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The digital twin and SAP S/4HANA®

Capgemini
March 1, 2021

As SAP plans to discontinue the mainstream maintenance of its existing ERP solutions by 2027, organizations are considering various methods in their transition to SAP S/4HANA®.

This presents a golden opportunity to transform and digitize operating models, processes, data, and technology to create an organization that adapts easily and with agility, while also accelerating the value of their S/4HANA roadmap.

The “S” in S/4HANA is for “simple”

Efficient, effective, and secure migration starts with data harmonization and end-to-end business process standardization, before launching a new, digital core.

It’s best to approach this strategically:

  • Design a frictionless, agile operating model, where global end-to-end processes are standardized and designed towards a common S/4HANA-enabled template
  • Assess digital opportunities to streamline, optimize, and automate processes, with AI-enabled controls and automation zones
  • Establish and integrate best practices and KPIs
  • Review existing SAP and technology architecture, with a view to minimizing customizations and assessing other digital tools (including platforms, workflow, robotic process automation (RPA)/artificial intelligence (AI) integration, data management, knowledge management etc.)
  • Enable simplification of the core by aligning with the overall business and IT roadmap to gain adoption
  • Conduct appropriate cost benefit analysis of future opportunities and prioritize, with assigned ownership.

https://youtube.com/watch?v=OWYqdKX12c0%3Ffeature%3Doembed%26enablejsapi%3D1%26origin%3Dhttps%253A%252F%252Fwww.capgemini.com

Enter the digital twin for S/4HANA

As the tools of innovation improve, the capabilities of digital twins are enabling more companies to enhance performance and drive stronger business outcomes.

A digital twin of an organization is a virtual replica of an actual and potential processes, products, or services that enables you to analyze and optimize those processes, products, or services in a digital instance to simulate the impact of change before they become reality.

The impact on business operations is to simulate the impact of change for any organization, using metrics, volumes, and data that can be integrated into the model.

Capgemini delivers digital twin

Capgemini recently worked alongside an organization on such a program. The aims were to:

  • Design an S/4HANA-enabled operating model to enable the client to recreate its process landscape and adjust to organizational changes over the years to come
  • Identify, evaluate, and prioritize opportunities for transformation in line with the business’s SAP S/4HANA migration roadmap.

The digital twin was set up to address the full scope of finance and accounting, supply chain, procurement, master data, and HR. The cloud-based SAP S/4HANA operating environment covered globally standardized processes, all modeled within the BusinessOptix platform. This model was enriched with AI and RPA-zones, roles and activity owners, S/4HANA Fiori-transactions, and integrated controls, to function as the North Star for our client’s organization.

As a result, ready-to-use process flows emerged that the organization could immediately introduce, significantly reducing the time and cost expended on training and onboarding.

The net outcome of all this is that the business is now able to merge the migration of its system landscape with the organizational changes it is making as part of its digital transformation.

The ultimate goal – a frictionless enterprise

In summary, developing a digital twin for SAP S/4HANA enables businesses to remove bottlenecks from current processes, simulate the impact of organizational change and establish a common design towards a digital future.

The ultimate outcome is what we at Capgemini term the Frictionless Enterprise – an organization in which data can flow seamlessly between people and processes, intelligently, and as and when it is needed.

Pre-configured solutions of this approach are available that can save weeks in days sales outstanding (DSO) and reduce total operational costs by 40 to 60 percent. The sooner businesses embark on the path to digital transformation, the better able they’ll be to take advantage of game-changing approaches like this.

To learn more about how Capgemini’s integrated D-GEM for SAP S/4HANA solution enables our clients to determine and operationalize their unique S/4HANA journey, contact: sanket.a.solanki@capgemini.com

Learn more about how Capgemini’s Frictionless Enterprise approach implements ways to detect, prevent, and overcome frictions in our clients’ business operations, delivering enhanced business outcomes in a value-focused way.

Sanket Solanki advises clients on implementing finance transformation opportunities across their operations that address their future strategic vision, whilst designing and developing agile business and operating models, augmented with AI, to drive sustainable business outcomes.

Frictionless, AI-driven record-to-analyze

Capgemini
February 26, 2021

Next year, you tell yourself, will be different. Next year you’ll be better organized. You won’t leave things to the last minute.

But the months pass, other things take priority, and before you know it, it’s that time of year again, and you’re no more prepared than usual.

I refer, of course, to annual tax returns. There aren’t many of us who carefully file and log each item of information away when it comes in, and make an early submission to the tax office as soon as we have the last piece.

No. Most of us delay. There’s a deadline, so we work to that, instead – and as a result, there’s way more last-minute stress in our lives than there needs to be.

The once-a-month mindset

In business, finance functions tend to be the same. A once-a-month mindset prevails: when the monthly close comes round, there is a rush to draw information together, to reconcile data from ledgers held on disparate systems, to execute checks and controls on transactions coming from upstream processes, resulting in people having to work late to meet the deadline. Compliance depends upon it.

The difference, though, is that the problems with personal tax returns are largely of our own making – but for month-end close, a number of factors are at work. High on that list is the disparity I just mentioned: data sources are all too often mutually inconsistent and disconnected, and until these mismatches are resolved, they are going to create work each and every time the deadline comes round.

AI-driven record-to-analyze

What’s needed is a permanent fix. When processes are re-engineered, when systems are interconnected, when accountants are augmented with artificial intelligence (AI) and intelligent automation, when the data from different sources and ledger are orchestrated and consistency is established, the effort involved in closing the month reduces substantially. In fact, it’s possible to do away with the month-end process altogether.

How so? By embedding intelligent automation and AI into the record-to-analyze (R2A) function. At Capgemini, we have what’s termed AI Controllership. This is an integrated R2A platform with embedded AI controls, real-time journal entries, continuous certifications, a virtual controller, and AI accounting insights, that delivers a seamless, continuous accounting and close.

With AI Controllership, everything can be posted seamlessly and completely – and in real time. It’s rather like that example I just gave of logging and filing your personal tax data as soon as you receive it: it happens straight away. There are no gaps, and no accruals – and what’s more, no one needs to wait until month-end to see how things stand. Instead, they have information that can be pulled up on demand, and at any time.

The difference this approach makes is quite stark. Traditionally, R2A involves identifying and locating errors in upstream processes, and those errors are often the result of the data integrity and inconsistency issues I mentioned. Within what we at Capgemini call the Frictionless Enterprise, the flow of data is seamless, because controls have been put in place at source, and not retrospectively. We eliminate the siloes between the process towers and operate as one frictionless finance function. If any errors do occur, they are identified and corrected as they happen, and not at month-end, and so the data entering general ledger and ERP systems in real time is dependable.

It’s worth summarizing the benefits:

  • Continuous accounting – move away from “once a month” approach to create a balanced workload
  • Continuous analysis – identify errors at source, when transaction occurs. Act earlier, rather than later. Predict
  • Imperceptible period-end close – minimal interference to the Business
  • Finance intelligence – generate insights supporting business and CFO strategy to enable informed business decision-making
  • Confidence – ensure compliance, minimize the risks, and provide assurance to completeness and accuracy of financial statements

One of the most important advantages on this list is implicit in the point about insight. When everything can be processed on demand, and the whole burden of month-end pressures goes away, people can instead spend time on what they do best – analyzing and thinking. Instead of striving to put the numbers on the page, they have them right there in front of them, and they can focus on what they mean, on what they suggest as a course of action for the business. That’s a way more productive use of their time.

Incremental benefits

One last thought. I said just now that achieving the fix of cross-functional consistency may be a permanent proposition. But that doesn’t mean it has to be monolithic. It’s possible to introduce elements of frictionless incrementally, one process at a time. As new elements come on-stream, so the benefits will multiply.

The R2A function is a pretty good place to start. Last year, in this area alone, a major multinational in the media and entertainment business achieved efficiency savings of more than 30%, with a significant portion of achieved through enabling touchless journal entry processing, which is one of the paradigms for continuous accounting.

It’s worth considering, not just because of the immediate benefits it delivers, but because of the implications of extending frictionless principles across the entire finance operation. With less time fighting fires, you’ll have more time to think, and plan – and maybe more time, too, to address the way you approach your own tax return.

To learn more about how Capgemini’s Frictionless Finance can help you start your frictionless  journey towards enhanced R2A processes and improved customer satisfaction, contact: robert.piotrowski@capgemini.com

Robert Piotrowski partners with clients in their transformation journeys, leveraging AI and intelligent automation to reimagine their finance functions.

Embark on a transformation journey to identify improvement opportunities and leverage best practices around the industry

Capgemini
February 26, 2021

While Heraclitus, the pre-Socratic philosopher, was not referring to modern-day enterprises, his statement resonates particularly well today. This blog explores why transformations are challenging and why no two organizations will ever share the same transformation journey.

Today, in a rapidly changing world, organizations build customer experience and gain insights in order to make smart investments into products and services. Business process transformation facilitates these transactions from the inside out while the organization builds its solution, keeping the customer at the center. Business process and digital transformation can be overwhelming for organizations and they don’t always know where to start. But they do know what to expect from a successful transformation; they want more value, more quality, and most importantly, they want it to be future proof.

When we talk to our clients about the business process transformation journey, we find that they want insight into their transformation rather than a flurry of buzzwords. No two organizations’ cultures will ever be the same and neither will their challenges, but surely there must be a common pattern or framework to solve them.

Process improvement has to lead the way for any transformation. Business processes form the strategy for digitally transforming an organization. When embarking on a transformation journey, it is natural to identify improvement opportunities and leverage best practices around the industry.

At Capgemini, within the Automotive and Manufacturing IndustryHub, we understand business processes and identify the best practices followed by industry leaders. We place the client’s portfolio of products and services at the core of our solutions.

We base our framework on standardized processes used by hundreds of organizations to define their business processes. Using research, we structure a path that uniquely matches our clients’ culture and ambitions. It is likely for an organization to have a unique selling Proposition (USP). We can help our clients to identify priorities for business transformation based on their relevant portfolios and ambition and visualize their applications from scattered legacy solutions to centralized and integrated systems.

Transformation cannot be limited to improvements in isolation, such as supply chain improvement or dashboards. It must stem from the integration of technologies and ecology of processes. To get the best out of a transformation program, organizations must think about innovative solutions that enable employees to make informed decisions looking at the integrated picture of processes and systems that interact across the organization with tangible business benefits.

Conclusion and suggestions

In the quickly shifting paradigm of new business models, companies have to make their systems and products relevant to the market. Business transformation takes leadership, tenacity, investment, and resources. It is not easy, but with a comprehensive and tested framework that puts business priorities and ambitions at the core, it will succeed.

This blog was written by Ankit Soni. To learn more about the Automotive and Manufacturing IndustryHub’s approach to and experiences in enabling business transformation, please contact Milind Dumbre or Roshan Batheri.

Authors

Ankit Soni Consultant CapgeminiMilind Dumbre Senior Manager
A&M IndustryHub
Capgemini
Roshan Batheri Director
A&M IndustryHub
Capgemini

Is your customer service set up for more disruption?

Capgemini
Capgemini
25 Feb 2021
capgemini-invent

The last 12 months have accelerated profound shifts in the way organizations serve their customers.

New norms and future storms

As the world hopefully starts to open up again this year, organizations are going to be increasingly pressed to balance their service needs across different channels. Years of customer-insight-driven assumptions will be turned on their head as consumers actively seek new types of information, services and products, increasing demand across different contact channels. The dependency on digital channels over most of last year will remain, but as customers crave more detail and immediacy of information, the organizations with the ability to deliver superior service seamlessly across channels will truly differentiate and be the ones to thrive this year and beyond.

There are few organizations in the world that haven’t been impacted by the rapidly shifting demands on their customer relationships. Regardless of whether an organization has remained open or not, the type of dialogue has changed, a change that will remain for several months more and, perhaps, indefinitely. Consumers will expect to interact in different ways; buying patterns will change and queries related to health and safety protocols in store or on delivery (previously rarely considered) will become more of a priority. In fact, a recent report by the Capgemini Research Institute, The Consumer and COVID–19, revealed that 59% of consumers prefer to shop with companies that assure them of safe delivery practices.

This will drive a significant shift for organizations: in how they engage with customers, how they support the changing expectations of their own employees, and in how they better integrate different functional silos, ensuring increasingly emotional customer priorities are addressed across the end-to-end value chain, from manufacturing to post-sales support. The response to COVID-19 will accelerate the move towards more flexible, dynamic customer service organizations, a move that that has been underway for the past few years.

The urgent question is: how do you meet demand and reduce costs?

In the past year, customer service organizations have faced the challenge of rapidly moving contact center personnel to homeworking, adjusting KPIs, technology and working practices, and have needed to support a cultural shift among sometimes hundreds of contact center workers spread out over different locations. Reduced service levels coupled with increased contact volumes have accelerated the shift to digital self-service. These changes could permanently reshape customer engagement. As the world starts to open up again organizations have the opportunity to use the changes to drive greater customer intimacy and meet increased demand while also controlling costs.

One organization that is already outfitted for future surges in customer engagement is Aegon, the multinational life insurance, pensions, and asset management company. During the pandemic they responded with agility to meet customer expectations after seeing demand for their service center increase significantly. Remarkably, they were able to adjust their service model and launch a web chat in just five days. This provided support to thousands of customers and financial advisers. And all these interactions of course give the customer analytics team invaluable data in order to serve demographics more effectively. Aegon agents now handle 200 online conversations a day to service their 400,000 customers.

Because you don’t get a second chance to answer a customer’s first query

To address this, organizations need support to relaunch their service capabilities in the right way, prioritizing key business tasks (for example customer retention, sales, or insurance claims) while focusing on the employee, customer experience, and changing customer behaviors. Optimizing operations is critical at a time when cost efficiency is becoming more of a business priority. It’s imperative to be able to scale as the economy grows while retaining the flexibility to adapt to any future adversities.

Organizations should now accelerate change in three key areas:

  1. Developing new capabilities and moving to the cloud

Implement CRM and Contact-center-as-a-Service platforms to support more flexible working across service organizations, ensure greater ability to flex resources in line with contact volumes and improve the experience customers get when they engage across multiple channels. Increase process automation and embed intelligent routing to react more rapidly to demand fluctuations. Ensure you are one of the organizations that has a continuous improvement capability in place!

  1. Digital channel shift

Build on the “enforced” channel shift that many customers have experienced with the closure of physical stores and reduced capacity of contact centers, ensuring consistency of experience and supporting the capabilities to scale self-service and other digital channels now and in the future.

  1. The creation of a flexible, dynamic customer service organization

Develop an operating model that puts service-driven insight at the heart of cross-functional decision making. Learn from new, COVID-19-enforced ways of working and seize the benefits of home working, flexible workforce management, and new resource models.

Customer service teams are at a pivotal point between adapting for the current crisis while having the flexibility and capabilities to deal with life getting back to a new normal. Organizations that are flexible and scalable enough to adapt to future challenges, COVID-19-related or not, will be those that continue to thrive.

Authors

Ghislain Melaine
Paul Johnston Director, Customer TransformationCapgemini InventGhislain Melaine Principal Consultant – Consumer & Shopper Engagement LeadCapgemini Invent

The project economy requires investments by project managers to realize the future we want

Capgemini
February 24, 2021

Two years ago, the new CEO of the Project Management Institute (PMI), Sunil Prashara, qualified the world as “being projectified” and coined the Project Economy. The large change initiatives in organizations are managed with projects. IBM’s Cindy W. Anderson added in her article Welcome to the Project Economy (2019): “The projects in these organizations, and others, are being led by people with a variety of titles, solving a variety of problems in industries big and small, and across all regions around the globe. The Project Economy has room for all of them.”

In early February 2021, NK Shrivastava and Phillip George conducted a PMI webinar Looking Forward to Project Management in 2021 after a Turbulent 2020. The undoubtedly well-intentioned key trends, I believe, underestimate the real needs in the project economy.

  1. Project delivery will continue to be impacted by COVID-19
  2. Cybersecurity projects will be as important as ever
  3. Demand for project managers will increase
  4. PMOs need to innovate to stay relevant
  5. Design Thinking approaches will be integrated by project managers
  6. The use of Kanban will increase on projects
  7. Agile and DevOps approaches need to integrate further
  8. Quality engineering will take precedence over quality assurance
  9. Agile teams will be more distributed than ever
  10. Agile coaching and transformation services will rise

One project has come to a standstill due to the pandemic, while other projects have just started to solve emerging problems. How literal and wry is one person’s death, the other his bread. Think of the projects at pharmaceutical companies to bring a highly effective vaccine against COVID-19 on the market within a year, the projects to develop a Corona notification app, organize source and contact research, set up test and vaccination lines, or to organize corona proof in the upcoming parliamentary elections.

In projects such as the Dutch Corona notification app and the serious data breach in the application that the public health services use to register source and contact research, the importance of information security became painfully clear. The importance of cybersecurity may well have increased.

I recognize the increased demand for project management competencies, but do not see PMOs as independent entities that remain relevant through innovation. Apart from a PMO in 2017, I can easily do without it for two decades. Design Thinking is one described, simple technique to facilitate the divergence and convergence of ideas. The suggestion that project managers are going to integrate this technique (s) requires explanation and context. A key trend is an exaggeration in this.

Using Kanban and projects in one sentence makes you rethink your field of expertise. Kanban originated as a signaling technique in assembly line work in production companies. Bottlenecks, such as a machine that has come to a standstill or stalled, must be resolved as quickly as possible to resume the flow of continuous production. As a contrast to repetitive activities in the Operations of an organization, we realize in projects the new products, services, or processes that will change that. Not as assembly line work in accordance with a configuration script, but a risky temporary company that wants to get from A to B based on good or even emerging approaches and deliver the required results.

The call to integrate Agile and DevOps suffers from the same problem. Agile is an umbrella concept of frameworks, techniques, behaviors, and principles to make people, teams, and organizations agile in a volatile, uncertain, complex, and ambiguous outside world. A multidisciplinary team develops something. This can be done in many ways, for example with an agile framework such as Scrum. By subsequently asking the team to also take care of the management and maintenance of the delivered items, Dev(elopment) and Op(eration)s are brought under one organizational roof. If you have delivered a good product, you don’t have to worry about it much afterward. As the parties involved, you know the most about the product, so it is logical that you can and can also provide a next version, an improvement, or change. If you have delivered rubbish, you can also clean it up yourself. This can be about software, but also about renewing and managing a section of motorway.

Building in quality instead of testing is commendable. With more and more working from home worldwide during the pandemic, the claim that Agile teams (meaning: development or DevOps teams in organizations) are spread over the workplaces of all individuals involved is an open door. This does not go without a struggle, it makes a considerable appeal to the people who have to provide coordination, leadership, and integration and shows daily how much you miss non-verbal cues in communication and collective learning becomes a source of headache.

And yes, with all those organizations on the move to implement and improve agile ways to work (together), there is a temporary or permanent need for coaching and change management. I do not see the direct link with project management key trends.

Megatrends for project managers looking beyond the obvious

If you really want to contribute to a better, more beautiful, cleaner world, check whether your project actually means something for themes such as:

  • COVID-19
  • Climate crisis
  • Civil, civic, and equality movements
  • Shifting globalization dynamics
  • Mainstream Artificial Intelligence

These five megatrends described by Cindee Miller et al on PMI’s Voices of Project Management on February 11, 2021, may take place outside of your bubble. At major Dutch banks and top 3 insurance companies, we think that everything revolves around software, everyone works agile and project managers are passé. The fact that I provide monthly project management training on PRINCE2 via the Capgemini Academy raises questions. Is PRINCE2 still in use? So yes. Otherwise, organizations would have no need to let their people do this training (s) and pursue certification.

Admit it, on your resume it is more interesting to be able to report that you have made a significant contribution to one of the above-mentioned megatrends than just another back-office migration, implementation of pieces of legislation, or the revision of an online dialogue for the application of an insurance product or a loan?

What skills are needed now and in the future?

The British project manager, author, and speaker Peter Taylor distinguishes three types of project managers (I also wrote about it in 2019 and the words are in full force in 2021):

  • accidental project managers (through harm and disgrace, rolled into the emerging field more or less by accident. Peter Taylor is an example of this);
  • educated project managers (project management as an element in the curriculum, a career move, colleagues with the necessary training and practical experience. I am an example of this myself);
  • intentional project managers (students who already choose to become a project manager, immediately do major project management and are able to lead projects from their entry into the labor market. As a people manager and trainer I regularly come into contact with such ‘energetic folks’).

The September 2019 New Statesman published an article Investing in 21st-century skills. This taps into the intentional project managers and points out how to prepare young people for the project economy by engaging in technical and social skills, daytime practice at work, as well as in volunteering, and other out-of-hours projects.

I think it is cool to work with young people in their twenties who have already led projects with PRINCE2 in their training, have a master’s in Innovation management, or have already learned to deal with conflicts, lead teams, or presenting convincingly. I prefer to put them on the track to lead projects instead of wasting time on typical young professional roles at an IT consultancy company as a tester, junior business analyst, or project assistant.

Regardless of the type of project manager you count yourself on, it is important to remain relevant. In the promotional video of the project economy, the change “From frameworks to whatever works” comes over. For me, it typifies the transition of project management. Do not dig (too) long in the past if you are looking for the future of project management (such as John Verstrepen, Roelof van der Weg, and Ben van de Laar in The project manager in translation: looking for the future of project management, 2017). On the shelf with the professional literature, new books such as Psychological Project Management 2nd edition or Citizen Development: The Handbook for Creators and Change Makers would rather belong than the upcoming seventh edition of A Guide to the Project Management Body of Knowledge (PMBOK Guide).

Five principles on which to build your marketing ecosystem

Dr. Thomas Dmoch
Dr. Thomas Dmoch
February 23, 2021

Five principles on which to build your marketing ecosystem for simplified, more efficient customer engagement

Consumers today want a contextualized and personalized experience. They expect convenience and unlimited access, and they demand it in real time, 24/7. Data and digitalization hold the key for the CMO and marketing teams responding to this new world of real-time customer engagement.

With data captured at every customer touchpoint, marketing holds a treasure trove of customer insights based on tracking of audience media and consumption habits. Aided by the latest marketing technology (MarTech), it becomes possible to use data to identify and understand the context of each customer interaction with a brand across different channels. How and when do consumers search for a product, see what their peers are saying, get help, personalize their purchase, place an order, and demonstrate brand advocacy?

In our new point of view, we describe how these outcomes become possible in an end-to-end operating model within a connected marketing ecosystem. Under the CMO’s new ecosystem remit, we see sales, marketing, and service merging as customer requests become interdisciplinary. Commerce across digital channels also integrates within this ecosystem, so that any interaction or transaction with the customer merges into a seamless experience.

Introducing Connected Marketing

At Capgemini, we call this Connected Marketing – and digital must be part of this picture. It is an enabler of the five principles on which Connected Marketing is built:

  • Personalization
  • Relevance
  • Data-driven branding
  • Responsiveness
  • At scale.

These principles are key success factors for the marketing ecosystem. Here’s how we bring them together for our clients: Connected Marketing means customer activation by personalized, relevant, and brand-specific content and services, delivered in the right moment by a responsive, fast, and interdisciplinary organization that is able to scale through marketing automation based on the right platform.

An ecosystem approach built on these principles helps the CMO address changing consumer behaviors and expectations for a highly relevant, two-way dialog (ideally in real time) with the brands they love. It breaks down organizational silos to ensure previously disparate teams, functions, and agencies are able to deliver a personalized brand experience that is the same at every customer touchpoint while mitigating budget pressures. It removes complexity from fragmented vendor landscapes in volatile markets, enabling the CMO to focus on creativity rather than on managing supplier relationships.

Our new point of view looks in more depth at each of the five principles, describing what it takes to deliver them, and the value of getting this right. For example, data-driven personalized experiences along the entire customer journey that are relevant to both the brands and their customers enable marketing to build loyal audiences and communities of advocates.

Building Connected Marketing with MarTech

We use MarTech as the pillar on which to build our Connected Marketing offer. A platform view unites everything our clients need to manage complexity, reduce time to market, and ensure marketing is truly part of strategic growth plans. This extends from data capture systems, automation capabilities, and social media monitoring, to digital asset management, data storage, and data activation.

Ultimately, we bring together this technology with data and a brand vision to create and realize our clients’ strategies for delivering real-time experiences at scale.

Learn more about Connected Marketing

Download the point of view, Putting your customer first – Shaping a new era in personalized marketing. Get in touch with our experts to learn more about how we’re embedding brand-driven data and simplification in our Connected Marketing solutions and services.

Drones – the key to the future of predictive maintenance of powerline assets

Capgemini
February 23, 2021

Introduction

The ability to quickly identify emerging defects in powerline insulators is one of the key challenges of the power transmission industry. Conventional methods of powerline insulator inspection are costly, time-consuming, resource-intensive, and even risky. The transmission utilities must therefore replace outdated methods with faster, automated, more accurate, and safer modern methods of insulator inspection.

Breakdowns need to be reduced to a minimum as they severely impact revenue and customer experience

Transmission line inspections are carried out as part of both breakdown and preventive maintenance, to localize and assess fault severity . Traditional methods generally comprise visual walk-through or drive-by inspection using hand-held instruments. This process is generally time-consuming, leading to slower resolution of faults and defects. It results not only in lost revenue for utilities companies, but also adversely impacts customer experience. Also, line inspections are necessary before re-energization, for the safety of life and transmission assets in the aftermath of natural calamities, such as cyclones or storms, or during transmission system breakdown. Modern inspection methods are increasingly deploying drones or UAVs (unmanned aerial vehicles), which use high-resolution cameras to capture visual and thermal images.

Capgemini offers a robust solution for powerline inspection, leveraging drones, image analytics and seamless integration with SAP, SCADA, OMS & GIS

Capgemini’s E&U Industry hub has developed a unique solution for real-time monitoring, visualization, and analysis of powerline insulators. The solution uses high-end images of powerline insulators captured by drones and combines intelligent data capturing, cloud computing, deep learning and smart video analytics to detect insulator faults, such as developing cracks or structural deformities. It leverages 5G communication technology for real-time video streaming and image transfer, which accelerates defect processing and decision making.

The image analytics help O&M field crews develop maintenance strategies and use aerial data insights to proactively manage faults, thereby avoiding costly breakdowns, service breaches, and reputational damage to the utilities company. The analytics also helps quickly attend to defects and restore the system.

The key differentiator of the Capgemini solution is its seamless integration with transmission utilities applications such SAP, SCADA, OMS, and GIS. The solution has the potential to considerably improve the reliability of the transmission system through proactive fault management, which has a direct impact on the utilities’ revenue and maintenance efficiency, as well as regulatory and service commitments.

This solution can be extended to monitor other transmission line assets as well

The solution is scalable and can be extended to monitor not just powerline insulators, but also other transmission line assets, such as tower structure, conductors, joints, spacers, vibration dampers, and features including transmission line sags (ground clearance) and vegetation undergrowth. The solution provides transmissions utilities the following tangible and intangible benefits :

  1. Better situational awareness of powerline insulators and other network assets
  2. Enhanced personal and asset safety during transmission line inspections
  3. Condition-based predictive maintenance and faster defect restoration
  4. Optimizing maintenance strategy, resources, and operational expenditure
  5. Improved reliability and availability of transmission lines
  6. Compliance with health, safety, and regulatory performance standards
  7. Contribution to sustainability due to reduced breakdowns and losses.

Our drone-based analytics solution can also be effectively deployed for the inspection and defect identification of the water and gas utilities infrastructures.

To learn more about this solution or see it live in action, contact :

Bragadesh Damodaran, Director – Energy & Utility IndustryHub

Jayant Sinha, SME Energy & Utility IndustryHub

Amit Gupta, GIS Lead, Energy & Utility IndustryHub

Aniket Mahato, GTM Lead, Energy & Utility IndustryHub

AI is breaking through to HR

Marek Sowa Head of Intelligent Automation Offering & Innovation, Capgemini Marek empowers clients to revolutionize business operations with AI and RPA. He aids Fortune 500 companies in creating scalable, high-performance automation solutions that enhance efficiency, employee satisfaction, and transformation. His current role involves shaping market-leading offerings, GTM strategies, and aligning global services in the Data & AI portfolio. Marek also manages product design, sales enablement, marketing alignment, and market adoption.
Marek Sowa
February 22, 2021

Most organizations receive hundreds of curriculum vitae (CV) documents on a daily basis from which they have to process the right information required to coordinate the recruitment process efficiently and effectively. However, they typically work with outdated, time-consuming, and labor-intensive recruitment systems, which are prone to errors, delays, and low employee satisfaction.

At Capgemini, our human resources (HR) leadership understood the impact intelligent automation and artificial intelligence (AI) could have on the efficiency of the recruitment process and engaged a team of advanced technology experts to develop an end-to-end, frictionless solution called CV-up Powered by Artificial Intelligence.

Bringing AI to HR

This joint effort enabled us to look at it from the business perspective and use state-of-the-art capabilities and natural language processing (NLP) to tell each individual applicant’s overall story. More importantly, this innovative approach enabled us to develop a tool that ensures HR team members focus less on making sure applicants fill in all the fields correctly and more time interviewing candidates and ensuring they get the right candidate for each role.

By putting our collective minds together, we were able to develop a way to make the data extraction from CVs more intelligent by focusing on the way language works within CVs, and other business texts, to enable specific data processing. This works primarily through crucial phrase extraction, NLP of raw text, and named entry recognition. By reducing the likelihood of human error, CV-up Powered by AI enables our HR department to concentrate on more meaningful tasks and the application process’s human side.

In addition, thanks to the application’s ability to leverage its agile cloud-based architecture and cognitive services, the tool can also be used for other documents such as agreements, contracts, and forms.

Recognizing innovation in AI

Our hard work and innovation have certainly paid dividends. Building on our success at last year’s AI Breakthrough Awards for a cash collections assistant powered by AI, we were ecstatic to learn that Capgemini has again been recognized as a leader in AI technology, this time using AI to bring the human touch back to HR. CV-up Powered by AI has also been recognized by the Business Intelligence Group at their BIG Innovation Awards given to companies or individuals whose ideas, big or small, that change the business world. We couldn’t be more thrilled.

This was truly a collaborative effort between HR and the Advanced Technology Lab in attempt to find an innovative, frictionless solution to an age-old problem. By augmenting the recruitment process with AI, we’ve enabled our recruitment teams to get back to doing what they do best, filling open positions with the highest caliber talent available.

CV-up Powered by AI is part of Capgemini’s Intelligent Process Automation (IPA) offering and Connected Employee Experience portfolio. To learn more about how IPA can help your HR function streamline its recruitment process, ensuring you get the best talent for each role, contact: marek.a.sowa@capgemini.com

Marek Sowa is head of Capgemini’s Intelligent Automation Offering focused on adopting AI technologies into business services. He leverages the potential hidden in deep and machine learning to increase the speed, accuracy, and automation of processes

Artificial Intelligence: With great power comes great responsibility – Part 2

Capgemini
February 22, 2021

As concluded in our previous article, Artificial Intelligence is a game changer.  It is hard to find a sector or organization that would not benefit from AI. At the very least AI can be instrumental in optimizing existing business processes, saving costs and increasing revenues. But it can also be used to come up with new business models. Uber, Booking.com and Deliveroo are some of the companies that have redefined their sector by using AI. We now have the means to continue on the promising AI journey, and have to follow the right approach to change the game. But what is the best way to start and to accelerate? In this article will deep dive into the factors that will enable an organization to implement and prosper from having an AI function.

Purpose, commitment & maturity

Starting point of the AI journey is to clearly understand the purpose of AI in your organization: what is the reason you want to apply AI? What is the intention with AI you abide and commit to? What is the long-term goal that is both personally and organizationally meaningful, and makes a positive mark on your customers and the world? Time and again during your journey this will both be your compass and benchmark by which you navigate your efforts.

Important in the AI journey is that it has to be continuously supported by C-level. This is not only essential during setup, but also to continue and scale the AI effort. C-level commitment ensures proper attention and funding, and it can prove to be instrumental in overcoming resistance to change and surviving the occasional road bump.

It must be clear by now that here is no successful AI without properly involving people. An important part of the organizational change is about making sure that your employees accept and trust the changes involved so they are better able to deal with this. Another part is the reskilling and upskilling of employees so that they are better able to play their part in the AI journey.

While understanding the goal, securing C-level commitment and addressing organizational change are obvious components of a successful AI journey, using AI maturity models is as important. Using a maturity model helps you understand your current position. In doing so it clarifies the challenges ahead and the next steps. To put it different: it guides your ambition. Before you can run, you need to be able to walk first. Understanding your starting position helps in finding and applying the best practices from organizations that are leading the AI journey – for your current maturity level. Best practices are not a standard recipe that you just need to follow, but it will tell you some of the essential ingredients needed for your own version of AI success.

In general maturity models distinguish five phases. When you focus on organizations that have actually started on the AI journey and disregard the last phase (Phase 5 in which organizations continuously reinvent and reorganize themselves based on AI outcomes – most would have not already achieved this), it comes down to the following phases:

  1. Orienting, learning on AI and how to start
  2. Pilots/Proof of Concepts launched, but not yet deployed in production
  3. Few use cases deployed in production, but on a limited scale
  4. Successful deployment in production and continue to scale

A survey by Capgemini Research Institute shows that during 2017-2020 the number of organizations moving beyond pilots and Proof of Concepts increased from 36% to 53%. The same study shows that sector wise the life sciences, retail, consumer products and automotive are ahead in terms of AI implementation with a range of 17 to 27%. This outperforms the global numbers where 13% of organizations have AI in production and scaling, 40% have implemented some limited AI applications and the remaining 47% have yet to leave the pilot/PoC phase.

How to move ahead

AI is a process and it needs to be handled as such. The technical part of AI is important, but by no means is it the complete picture. Take into account that crossing the chasm from AI prototype to AI at scale is a common challenge, so prepare bringing ideas to production from the first step in your AI innovation processes.

When moving ahead, one important decision is how to realize your AI capabilities: build or buy. Do you have (or make) the time to build inhouse capabilities and putting together teams of data scientist, ML Engineers and others or are you opting for a quick start by purchasing solutions in the market.  Also consider working with your partners on AI and leveraging each other’s strong points. One consideration worth making is setting up a hybrid AI ecosystem where you use external data and AI models to enrich your internal data and AI models.

Adopting a cloud first approach to AI is quickly becoming the way to go, even when requirements are still unclear. Cloud Machine Learning (CML) platforms such as AWS ML, Azure ML or Google Cloud ML (TensorFlow) can power the ML models that you are creating. There are also many AI cloud services available that you can tap into. In addition to the extensive availability of rich AI functionality it brings, cloud is the only sensible way to scale.

Infusing AI while the store stays open

Any innovation with AI should have a positive business case, either quantitative or qualitative. Driving AI by means of a business case ensures that it does not fade away as an expensive hobby or solutionism, where it’s solely about having an AI project without any concrete game changing factor. Consider applying a self-funding approach: reinvest benefits achieved by applying AI in the further innovation with AI.

When applying AI to improve existing business processes, ensure that both the data and models are treated as the enterprise assets they are. Areas to take care of are at least: clear ownership and governance, version management and automated testing and deployment. AIOps/MLOps – inspired by the successful DevOps paradigm – have proven to be a valuable approach in managing AI.

Trusted. Data.

AI is powerful, yet also surrounded by controversy. This implies that AI has to be used in a responsible and ethical manner, where explainability and fairness have to be paramount to profits and growth, and because you want to prevent unintended consequences or failures. And maybe even more importantly, you want to avoid AI rejection by important stakeholders like users, clients, citizens, employees, sponsors, shareholders and regulators. The assessment list for trustworthy artificial intelligence (ALTAI) provided by the European Union can act as a guideline for self-assessment in this area. Ethical principles have to be woven into the AI fabric of your organization. Not only to ensure the application of AI adheres to these principles, but also as a message to the outside world that you understand the concerns and powers surrounding AI and are taking it very seriously The goal here is build an ethical AI capability, supported by frameworks and tools. In many sectors and organizations Code of Ethics are put together that support and strengthen the emergence of ethical AI.

There is no intelligence without data at scale: models need data for food, lots of it. Data is both required to train your AI models and to feed them while they are used in production. This means data quality is a critical factor in the performance of your model. Yet data can bring about another risk: bias. If you train your models with biased data – this can already be the case by just using your historic data – there is a fair chance that the outcomes of the models are also biased, resulting in reasoning errors and unintended consequences. If you have lots of personal data, privacy considerations can limit the use of data and working with synthetic data or masked data can help.

AI benefits from a data centric architecture, where data has been organized in its own right and not as a byproduct of applications. In such an architecture AI can access all required data without friction, and there is a continuous flow of data to AI models like water running from a tap. Looking beyond the walls of your own data to the outside world is another must-do. It contains a huge wealth of data that can be leveraged to boost the value of your AI models, and ultimately boost the value for your stakeholders.

Conclusion

The journey towards successful implementation of AI is not easy, but it can be highly rewarding. Starting it off with purpose, commitment and a business case focus is essential. Having a solid and trusted AI innovation and operating model is important to continue to channel the energy in the chosen direction while continuously building on the support of both the governance and the workforce of the organization. In a subsequent article we will discuss proven AI patterns that can be leveraged to accelerate the value and scale of AI, without reinventing the wheel.

This blog has been co-authored by Erwin Vorwerk and Paul van der Linden. Please reach out to the authors for more information.

The autonomous supply chain – the road ahead

Capgemini
February 22, 2021

In this short series of articles, we’ve been looking at the supply chain challenges organizations typically face, and the extent to which they have been complicated by current pressures. We’ve also outlined the characteristics and benefits of the autonomous supply chain.

In this, the third and final article, we’re going to assess the current climate for the adoption of this approach, at critical success factors, and at the support an external services provider can give.

Key focus areas

In previous articles in this series, we’ve already seen indications of a business appetite for the end-to-end visibility that the autonomous supply chain can provide. Indeed, in a recent report conducted for Capgemini by NelsonHall, we learn that roughly a third of enterprises (34%) plan to undertake significant autonomous supply chain initiatives over the next two years. These initiatives can be broadly grouped into three areas: planning and forecasting, supply chain optimization, and supply chain execution.

Within these three areas, the functions on which survey respondents were most focused included:

  • Supply forecasting (40% of respondents) – obtaining more data from key suppliers to enable longer range planning
  • Demand forecasting (32%) – using wider sources of information such as social media, and increasing campaign integration with major retailers
  • Warehouse optimization (22%) – fully automating orders, right through to depot picking and dispatching. Also, moving raw inventory on plant pull signals with no manual interventions
  • Consignment tracking (52%) – implementing real-time tracking on more raw inventory for greater overall improvement of the supply chain. Also, simultaneously improving customer satisfaction and reducing inbound service inquiries, by using machine learning techniques to track data supporting logistics movements, and then proactively providing that information to customers.

Partnership criteria

The supply chains of major enterprises are so large and complex, and their role is so crucial, that it’s no surprise to find that, according to the survey in the NelsonHall report, 84% of organizations will involve vendors when implementing autonomous supply chain initiatives. So – what should you look for in their potential partners?

Perhaps, needless to say, it’s important to work with service providers with both the consulting and operational supply chain expertise to reimagine and deliver supply chain transformation projects – and who are also able to address your organization’s own global scale of operations.

Less obvious, maybe, is that this process knowledge needs to be matched with substantial experience of automation and analytics. For example, machine learning and deep learning technologies are rapidly becoming essential in the supply chain’s ability to become touchless and autonomous. To demonstrate relevant experience in these areas, potential partners should be able to show they have developed best-in-class solutions based on integrated combinations of process models, industry platforms, and automation technologies.

Critical success factors

There have always been significant and complex demands made of enterprise-level supply chains, and the COVID-19 pandemic has increased the pressure for them to deliver – both figuratively and literally.

There are several key elements for success:

  • A staged approach – it’s a good idea for the overall strategy to involve a series of linked short-term projects, each delivering demonstrable returns on investment (ROI) in the near term
  • A pilot program – each of these stages should be piloted, so as to provide a working prototype that addresses all the issues that have arisen along the way
  • Leadership buy-in – continuing to demonstrate ROI will maintain senior support for the transformation, and this, in turn, will help to keep things moving through to completion
  • External buy-in – trading partners need to be on board, too
  • A good team – the people implementing the program are likely to be a mix of internal personnel and those from vendors and service providers. They need to have relevant complementary skills and experience, and they also need to work together well, and towards shared goals
  • Good data – legacy systems and manual processes present problems. The prospect of tackling them is daunting, but the main lifting and shifting will with luck be a one-time fix, and the results will be worth it
  • Continuous improvement – addressing the major legacy and manual issues may largely be a one-off, but transformation as a whole certainly isn’t. An autonomous supply chain, and the Frictionless Enterprise of which it is part, have versatility and flexibility in their DNA.

Experienced service providers will of course be part of the good team on this list, and they will be able to help ensure you address all these factors efficiently and effectively.

To learn more about the autonomous supply chain and its role within the Frictionless Enterprise, read NelsonHall’s full report “Moving to an Autonomous Supply Chain: An Essential Guide for Manufacturing & CPG Firms.”

Read the “Fast Forward: Rethinking supply chain resilience for a post-COVID-19 world” report by the Capgemini Research Institute (CRI) to understand how you can future-proof your supply chain for a post-COVID world.

Finally, to learn about how Capgemini’s Digital Supply Chain practice  can help your organization build a resilient, agile, and frictionless supply chain, contact: dharmendra.patwardhan@capgemini.com

Read other blogs in this series:

Dharmendra Patwardhan is responsible for developing offers and capabilities for transforming supply chain operations that drive tangible business outcomes for Capgemini’s clients.