment can feel overwhelming, but the sooner businesses harness the power of the cloud, and the data that comes with it, the more likely it is that they’ll be on the winning side.

Without dwelling too much on the current crisis – or giving too many hints at what’s to come in our next blog – hopefully this gives us a level set on where the industry current is, and what’s to come for our reality in the near future.

Can’t wait until the next blog and want to hear more? Listen to the full episodes, featuring our own Dave Chapman, Sjoukje Zaal, and Rob Kernahan as well as CxO Advisor, Daniel Hartert.

Capgemini Earthlings Ecopreneur (CEE) is such a platform that addresses this need. This is a portal that can be accessed only by the employees of Capgemini and is thus compliant to all regional standards such as GDPR. Everyone, as an employee, has equal right to create an individual mission (pertaining to Capgemini & UN Goal) and anyone, who is also an employee, can join in. The mission can be a digital mission e.g., a sustainable solution deployed for a client or a POC, or something as simple as cleaning the personal storage, or a social mission like planting a tree or ocean cleaning. The joiners can then forecast the KPIs that they are looking forward to achieving and at the end of the mission will update it with the actual result. The system then analyzes the impact of the mission once that is completed.

In this post, we will share an architectural reference from Capgemini for a solution that can help solve challenges in an employee portal exclusively dedicated for sustainability missions. The solution is resilient, scalable and uses multiple services, data, and asynchronous communication managed completely in the Google Cloud Platform.

What problem do we wish to solve?

Most of the internal portals of an organization primarily act a webpage with information regarding that organization and that may also support some synchronous request/responses with other internal or external hosts.

A few other applications are primarily COTS employee applications that are configured and customized for a specific employee usage like payroll or time reporting.

However, almost no organizations have an exclusive employee application solely dedicated to the cause of sustainability. We from Capgemini felt it is utmost important to have an application which will only serve the cause of sustainability, make each employee feel empowered so that we all can contribute effectively to the net zero goal that the Capgemini Group has set.

Hence for a sensitive subject like Net Zero and Capgemini Group’s vision to come to work in reality, we needed our own solution catered to our visions & exclusive strategic needs.

Capgemini Earthlings Ecopreneur (CEE) is a portal solution for all our employees that acts as a one stop platform for whole group to ENGAGE on Sustainability. It is a single pane of glass for all the sustainability related work that all the employees in Capgemini Sweden can do and is one of its kind in the group and outside.

Here all employees engage on a cause that is close to their heart, whenever they can. Every step taken by any employee towards sustainability counts in the Group’s overall objective.

The cloud that proudly proclaims to be the ‘cleanest cloud in the industry’ naturally was our preferred platform for implementation of our sustainability portal solution. Capgemini Group has a rich history of great relationship with Google Cloud. With a multicultural team of 300,000 people in 40+ countries, we have more than 100+ GCP certifications in Sweden alone.

Non-Functional Requirements

This portal is for all global employees, hence some of the key NFRs are

• Simplicity
• Ease of use
• GDPR Compliance for Users in Europe
• Scalability

About Capgemini’s Solution

We have created the Capgemini Earthlings Ecopreneur solution using GCP that is built on a polyglot service architecture using primarily React Framework in the Front end and services written in Java in the backend. Here all communications are in real-time asynchronous mode which ensures eventual data consistency and higher scalability.

The solution is following the 3-tier architectural model with clear separation of the view/presentation layer from the backend service and data layer. There are 3 distinct tiers in this application architecture – Presentation tier, application/business tier (handled with multiple APIs), and Data tier. The API first design methodology is adopted. All UI elements are interacting with the persistent data stores through various APIs created, optimized, and made reliable for information retrieval.

Presentation Tier

This is the topmost level of the application. This tier directly interacts with end users through user interfaces. Interactive user interfaces which enrich the user experiences for portal front-end is designed with latest React library and based on reusable components.

API driven Application/Business Tier

The API-first architectural modelling starts with the API design kept at the top. The API centric design and development adds some components into the overall architecture for better management. The APIs are deployed into a managed containerized environment in Google Cloud Platform Cloud Run. The APIs are developed in Java based REST services.

Data Tier

The application persistent storage will be managed through Google Cloud Platform’s Firestore which is a managed, scalable NO-SQL database.

Solution Architecture

User Interaction Diagram

1. End user will create a new mission by selecting a mission template. Each mission template is associated with a specific Capgemini goal which may serve one or more UN goals. While creating a mission, user must provide a forecast on the mission KPI.. Each mission must have an end date after which mission is no longer active and final report is calculated.
2. After creating a mission, it will go to the admin for approval.
3. If everything is OK, then admin will validate the forecasted KPI values based on the type of the mission. Based on these KPI values, the system will generate actual report once mission gets completed.
4. Once mission is approved other users can view and join it.
5. User who joins a mission must provide information related to the mission KPI.
6. Admin can approve a mission and reviews the KPI related information.
7. Mission is closed on the end date or if mission creator wishes to complete the mission if mission objective is reached.

Once a mission is closed, the actual KPI metrics are compared against the forecasted ones and system generates the final report. This report on the portal provides valuable inputs on how much contribution is made towards our sustainability objectives. Note: There are several other services e.g. sharing a mission (using social media channel) and reacting or commenting against a mission.

How the solution works

SSO

We are using PING SSO for user (employee) authentication and that has been implemented via a node.js service. Capgemini Earthlings Ecopreneur(CEE) application is protected under an authentication guard It first checks if the user is authorized or not, if not then user is redirected to Capgemini Single SignOn URL. After internal verification, it will be redirected to CEE portal. Two node.js service endpoints are used here to generate token  for fetching user information to be used in our solution as per GDPR compliance.

Compliance – GDPR

This is taken care by the infrastructure, configuration, encryption, and redaction in GCP platform and our data retention policies which are GDPR compliant.

List of Java Services

GCP Core Services used in the solution

Cloud Run

All services in CEE solution are deployed using Cloud Run. It is serverless and supports easy deployment of containerized microservices, written in any language, and can be invoked via requests or events.

Cloud Service Account

Access control in CEE platform is managed by Service Accounts. It represents a non-human privileged account that is used to execute applications and run automated services on Google Cloud Platform and ensures deployments are independent of users and admins.

Cloud Logging

Application logs of CEE are stored and managed in Google Cloud Logging. It is a fully managed service that allows to store, search, analyze, monitor, and alert on logging data and events from Google Cloud and from over 150 common application components, on-premises systems, and hybrid cloud systems.

Cloud Pub/Sub

All real-time asynchronous communication in CEE solution is handled via Google Cloud Pub/Sub. It is a no-ops, secure, scalable messaging that allows services to communicate asynchronously and enables creation of event producers and consumers.

Cloud Storage

All static images used in CEE portal are stored in Cloud Storage. It is a low-cost, scalable, reliable, and secure object data storage service in GCP that supports object life cycle management and retrieval in any desired frequency.

Cloud Firestore

The mission related data of CEE solution is managed in Firestore. It is a cloud-hosted, NoSQL database that web apps can access easily and directly via REST or native language SDKs.

Cloud BigQuery

The data needed for analysis in CEE application are managed in BigQuery. It has a flexible architecture that supports access to data on-demand with high performance queries and offers an amazing scale-friendly pricing structure.

Summary

Capgemini Earthlings Ecopreneur solution is a one-stop platform for every single sustainability related endeavor by all Capgemini employees built on a modern API First Approach and supporting real-time asynchronous integration on Google Cloud Platform. The architecture is completely language agnostic and capable to support theoretically infinite number of sustainable activities of 300000+ employees globally. This is also one centralized place for the management to set and measure the KPIs in terms of how many employees participated as sustainability volunteers individually or from a team and measure the Co2 impact of the mission that employees create and collaborate in a specific region or time. Powered by Google Cloud, the core USP of the solution lies in its simplicity. Anyone who wishes to have an exclusive portal for their employees to work on sustainability goals can easily adopt this solution. The solution is also capable of providing an easily readable dashboard for the management to view and analyze various sustainability KPIs, especially from voluntary participation of passionate employees which are otherwise not tracked in an organization. These are little steps, but important ones for a better future. And what better platform than Google Cloud Platform that uses 100% renewable energy on all cloud regions! Remember, there are no alternate plans for our planet. We must plan and act NOW.

Learn more about the power of our Google Cloud partnership.

Weaving the complex threads that form the fabric of breakthrough innovation is one of the joys of being at Cambridge Consultants (CC). I work alongside talented, multidisciplinary teams of experts who inspire me and motivate me at every turn. A recent project to help influence the future of quantum sensing in medicine is a case in point, where we brought together our in-house knowledge of quantum physics and practical real-world quantum application, with a deep understanding of the medical sector. That’s a potent mix.

To explain, let me rewind to early last year when CC was fortunate enough to begin a collaboration with the Swiss company Qnami, a renowned leader in quantum sensing technology. Their quantum microscopes incorporate nitrogen vacancy (NV) centers, in a diamond atomic force microscope tip, to offer extremely high sensitivity magnetic field measurements at an atomic scale.

The technology is currently most applicable to research activity, as well as some industrial R&D purposes. But Qnami were keen to identify other potential applications – particularly in the biomedical area – where NV magnetometry could provide clinical value and open new commercial avenues.

That’s a big ask, of course, but as a quantum physicist working in a commercial environment, I think it’s energizing that we’re increasingly able to put the big “what if?” questions out there. We can argue at length about the plausibility of individual scenarios, but the sheer potential of quantum technology enables us to hypothesize.

For example: “What if quantum computing could almost guarantee success for drugs in clinical trials, reducing cost and increasing the rate at which new diseases could be cured?” Or: “What if quantum encryption could ensure the absolute security of medical data?” And even: “What if quantum computers could tailor optimal personalized treatments, increasing the likelihood of a therapy being effective?”

Quantum effects increase sensor performance

What can’t be questioned is that using quantum effects to enhance sensing has the potential to increase sensor performance by orders of magnitude. This step-change in performance promises to enable new applications across many sectors, including in the life sciences. What exactly is quantum sensing? Essentially, it is making use of quantum effects to achieve something that an ordinary sensor simply can’t. Take a standard clock. It runs to an accuracy of around a second a day. But an atomic clock, based on a fundamental property of rubidium atoms, can be accurate to one second in millions of years. Other types of sensors, which are being unlocked by advances in the research underpinning them, can achieve similar feats – detecting with a sensitivity and stability that has never been achieved before. 

To unleash this potential, quantum sensing technologies are starting to move away from lab-based demonstrations and towards robust products suitable for real-life industrial applications. However, initial applications are often niche and typically serve research and development business functions. Finding market opportunities for new quantum sensing technologies, which are commercially attractive and can generate significant value, is critical for ensuring widespread uptake.

As indicated, we were able to respond to Qnami’s request with a with team made up of a unique set of skills – physicists who understand the fundamentals of quantum sensing, engineers accustomed to developing products to work in any environment, with tight cost and performance constraints, and domain experts with decades of experience working with the needs and challenges of medical device development. We also had something of a head start in terms of potential applications and challenges through a number of internal and client projects.

Our project with Qnami began with a market opportunity identification exercise that involved three tasks. First, we familiarized ourselves with Qnami’s core technology and captured key functional attributes. Second, CC experts identified a shortlist of potential opportunity hypotheses in a biomagnetic imaging application (in other words: where the technology could solve challenges in the life sciences). Finally, we assessed three of the most promising areas and analyzed the opportunity for Qnami to understand the risk/reward profile.

The project is one I’m proud to add to CC’s record of championing and pioneering emerging technologies, applying a wide range of specific skills and a comprehensive understanding of quantum physics to continue to push the boundaries of what is possible. Working in a team combining quantum sensing, deep medtech industry knowhow, technology insight, and strategic advisory services – that’s a great environment to be a part of.

First published on Cambridge Consultants Jan 2023

For more information on quantum sensing applications, go to Unpacking the potential of quantum sensing

[“Sabrina]” is                                [“Jill”]                                             [“Kelly”]
 GPT-3 from OpenAI                    Jurassic-1 from AI21                   Cohere from Cohere.
 
None of the responses were edited. We prompted the three different AI models three times for each question and selected the best responses. The humans in the loop were Rajeswaran Viswanathan, Aishwarya Jagtap, and Karan Kajrolkar, Capgemini.

How can we use data for a more sustainable world?

SABRINA: Artificial intelligence can be used to make the world more sustainable by helping to harness natural resources while also helping to reduce environmental costs. For example, AI could help to identify and manage plant growth in soils to optimize the use of resources and could also help to predict when and where wildfires could happen.

JILL: In the agricultural sector, AI is enabling farmers to predict crop yield and disease outbreaks, helping them reduce losses, optimize inputs, and improve yields. AI is improving the efficiency of water and energy use in buildings, helping to reduce energy costs and greenhouse gas emissions. In transportation, AI is supporting efficient freight transport, optimized routes, and real-time traffic management. In the energy sector, AI is improving the performance of wind farms and solar panels, helping to reduce carbon emissions.

KELLY: AI can be used to make the world more sustainable. A number of companies are using AI to reduce their carbon footprint and save money. For example, AI-powered predictive analytics and intelligent grid systems can manage the supply and demand of renewable energy, cutting costs and unnecessary carbon pollution generation. AI can also be used to fight climate change. AI self-driving cars, for instance, may reduce emissions by 50 percent by 2050 by identifying the most efficient routes. AI can also help make the world more sustainable. For example, AI can be used to support the UN’s Sustainable Development Goals (SDGs), and the UN Global Compact’s Ten Principles, which include human rights, labor, environment, and anti-corruption.

Can data and AI make the world more sustainable?

SABRINA: A lot of people think that data and AI can help make the world more sustainable because they can help us better understand how our actions affect the environment and how to make better decisions. However, there are also some concerns that data and AI could actually make the world more damaging because they could lead to more wasteful and destructive behavior.

JILL: Yes, data and AI can make the world more sustainable. Data and AI can help address many sustainability challenges. From enabling smarter transportation to making buildings more energy efficient, from enhancing environmental monitoring to improving waste management, from providing personalized healthcare to improving food supply chains, AI and data can advance sustainability.

KELLY: AI is helping to change the world for the better by making decisions, improving efficiency, and minimizing risk, as well as inspiring innovation and supporting sustainability. For example, AI can help governments and businesses improve supply chain efficiency, monitor progress toward goals, predict threats, and avoid risk. AI can also be harnessed to enhance productivity and increase transparency. This could be done through the integration of AI into environmental sustainability platforms that track supply chain, social and environmental impact, or by sharing information in real-time about energy usage or pollution with consumers, regulators, and other stakeholders.

What are the creative ways in which AI can be used to make the world more sustainable?

SABRINA: Artificial intelligence can be used to make the world more sustainable by helping to harness natural resources while also helping to reduce environmental costs. For example, AI could help to identify and manage plant growth in soils to optimize the use of resources and could also help to predict when and where wildfires could happen.

JILL: In the agricultural sector, AI is enabling farmers to predict crop yield and disease outbreaks, helping them reduce losses, optimize inputs, and improve yields. AI is improving the efficiency of water and energy use in buildings, helping to reduce energy costs and greenhouse gas emissions. In transportation, AI is supporting efficient freight transport, optimized routes, and real-time traffic management. In the energy sector, AI is improving the performance of wind farms and solar panels, helping to reduce carbon emissions.

KELLY: AI can be used to make the world more sustainable. A number of companies are using AI to reduce their carbon footprint and save money. For example, AI-powered predictive analytics and intelligent grid systems can manage the supply and demand of renewable energy, cutting costs and unnecessary carbon pollution generation. AI can also be used to fight climate change.

AI self-driving cars, for instance, may reduce emissions by 50 percent by 2050 by identifying the most efficient routes. AI can also help make the world more sustainable.

For example, AI can be used to support the UN’s Sustainable Development Goals (SDGs), and the UN Global Compact’s Ten Principles, which include human rights, labor, environment, and anti-corruption.

What should humans do to make the world more sustainable?

SABRINA: There is no single answer to this question, as the best way to make the world more sustainable depends on the individual and community context in which the act of reducing environmental impact is accomplished. However, some potential actions that could be taken to make the world more sustainable include implementing sustainable tourism policies, supporting renewable energy sources, and reducing consumption patterns.

JILL: The answer to how we can make the world more sustainable lies in what we, as individuals, do. What we can do as individuals is reduce our carbon footprint, minimize waste, recycle, plant trees, plant more trees and stop using plastic. We can also try to minimize our meat consumption, buy locally, support local artisans, buy less and donate more, reduce our water consumption, drive less, buy less and donate more, and buy less and donate more.

KELLY: Our choices have a profound impact on the environment and climate. From the way we get around to the food we eat, every day we make choices that affect the environment, the climate, and other species. It is time for us to rethink the way we do things. AI is not going to help if we do not make better choices. Here are some of the best ways you can help make the world more sustainable: recycle, cut back on plastics, buy in bulk, switch to a reusable water bottle, and grow your own food. Be energy efficient, take shorter showers, replace your light bulbs with LEDs, and lower your heat in the winter and raise it in the summer, stop eating meat.

How can humans and AI work together to create a sustainable world?

SABRINA: AI can help us to identify and quantify environmental problems and provide solutions that are tailored to specific local conditions. For example, AI can help us to map land use, water resources, and carbon emissions, and to develop plans for mitigating and adapting to climate change. AI can also help us to better understand and protect biodiversity and to develop sustainable agricultural and forestry practices. In addition, AI can help us to monitor and manage natural resources and to find new sources of renewable energy. By working together, humans and AI can create a sustainable world.

JILL: Humans and AI working together can create a sustainable world. The IPCC has concluded that the world needs to reduce emissions by 45 percent by 2030 to limit global warming to 1.5°C. With the right technology, humans and machines can work together to help achieve this goal. The combined power of people and machines can power innovation, create new economic opportunities, and drive climate action.

KELLY: The confluence of human and machine intelligence is enabling radical new approaches to solve the world’s biggest problems. As part of the Fourth Industrial Revolution, artificial intelligence is aiding everything from clean energy to new lifesaving treatments, and from conservation to policy creation. While AI has the potential to deliver many benefits to humanity, it also has the potential to wreak havoc if it’s not deployed responsibly. When it comes to building a sustainable future, what does it mean to be responsible? At this point, AI will be working side-by-side with humans for the foreseeable future. To maximize the benefits of AI for the future, it is important to involve humans at every stage of the development process, including planning and design.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 5 features 19 such articles crafted by leading Capgemini and partner experts, about looking beyond the usual surroundings and be inspired by new ways to elevate data & AI. Explore the articles on serendipity, data like poker, circular economy, or data mesh. In addition, several articles are in collaboration with key technology partners such AWS, Denodo, Databricks and Dataiku. Find all previous Waves here.

Although incremental change allows companies to experiment and iterate during their digital journeys, the COVID-19 pandemic rapidly accelerated the evolution of online and contactless shopping. Evolution became a revolution, with most Consumer Product and Retail (CPR) companies still mastering the omnichannel generation of their digital transformation to create a seamless shopping experience. Companies that are more digitally mature are already aspiring to the consumer-centric phase, embracing opportunities made possible by technology such as personalization and automation. 

What consumers want

Customers have more choices in how they shop and engage with brands. This has made it harder for brands to predict and anticipate needs across customer journeys. And that’s convincing some companies to innovate more quickly as consumer demand drives the need for speed and scale.

Think about your own online behavior. Say you’re shopping for an item and searching online for the closest store in your neighborhood. Google is likely your go-to for finding that information. Looking to troubleshoot an issue with a product or seek out a service? Again, you’ll likely hit up Google first, not even considering going directly to a brand’s website for answers.

Both scenarios point to a disconnect between virtual and physical worlds, a gap technology can bridge in numerous ways such as breaking down silos and integrating fragmented media channels. Interestingly, though, not everything will be centered online all the time. In our recent study on consumer behavior, The great consumer reset, Capgemini discovered 57 percent of shoppers plan to return to brick-and-mortar stores post-pandemic, which is basically unchanged from the 59 percent who often interacted with physical stores before.

But business as usual? Not even close. Consumers have come to expect a frictionless shopping experience (buy online, pick up in store) or an immersive one (products displayed online using augmented reality), and are not content to return to in-store lineups, empty shelves, or a one-size-fits-all approach. Moreover, customers want personalized interactions while ensuring their data and privacy are protected.

So the role of the store is changing. In fact, many online-only brands are opening brick-and-mortar establishments to drive customer experience. In our research on “smart stores,” we found the majority of consumers (66 percent) believe automation can improve their shopping experience by solving the challenges they face at retail stores.

From personalization to serendipity

Retailers must recognize that they have to win consumer trust and confidence. Many consumers believe retailers’ use of tech is focused on reducing costs rather than easing friction. And they’re right. That same Capgemini research found that only one-third (35 percent) of retailers consider “solving customer pain points” as the most important criteria when deciding which automation use cases to implement.

“Retailers are largely in the early stages of adopting automation, and that’s an opportunity to rethink how they’re using technology, not just to smooth out friction and engender consumer trust but to build unexpected consumer benefits,” says Neerav Vyas, Head of Customer First, Co-Chief Innovation Officer, Insights & Data, North America, Capgemini. “We’re trying to move towards this idea of delivering serendipitous experiences to bridge the physical and digital divide.”

The focus is not solely on shoppers seeking out a specific product. “When consumers are in an exploratory mood, retailers can recommend products and services customers didn’t even know they wanted,” says Vyas. For example, business teams that use personalization platforms as part of an integrated media strategy can optimize algorithms against outcomes such as improving conversion and driving engagement. 

Vyas says the elevated experience from “personalization to serendipity” fosters trust in the ability of recommendation architectures to persuade and influence consumers’ choices in beneficial ways. A case in point: our research found that half (52 percent) of spending by millennials goes towards experience-related purchases. As always, the key is to meet consumers where they are. Even better, according to Vyas, is to anticipate and understand when signals like customer intent are changing.

How to create value throughout the customer journey

One solution companies can implement right now is an integrated media spend platform that incorporates reporting, planning, and strategy across the entire customer journey. This offers value throughout the customer journey by using technology to reduce friction along the way. Think of it as starting with the customer looking for a product (search and discovery), moving on to the purchase (omnichannel basket, “shoppable” screens) and pick up/delivery (QR code scan in store), and through to post-purchase engagement with the retailer (Google Contact Center AI).

Such a holistic approach also accelerates data acquisition, integration, and reporting using advanced analytics to break down silos and emphasize the importance of privacy and first-party data. This in turn guides end-to-end interventions across customer journeys that enable optimized media spend, empowers businesses to analyze their spend distribution, fine-tunes owned and paid tactics with agencies, and promotes stewardship to support audit efficacy.

A culture of experimentation

With this data-driven focus, CPRs can create a 360-degree perspective of the customer. That intelligence can be used to enhance and humanize automated shopping experiences by putting the customer in control, whether online, in store, or across company brands. Moreover, by using Google Cloud’s emerging technologies such as artificial intelligence (AI), we help companies accelerate value across the spectrum, from supply-chain optimization and customer innovation to consumer experience.

Building a culture of experimentation is a team effort. “It’s not ever just one person who had a big idea. It’s all incremental steps,” says Jennifer Marchand, Google Cloud COE Leader, Capgemini. “Finding the right use case and timing is everything.” Take Google Glass Enterprise, she continues. For greater consumer experience, it can enable in-store associates to better serve with hands-free checkout, customer personalization and recommendations, and special offers. At the same time, Computer Vision and Smart Shelves can help prioritize tasks for employees, notifying them of low stock or a spill in the store.

Marchand points out that companies and consumers alike might not be ready to fully adopt some technology like facial recognition, but since almost everyone has a smartphone these days, they can benefit from automation with ease. “What’s interesting,” she adds, “is the way Google thinks about these types of problems, solving them for the long term.”

The store of tomorrow

Imagine a truly frictionless shopping experience, where state-of-the-art computer vision and AI identifies the products you pick up, put back, and keep, allowing you to head home, completely bypassing the checkout, with a 99 percent accuracy rate and receipts sent directly to your mobile app. That utopian experience is already taking shape at CornerShop, Capgemini’s live experimental store in London, UK.

Jamie MacLoud, Transformation & Strategy Consultant at frog, part of Capgemini, describes the retail space, which runs on Google Cloud, as the store of tomorrow, and not the distant future. It’s an experiential space where retailers and brands can explore, develop, and test technological shopping innovations in real-time. The outcome is a clearer understanding of how digital innovation can enable new ways to progress the customer experience, improve in-store operations, and help consumers to rediscover the joy of in-person retail through new ways to shop and engage with brands. 

“We build, test, and learn about store concepts of tomorrow that we believe could be implemented into actual stores in the next one to two years. Getting these experiences in front of real customers in the CornerShop allows us to generate tangible learnings that we can share with our clients and use to shape future store strategy”  says MacLeod. CornerShop was opened to the public in two eight-week stints, which allowed real-time testing to see what technologies resonated with customers, which brands can adapt and scale. Frictionless checkout, not surprisingly, was a big win for customers, but the technology underpinning the “virtual try-on” of clothing was deemed more suitable for the store of the future.  

So, unlike an innovation lab, CornerShop lets companies experiment risk free, speeding up the process from hypothesis to full-scale implementation. It’s also another step toward solving the challenges customers face, while delivering those serendipitous experiences that build brand loyalty and longevity.

Learn more about how Capgemini is partnering with Google Cloud to help retailers create next-generation shopping experiences today.

Increasingly, many in the corporate world and public sector are adopting a new hybrid model in which their internal R&D is complemented by ecosystems of startups. But the real implications of this change to the traditional tech adoption model are only slowly being realized. Increasingly, startups can deliver plug and play solutions that can be adopted quickly and directly – so, where does this leave Big Tech, clients, and service providers, and what is their new role in the value chain?

The market dynamics are changing fast, and corporate as well as public bodies must find the most appropriate way to leverage the power of startup ecosystems to create sustainable value.

“Standing still is the fastest way of going backwards in a rapidly changing world.” These words, attributed to the Hollywood actress Lauren Bacall, could easily apply to corporate ambition in the 21st century. While every enterprise recognizes the imperative to move forward by leveraging breakthrough technologies and evolving innovative products and services, some have also recognized that the sources of new thinking and ideas are evolving too. Where a decade ago businesses would rely on their own R&D departments, together with bilateral partnerships and strategic alliances with Big Tech companies, now there are new players in town. These are the growing number of tech startups, disrupting markets and powering technological innovation to an ever-increasing extent. Dynamic, agile, and unafraid to take risks, it is estimated that by 2025 they will constitute 44% of innovation sources, compared to 10% today.

The ability to implement groundbreaking solutions at speed – to achieve both significant change and incremental gain – is the holy grail for businesses. This is precisely what startups can help them deliver, often with plug and play solutions and capabilities and expertise that companies cannot always source in-house. Of course, external sources may always need to be complimentary to their own R&D, but whatever particular challenges a business faces, there’s a strong chance that a solution will be developed faster with the help of a startup.

With this new dynamic, the traditional way of collaboration may no longer be the right model. Corporates know that they need to widen their horizons but are understandably wary of bilateral or consortium partnerships with young businesses that have no track record and little accountability. Some have already dipped their toes into forging relationships and investing in startup businesses, but the chance of backing the wrong horse holds others back. A collaboration can seem like a leap in the dark for notoriously risk-averse corporates.

Time for a new collaboration paradigm

So, instead of thinking in terms of closed, siloed partnerships, let’s blur the boundaries and open up the conversation. One way to accelerate the adoption of innovation and dynamic intelligence is through an open ecosystem that facilitates collaboration between corporates, Big Tech, and an infinite number of startups.

Of course, there’s more to think about than simply adopting an open ecosystem and embracing the startups within it. There are important considerations and questions to answer that we will address in more detail across a series of blogs and videos, including:

1.   Will organizations need to change at a fundamental level?

Working successfully with startups is not simply a change of mindset. As collaboration through an open ecosystem speeds up time to market (one of its core benefits), enterprises may need to adopt completely new ways of working, adapting their organization, processes, systems, and even business models.

2.   How can risk management cope with startups?

For a large corporation, adopting startup solutions at scale into the organization comes with a clear cultural shift and, specifically, it needs to overcome its intrinsic risk aversion. To make deployment easier, it is necessary to properly consider the critical aspects to be addressed.

3.   How will Big Tech and VCs influence innovation in the new model?

Big Tech and VCs are still a primary source of investment for startups. According to a recent IDC study, Salesforce and its partners will grow the Salesforce economy by 1.2 trillion dollars by 2024, creating 4.2 million new jobs – a potential game changer for the startup ecosystem. Venture capital funds are also investing in innovative startups at unprecedented levels. According to CBInsights, global funding for startups has increased by 157% YoY between Q2 2020 and Q2 2021, reaching $156 billion in just that last quarter. On top of funding, the VC industry has clearly become a critical source of qualified market intelligence.

4.   How can the startup ecosystem be leveraged for strategic insight?

Given the depth and diversity of startups, analysis of qualified intelligence can provide advanced indicators of technology evolution and market trends. This could become a strategic lever for corporates to use to their advantage.

5.   The corporate dilemma: Collaborate or acquire?

Buying a startup is clearly part of the “make or buy” dilemma, as demonstrated by GAFAM (Google, Apple, Facebook, Amazon, Microsoft), who are currently acquiring startups at a rate of one a week. Is this the right strategy, and are all stakeholders aware of the driving forces and benefits of a dynamic startup ecosystem?

6.   Beyond POCs/POVs with startups: How to ensure adoption at scale

Since startup solutions are often plug and play, adoption could be seen to be as simple as the IT integration of the solution. Yet, that is often only true in theory. Our experience has demonstrated that the adoption of SaaS into established organizations often faces major integration and cultural issues due to the existence of legacy IT and well-established processes. Therefore, sustaining value creation at scale becomes a lot more complex than expected.

The change is happening now

The simple truth is that startups are becoming a core part of new technology solutions and every corporation must define a strategy of working with them or risk missing out on the disruptive technologies that could power their future. An open ecosystem has huge potential advantages for all players – corporates, Big Tech, and the startups themselves. But what structure should apply to this ecosystem, and what framework needs to be designed to ensure a successful and sustainable collaboration? Working with tech providers has been Capgemini’s core business for decades and, today, opening the collaboration play to emerging yet promising tech partners has become an absolute necessity to keep bringing and creating value for and with our clients. In the forthcoming blogs and vlogs, we will be capturing insights from various ecosystem stakeholders to better understand how to sustain innovation at scale within big private and public companies.

The changing privacy and marketing technology landscape continues to create more uncertainty in measuring marketing ROI. Coupled with the deprecation of cookie-based ad technology, advertisers will no longer be able to target, re-target, model, and analyze campaign performance to make informed decisions – unless they future-proof their systems and processes.

Advertisers currently face significant challenges combining first-party data with third-party advertising and marketing data to measure and plan advertising campaigns in a privacy-compliant manner. That is why Capgemini is partnering with Amazon to deliver advanced advertising solutions using the Amazon Marketing Cloud (AMC), a solution from Amazon Ads that tracks signals across the platform and their advertiser-owned pseudonymized data. Together, they provide purpose-built solutions to meet the needs of advertising agencies, marketers, and publishers.

AMC and the Amazon Demand-Side Platform (ADSP) have together become an essential platform for unlocking insights and reaching the 135 million unduplicated US viewers on Amazon’s streaming service.

With AMC, advertisers have a solution that helps combine their first-party data with Amazon advertising data within a scalable and secure architecture for multi-party analysis. Once first-party data has been uploaded to AMC, advertisers can perform analyses in combination with Amazon Ads data – and begin receiving insights that help improve understanding and performance of their Amazon Ads campaigns.  AMC ensures that first-party data is stored and controlled within an advertiser’s own AWS account, that they have full control of any data uploaded, and that Personal Identifiable Information (PII) is not uploaded directly to AMC.

AMC has evolved from a post-campaign measurement and analytics offering to a solution for audience activation.

Amazon has also released an AMC-based attribution tool for in-store sales via their owned grocery networks (i.e., Whole Foods and Amazon Fresh), and now also supports video advertising data from Twitch, the popular live streaming service it acquired. Lastly, since Amazon has an extensive Amazon Shopper Panel in the United States, it is piloting a new metric called Amazon Brand Lift, which companies will use to measure upper-funnel metrics such as brand awareness and intent.

Capgemini’s customized AMC solutions help advertisers quickly get up and running with multi-touch attribution, media mix modeling, and more with an approach that streamlines implementation to maximize benefits. Immediate outcomes include unlocking insights to reduce customer acquisition costs (CAC) and increase lifetime value (LTV). Additional outcomes include gleaning new insights on audiences who engage with ads and customers who buy products from third-party retailers.

“Capgemini helps clients jumpstart their AMC journey with a package of accelerators that deliver personalized ad experiences, optimize ad serving performance and cost, and innovate with advanced audience segmentation and attribution,” said Neerav Vyas, Head of Customer First North America, and Co-Chief Innovation Officer – Insights & Data, North America at Capgemini.

Capgemini’s package of AMC accelerators enables advertisers to rapidly access a complete view of audiences throughout the customer journey across all touchpoints – enabling the consistent delivery of relevant ads to target audiences across devices and formats and allowing advertisers to attribute advertising and conversion events when they occur on different devices.

Capgemini’s solution, built on AMC, enables multiple integrations and distribution channels for sharing data with flexibility and interoperability, and provides tools for better managing first-party data and integration with third-party platforms. The goal is to make marketing operations more actionable and data-driven by fostering creativity and strategic planning to drive analysis, optimize marketing ROI, and harness customer journey and path to purchase analytics.

For more information about how Capgemini can transform your digital marketing strategies, please reach out to Neerav Vyas at Neerav.Vyas@capgemini.com or Dio Favatas at dio.favatas@capgemini.com

For the second year in a row, Databricks recently partnered with MIT Technology Review Insights to survey 600 CIOs, CTOs, and CDOs from large enterprises. The key result: CxOs and boards recognize that their organizations’ ability to generate actionable insights from data, often in real-time, is of the highest strategic importance. All respondents agreed that companies must view AI adoption as mission critical in order to succeed. But without effective data strategies, businesses miss massive opportunities to better understand their customers, offer high-value products, and streamline operations.

With such a significant link between effective AI strategies and strong data, not using the right AI tools or neglecting to leverage AI in the most effective ways can foil even the best-laid data plans. Here are four resolutions to make your data strategy pay off this year.

1. Reassess your data architecture

Most executives (72 percent) say that data, both fragmented and with poor quality, is likely to be the biggest issue when aspiring to achieve AI goals. The only way to better prepare for these challenges is to invest in a flexible data and computing architecture, like a lakehouse, that embraces open standards and can scale to meet the changing needs of the business. By creating a lakehouse, a company gives every employee the ability to access and employ data and artificial intelligence to make better business decisions. Many organizations that implement a lakehouse as their key data strategy are seeing lightning-speed data insights with horizontally scalable data-engineering pipelines. Walgreens specifically shared that a lakehouse enabled smarter algorithms and generated new types of reporting that help people understand the supply chain and store labor and productivity, patient vaccine scheduling, and prescription pickup processes.

2. Build your tech stack in the multi-cloud

Many data and technology leaders believe it’s not enough to think about the cloud in the singular sense — instead, they think about building a multi-cloud environment. As the adoption of cloud-based technology grows, many look for solutions that can move across major clouds (such as those from AWS, Azure, and Google Cloud). In our survey, 78 percent of executives agreed that a multi-cloud approach ensures the most flexible foundation possible for AI development. It offers organizations easy integrations when bringing on new solutions or businesses that use other cloud providers, flexibility to run workloads anywhere, and the assurance that they can comply with regulations down the road. Organizations that adopt a multi-cloud approach can also create new revenue opportunities and enhance customer experiences.

“Without effective data strategies, businesses miss massive opportunities to better understand their customers, offer high-value products, and streamline operations.”

3. Invest in low/no code

Low- and no-code approaches are opening new pathways to innovation and lowering the barrier to entry for people who want to get quick insights from their data. Given how competitive it is to find the right tech talent in today’s hiring market, low- and no-code tools are key to relieving some of the pressure on data teams, empowering less technical teams to build models – even with just a basic understanding of machine learning. No-code platforms make it possible to leverage AI without hiring expensive developers and data scientists, which means smaller businesses can more easily harness its power. Columbia Sportwear embraced this resolution and has seen more business units using the platform in a self-service manner that was not possible before. This has sped up the time for insights for all groups.

4. Embrace opensource AI and open standards

Open-source data lakehouses are quickly becoming the standard for how the most innovative companies handle their data and AI. It prevents teams from building tricky solutions in-house from scratch, which eats up resources. In our survey, 50 percent of respondents said that open-source standards and open-data formats were at the top of their dream tech stack list. Open source usually comes at little to no cost and, more importantly, it’s tried and true — it’s a community effort, and solutions have been adopted and vetted by many, which equates to fewer headaches for your IT team down the road. On top of this, the commitment to open data standards fuels the open-source community, which helps create a large talent pool of data experts who are better equipped to move use cases to production. It’s easy to get overwhelmed with your new year’s resolutions – especially the hard ones. Organizations must continue to stay inspired when they think about their data strategy. Our survey showed that a smart data strategy will ultimately provide better data value.

Stay the course to be prepared for a happy new year!

INNOVATION TAKEAWAYS

BUILD YOUR TECH STACK IN THE MULTI-CLOUD

A multi-cloud approach ensures the most flexible possible foundation for AI development.

INVEST IN LOW/NO CODE

Leverage AI without hiring expensive developers and data scientists.

EMBRACE OPEN – SOURCE AI AND OPEN STANDARDS

Take advantage of an open-source community and talent pool.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 5 features 19 such articles crafted by leading Capgemini and partner experts, about looking beyond the usual surroundings and be inspired by new ways to elevate data & AI. Explore the articles on serendipity, data like poker, circular economy, or data mesh. In addition, several articles are in collaboration with key technology partners such AWS, Denodo, Databricks and Dataiku.

You can also find all previous editions here.

The current HR Cloud market is broad and offers a variety of unique features and functionalities that can often be difficult to keep track of. Regardless of the type of system (e.g., HR suite, HR enterprise platform, or experience solution), the right decisions should be taken with a focus on People’s Experience, Experience Excellence in HR and not forget the “Experience Excellence Value Case” focusing on the optimal balance between HR automation ambition, HR IT investments and the level of people experience and seamless workflow design desired. Careful consideration of all companies, business, people, HR and IT-related requirements is essential to ensure that the right solution is selected, the configuration is a success, and will fit with the company’s business case and experience culture.

HR Cloud selection and implementation

To take the right decisions, we recommend a structured vendor selection approach in the first step that guarantees the future HR Cloud system selected best fits the company’s budget, HR products & Service Delivery ambition, process requirements (e.g. in terms of ET&C, legal compliance) and the desired people experience & way of working culture. Afterward, a cloud readiness assessment stream ensures that the company can start the subsequent cloud implementation with all necessary preparations and requirements. To achieve all this, a detailed upfront consideration of the targeted HR IT strategy and vision is a must, defining the organization’s future HR IT Landscape ambition and related optimization and investment need decisions to be taken.

For a successful cloud implementation, it is crucial to also empower the HR team, employees, and managers as new processes are rolled out, political obstacles are carefully managed and moderated and a joint future cloud mindset is proactively promoted and growing. Our dedicated cloud advisory approach combined with agile program & change management capabilities is tailored for the suite, enterprise and experience solutions, and associated vendors. It is developed by agnostic HR Cloud Advisory & systems experts and enables customers to take the right decisions, from technical and functional perspectives. When handled in this way, organizations can generate major benefits towards seamless workflow and process design as well as HR IT architecture optimization and the defined Experience Excellence Value Case.

Rethink the onboarding experience

But what does this all mean in concrete terms? Let’s dig into one prominent example our clients frequently address as their major area of concern: large potential for experience-driven HR IT optimization is frequently identified e.g., in the Onboarding process. This process focuses on how organizations integrate new employees and prepare them for their new roles. When the process is successfully streamlined in our experience-driven way, we directly see project outcomes such as improved retention rates, employee engagement, and productivity as return on investment. But how to? As part of our HR IT Onboarding redesign of end-to-end processes, structures and responsibilities are reviewed and redefined in the experience-/ user journey-driven way considering all external and internal stakeholders involved, such as external workers, recruiters, hiring managers, IT employees, etc. This makes Onboarding processes for the HR IT landscape optimization certainly increasingly complex.

Almost all major HR management software platforms offer their own Onboarding modules. In this blog series, we take a closer look at the offerings from vendors of the suite solutions Oracle, SAP and Workday, as well as the enterprise solution, ServiceNow. Furthermore, we will offer an approach that leads to the optimal Onboarding experience, covering three Onboarding phases leveraged by HR Cloud technologies.

Our next blog #1 takes a closer look at creating the decisive factor for employees to stay by leveraging HR Cloud technologies.

Interested? Looking forward to reconnecting! 

Part of Capgemini’s HR CloudWatch Blog, hosted by Dr. Sandra Duesing, Vice President of Capgemini Invent Germany, and the Global Head of “Reinventing HR.”