For the past several decades, telecom operators focused primarily on connectivity, with end-user devices consuming network resources. However, the landscape has since evolved, with a significant amount of content now generated by applications such as over the top media services (OTT), direct-to-consumer platforms, and other media services.

To stay relevant, operators must pivot towards providing value to content creators, which entails offering insights derived from the network to these applications. This shift requires implementing software-defined interfaces and adopting a consumption-based business model.

Further, Telcos’ software strategies extend beyond network virtualization or softwarization. Rather, it encompasses the entire stack, from networks all the way through the customer experience. In taking a more holistic approach, operators can benefit from faster time to market, proactive service provisioning, automation, autonomous networks, precise asset management, and digitization of customer services.

In our most recent research, The art of software: The new route to value creation across industries, we explore the shift from Telco to Tech Co. and the specific role of software in this evolution. In this post, we present three key takeaways from our research, as well as our own expert insights, that highlight how Telco companies can prepare for and lead the way to a software-driven future.

3 ways Telco organizations can prepare for a software-driven future

1. Accelerating the shift to cloud native

To be a software-driven business, Telcos must also be a cloud native business. This point has become non-negotiable as most, if not all, new network elements and equipment demand a cloud native foundation. This means that companies across all subsectors of the industry must possess the capability to develop cloud-native software, implement robust tooling, automation, CI/CD pipelines, and other essential components inherent to the cloud-native model.

The cloud is also a key to developing and scaling software-based services, which is a critical revenue driver in the Telecoms industry. In fact, our research shows that Telco executives, as a group, expect to see the highest increase for the share of total revenue by software by 2030 (39% for telecom vs 29% average). For companies that expect to tap growth lines outside core telco services—be it through cybersecurity, IOT solutions or edge services—they must become cloud native.

2. Leveraging the power of AI to scale.

Current network automation solutions often operate in silos, with custom automation resulting in a “spaghetti integration.” Intelligent inventory management and automation can address this challenge by effectively managing dependencies across network assets.

Adopting a software-driven approach enables telcos to scale and extend automation capabilities, accommodating new generations of connectivity technology seamlessly. This approach offers various benefits, including reduced total cost of ownership (TCO), accelerated innovation, and avoidance of vendor lock-in.

AI is instrumental in realizing this vision, alongside other software-based automation approaches such as rules-based, model-based, and ML-based automation. As such, Telco organizations are not only required to significantly expand their technical workforce but also build teams equipped with a profound understanding of AI, data consumption, and the ability to craft software snippets that facilitate automation.

3. Creating a strong culture of collaboration and transformation

Though it may seem counter-intuitive, at the heart of every successful software-driven business is not simply great technology, but an excellent experience. To deliver on this front, companies need to understand their customers, their needs, their challenges and the context in which they operate.

For some Telcos, shifting to software means becoming a true customer-first business. This involves seamlessly integrating various aspects of the service, from network infrastructure and product development to service and marketing, all orchestrated with the primary goal of delivering an exceptional customer experience. This requires a fundamental reimagining of how teams operate, the talent they attract, retain, and nurture, and an ongoing focus on continuous product development and operation.

Finally, it will be nearly impossible for Telco organizations to make this journey alone. Another key finding of our research is that success requires an ecosystem approach, bringing together multiple stakeholder groups, such as chipset providers, hardware and sensor vendors, cloud and platform providers, connectivity providers, testing and others, to assemble the necessary expertise and capabilities needed to take full advantage of the benefits of software-driven transformation.

Reclaiming the innovation story: How Telcos can kickstart their softwarization journey

While many Telco organizations have significant work ahead to become software-driven companies or build the maturity of their business models, the upshot of our research is that they are hardly alone in the struggle: Only 29 percent of organizations across industries have started to scale and utilize software to drive transformation – with only 5 percent fully scaling identified use cases.

The rest of companies, and likely many Telco organizations, find themselves squarely in the experimentation stage, identifying application areas/use cases or implementing pilots/proofs of concept (PoCs). This means that there is still ample time to start the journey and shape the future.

That said, we must remember that when it comes to technology, the future moves fast. Telco companies have time to act, but not time to wait.

Are you ready to take the next step towards a software-driven future? Download our recent report, The art of software, and schedule a consultation with our authors to start your journey from Telco to Tech Co. today.

TelcoInsights is a series of posts about the latest trends and opportunities in the telecommunications industry – powered by a community of global industry experts and thought leaders.

In the first blog of this three part series, you learned about the importance of order management to supply chains, and how the order management process can be improved.

In this blog (part two) you will learn about Supply Chain Quality Management – what it is, how it works and why it matters.

Quality problems in the supply chain: a hypothetical example

A retail company has been experiencing a surge in customer complaints about a particular smartphone model they sell. Customers report issues such as malfunctioning screens, battery failures, and overheating problems a few months into using the phones.

Upon investigation, the company discovers that the defects stem from components supplied by one of their overseas vendors. The vendor, located in a different country, has been struggling with quality control issues in their manufacturing processes. However, due to the lack of robust supplier quality management procedures in place, the retail company failed to identify and address these issues promptly, and now struggles to find an alternative, more reliable source of components.

The importance of supplier awareness

In manufacturing, an average of 80% of a product’s value comes from suppliers.

Mastering supplier management (and thus the quality of supplier goods) is critical for all organizations with a supply chain – especially in this era of global disruption and uncertainty. This involves mitigating supply risks, which is in the DNA of the Supply Chain Quality Management (SCQM) team – whose job it is to provide a situational awareness picture of the supply chain, as well as provide steps to solve the many problems that can occur.

To this end, businesses need a robust action plan that contains, for example, a set of quick containment actions that support quality control or complaint management. One way to support this is through the Eight Disciplines (8D) approach. Originally developed at Ford Motor Company – this methodology can be used for supply chain problem identification and solving.

For a company, being able to regularly assess its global supply chain is the first step in properly monitoring (and understanding) the global manufacturing capabilities of its suppliers. This understanding allows companies to, for example, pre-empt critical component shortages by changing the manufacturer for a specific part. To this end, we implement various specialized audit methodologies (eg. VDA6.3 and Aero Excellence) that provide detailed insights into the quality of your supply chain, and that leverage best practices from several industries.

This methodology allows us to identify individual patterns – but also global ones. For example, we recently performed a complete assessment campaign for one of our clients, in which we audited more than 200 suppliers in 35 countries over 17 weeks.

From this snapshot, we are able to create a supplier development program using robust methodologies initially developed for the automotive industry, but that are today widely applied in other sectors, such as Advanced Product Quality Planning (APQP). We can also create entirely bespoke audit methods for clients.

‘Rightshoring’ for your supply chain

Rightshoring can be defined as locating a business’s manufacturing in areas that provide the best combination of cost and efficiency. To help our customers succeed with this approach, we rely on our ‘rightshore vision’. This leverages a network of 2500+ experts across the world.

As part of this vision, our local consultants and audit teams quickly get to work on client premises, reducing travel time, costs and project eCO2 emissions. We interact, if possible, with suppliers in the local language – streamlining remediation. Through this rightshoring approach, we have demonstrated a reduction of 60% eCO2 when compared to the traditional approach of European experts traveling overseas.

As is very clear for anyone who has bought an item that did not deliver upon expectations, quality control is essential. And it is increasingly important, the more complex that products become – as more components means more points of failure.

As electronic goods become increasingly complex, and as supply chains continue to endure geopolitical instability – SCQM, and the people who do it, will be more important than ever.

In the third and final part of this blog series, you will learn about the importance of sustainability in supply chains, and what steps you can take to make your supply chains more sustainable.

If you are currently facing delivery disruptions, or if you need to ramp up your supply chain to meet changing demand, we can help. Capgemini has years of experience helping companies across sectors and countries with supply chain quality management, along with access to some of the world’s leading experts in the subject. To find out more, contact our expert .

Generative AI (GenAI) is beginning to transform many activities, and product support is no exception. Product support is vital for the ongoing function of all products, from Microsoft Office to niche robotics systems. Users need product support when installing systems, integrating with other software, working out how to use the product, and resolving issues when they arise. 

Such work must be handled by experts who understand the product and its operation. The cost of this support must be factored into any product cost model, so improving the support process can unlock revenue by extending the life of products while reducing the costs of supporting them. This is particularly true as products reach “end of life”, when user numbers often shrink, and support costs relative to revenue can become problematic.

The potential of GenAI in product support

Because GenAI can process information and predict the answer to a question based on experience, it opens a world of possibilities for product support. Given sufficiently large training data of good quality, GenAI can be taught about the fundamental nature of systems and predict the most appropriate answers to questions about them. A few examples of GenAI’s potential uses in product support are developed below.

• Tech support automation: GenAI’s ability to learn answers to common technical questions about problems and provide quick and detailed responses means such a service can be available 24/7. Further, GenAI responses can be adapted to the specific user query and context. This approach is an important improvement on the typical support model, based on asking a series of fixed questions and pointing the user to an off-the-shelf ‘how-to’ article.
• Augmenting human support workers: GenAI can facilitate the work of human support workers by summarizing requests and providing these workers with the relevant information to solve these requests quickly. If support workers respond by email, GenAI can help them turn their response into text that will be easier for the user to follow, based on the GenAI model’s technical knowledge. It can also translate responses, allowing teams to offer support, even when they do not speak the user’s language.
• Onboarding new hires in the support team: A support GenAI can be used to train new support engineers on common product issues.
• Software product upgrades: Generative AI can be used by support engineers to facilitate software product upgrades, for example, translating software code into a newer language or modifying code to be more efficient as part of a green code sustainability initiative.
• Streamlining processes: GenAI tools can automatically categorize emails and support tickets and learn to prioritize in order of importance, assigning these to the relevant experts or those with the most capacity.

A well-composed suite of GenAI-powered tools can reduce time-to-solution, human error, and product support costs and so allow experts to focus on the more complex tasks that humans are best suited to.  

GenAI in product support – the art of the possible

Theoretical possibilities are all well and good, but what is happening in the real world? Capgemini is fortunate to have worked with multiple clients on projects to create value by harnessing GenAI in their product support processes and systems.

In one example, a large computer hardware organization wanted a system to identify multiple ticket types, handle initial conversations with users, and respond in various languages. The GenAI system we developed provided the firm’s customers with step-by-step instructions on how to resolve their queries. These responses were based on information in product knowledge bases and user manuals. It also identified user queries that couldn’t be solved using this approach and then escalated them to human support engineers. Finally, the GenAI collated user feedback and used this to propose updates to the knowledge base. The outcome was considerably fewer tickets routed to human agents, saving time and money.

In another case, we worked with a Network Equipment Provider to develop a chat assistant to provide ‘human-like’ first-level responses and summarize tickets for efficient handover to other support staff. Again, we saw reduced operational costs and improved SLA (Service Level Agreements) adherence in their 24/7 operations.

In a final example, we built a do-it-yourself (DIY) tool and analytics generator for a leading telco. They needed to document the standard operating procedures (SOPs) of their support engineers for future training and generate role-based visualization and prediction. The customer required a centralized management dashboard that unified all IT platforms on a single pane and a GenAI-based tech stack for predictive and preventive monitoring. 

The challenges of integrating GenAI in product support

Developing, deploying, and running GenAI-powered systems is becoming ever more accessible, thanks to the increasing availability of large open-source language models. However, care needs to be taken when integrating AI into systems.

Firstly, GenAI must be carefully crafted and trained for the specific use case – using up-to-date, high-quality data. The AI will be wrong if the user manual or knowledge base is wrong. This means that people who understand the product for which the GenAI support system is being developed must be involved in designing and testing it. They must ensure it has been trained correctly. Because GenAI is probabilistic, GenAI outputs can occasionally be wrong; this is often described as a ‘hallucination’ in the GenAI community. Consequently, quality control is vital.

Secondly, there are IT practicalities to consider. The IT infrastructure must offer sufficient computational power to run a GenAI model and provide the connectivity needed for the GenAI to interact with knowledge management databases and issue management systems (including email, WhatsApp, etc.). There must also be a single source of truth so that any updates to the knowledge base – by humans or AI – feed into the GenAI’s model of the world. Organizations must be willing to share this data, regardless of its sensitivity.

Finally, GenAI project timescales need to be calibrated to the business case. Training takes time, but no business wants to wait a year for a perfect GenAI support system that will be obsolete when launched. An AI that can solve 50% of queries and refer the rest to humans but takes three months to build and deploy may offer better value than one that can solve 60% of queries but takes two years to deliver.

Ultimately, the recipe for success with support systems is the same as most data projects. Set clear goals and expectations. Work with experts who know the tech and the domain, and use frameworks that allow you to move efficiently through the development process.

Capgemini has multiple software frameworks and project blueprints to accelerate the development, deployment, and operation of GenAI in product support systems. Contact our experts to learn more.

“Good companies manage Engineering. Great companies manage Product”.

– Thomas Schranz

Semiconductors are the backbone of modern technology, playing a pivotal role in virtually every aspect of our daily lives. These tiny electronic components – which manage the flow of electric current in a device – can be found in everything from smartphones and LED bulbs, to cars, kitchen white goods and medical devices.

Looking ahead, the importance of semiconductors is only expected to grow as society becomes increasingly reliant on digital technologies. The rise of the Internet of Things (IoT), autonomous vehicles, artificial intelligence (AI), and 5G networks all require sophisticated semiconductor technology. These advancements require faster, more energy-efficient, and smaller semiconductors to accommodate the ever expanding demands of a digitally connected world.

As such – semiconductor manufacturers must produce more efficiently, meeting the ever increasing need for ‘smaller, faster, cheaper’, whilst maintaining margins, and dealing with fluctuations of demand and uncertainty of supply. Because of this, it’s increasingly evident that these companies need to better manage the requirements of the semiconductor chip product lifecycle – eg. the mix of chip complexity and the need for specialized ‘mission-specific’ chips, regulatory constraints, and various other challenges. This will allow companies to gain R&D, operational and margin efficiency, and decrease their time to market – largely by enabling digital continuity across their systems.

Below we outline major trends affecting the semiconductor industry which, due to the impact of semiconductors, also have broader global significance.

Semiconductor industry trends

• The growing importance of ecosystem partnering and selling across vertical industries: Proof of functionality and new next-gen technology, for example, AI, Metaverse, 5G, and Edge, are driving partnerships across the semiconductor ecosystem to address end markets with complete end-market platforms.
• 5G is accelerating the pace and possibilities of connectivity – and the use cases it enables: Next-gen connectivity is evolving, from wired and wireless networks to private 5G, which is revolutionizing use cases across a wide range of industries.
• Verticals are bringing chip design in-house: Semiconductor manufacturers are losing share to a growing number of product/system companies, which are designing chips in-house for use in their own products/services – allowing them to disrupt, differentiate and control the supply chain.
• The steady shift towards ‘Industry 4.0’ and fully automated manufacturing – Digitization is creating an array of challenges (and opportunities) related to collecting, managing, processing, analyzing, visualizing, and effectively utilizing data – a microchip-hungry endeavor.
• Increased product innovation and reimagined customer experiences – An increased focus on co-innovation and co-design with the goal of establishing digital continuity and a single source of truth (SSoT) for all product data. The intent is to accelerate product innovation and consequentially delight customers.
• The value of Moore’s Law diminishing: Semiconductor manufacturers competing on performance, power, and area (PPA) seek creative ways to achieve a competitive advantage, while others add value by producing customizable modular chips called ‘chiplets’ that can be combined to form a complete system-on-chip (SoC).

Why is digital continuity important to the semiconductor industry?

‘Digital continuity’ is an organization’s ability to maintain (and put to use) important information, despite ongoing changes to the organization’s ways of storing data, and relentless evolutions in digital technology. This allows an organization to connect the ‘digital threads’ (information flows) of this data across its systems. Through this intelligent information sharing and monitoring, digital continuity helps the company and its ecosystem to operate more efficiently.   

The ability to manage information will be a competitive differentiator. Success for companies that produce these chips will depend upon these companies achieving a faster time to market with a ‘first time right’ approach. Geopolitical changes and challenges (eg. certain countries ‘reshoring’ the production of core semiconductors for national security purposes) will continue to force the localization of production, and these new greenfield plants will only be able to meet the required pace with the right PLM backbone and digital continuity foundations.

The previous approach to development, ie. using custom homegrown disconnected systems, results in misaligned technical investments and technical debt – namely the accumulated cost of shortcuts taken during software development, creating increased complexity and maintenance efforts over time.

The traditional document-centric development approach often does not allow traceability between requirements, product design, or the front and back-end manufacturing of products. This loss of traceability creates additional costs, quality control issues, compliance risks and sustainability overheads for enterprises.

As such, there is a clear need for an industrialized PLM backbone that provide a single source of truth (SSoT), offering consistency, accuracy, and reliability in the use of data and information across all departments and processes. In addition, rapid integration into end-user product ecosystems (which is required to meet the competitive pace of business today) requires the use of simulation and model-based approaches.

What features would such a PLM backbone require?

• A complex hierarchical data model: Allowing oversight of variables like chip order part numbers and customer part numbers. It could also manage complex chip design, development & verification and tapeout, as well as finalize die designs. Other capabilities would include register-transfer layer (RTL) design, GDSII data management, mask set management, along with control over reticles & die variants, wafer fabrication & sort – and, ultimately, the chip assembly process to the final product.
  
  • This data model would also address product complexity and technology development needs for the data models that are used by downstream systems to design and manufacture products. These include engineering bills of materials (EBOM), manufacturing bills of materials (MBOM), and production bills of materials (PBOM).
• Management of new product introduction (NPI) programs and product portfolios: Meeting the need for new markets, changing consumer demand and emerging technologies.
• Integrated fabless and foundry management: Once designs are ready to hand over to approved foundries or to outsourced semiconductor assembly and test (OSAT).
• IP management: Providing integrated IP reuse that is controlled and secured. Transparent IP management increases efficiency in R&D, operations, and margin efficiency – whilst avoiding the risk of IP infringement.
• Product sustainability and environmental compliance: Offering integrated material substance declarations and compliance checks for Integrated Device Manufacturer and Original Design Manufacturer compliance management. Ultimately, this can help to increase the effectiveness of semiconductor equipment, moving us towards the future of sustainability compliance in the factory.   

With all the above, the semiconductor industry is looking to build integrated close-loop quality system tracking into its design and manufacturing processes.

An opportunity, for those with the means to seize it

Once the hard work has been done to establish digital continuity across an organization’s many systems, companies can expect increased efficiency in R&D, operations and margins, decreased time to market and, of course, a significant competitive advantage.

Semiconductor manufacturers today have a major opportunity to support the next generation of technology, but will only be able to properly exploit it with the kind of digital continuity that sophisticated PLM provides.

Capgemini’s world class team of semiconductor industry experts is ready to help you build a next-gen secure, intelligent PLM backbone for your semiconductor business.

Our VLSI practice experts be an integral part of your team, working closely with your business product managers and fab leadership team. We also offer pre-configured semiconductor solutions and accelerators for PLM, MES, and ERP triptych products – to help you bring everything together.

Ready to progress, or want to learn more? Meet our experts.

What do these three very different technologies all have in common – generative AI, 6G mobile networks, and autonomous vehicles? Clearly they are all exciting, but they also all rely on the science – and the magic – of advanced processors. GPUs (Graphics Processing Units) are a member of this family; a family which boasts sophisticated architectures and exceptional miniaturization, enabling high performance for massive data processing while balancing size, speed, and energy efficiency. But are we in danger of taking this incredible technology for granted?

The journey of GPUs from the 1990s to today is a tale of innovation and competition. Initially designed to enhance gaming 3D graphics, GPUs have transcended their original purpose. Thanks to their powerful parallel processing abilities, they now play a pivotal role in artificial intelligence and deep learning. Today, GPUs have transformed from specialized gaming hardware to indispensable tools that enable cutting-edge technology and underpin critical day-to-day services.

Europe’s position and challenges

Despite the critical role of GPUs, Europe finds itself behind in the manufacture of these essential processors.

High costs of cutting-edge semiconductor manufacturing technology limit GPU production to just three global players, and Intel is the only one considering production in Europe by the end of the decade. However, the design of GPUs is as crucial as their production and offers a way for Europe to regain some sovereignty in the market. Once the design of a processor (its system architecture and key intellectual property blocks) is mastered, it is technically possible to have it produced anywhere. In terms of sovereignty, this offers freedom. That’s why Europe must design its own advanced processors, even if it must depend – and it has no choice in the short term – on non-European manufacturers.

Recognizing this, global tech giants and countries around the world are investing heavily to quickly design alternatives and take back control. Yet Europe is not currently part of this effort and until it enters the fray, the gap with the rest of the world will continue to widen.

Envisioning a European GPU

Designing a European GPU is therefore a strategic necessity. The European industrial fabric (health, defense, aeronautics, automotive, telecoms, data centers) cannot depend on a single source of supply – especially one outside the region. But it is a challenge that requires significant investment estimated at several billion euros over several years. This is not just to catch up, but to ensure a diverse supply chain for critical technology.

The focus of this investment is not only on creating a GPU, but on developing a complete advanced processor with a heterogeneous architecture combining different functionalities for efficiency (though the modular ‘chiplet’ approach also offers interesting possibilities). Progress has already started across Europe. France, Germany and the Nordics have already taken steps towards this goal, benefiting from collaborations with global tech firms like Thales, and smaller specialists such as Kalray, SiPearl, VSora, GreenYellow, Menta, Scalinx, GrAI Matter Labs, and many other leading lights in the world of CPU and accelerator technologies. Capgemini, following the acquisitions of Altran and HDL, is now Europe’s leading silicon engineering services company and can drive this project forward. Leading forces across the continent have never been brought together for a common sector project like this. Combined, they give Europe the foundational elements that, if properly assembled, could constitute the embryo of a sovereign advanced processor, potentially rivalling non-European tech giants in the long term.

A unified industrial vision

The realization of a European GPU hinges on aligning European stakeholders around a common industrial vision. This involves a coordinated effort to define a unique architecture, development roadmap, software environment and ecosystem, and market strategy, supported by both the state and private sector investment.

A rapid task force could kickstart this initiative, outlining a political and industrial framework within three months. This would catalyse collaboration among industrial clients and technology providers, addressing Europe’s pressing needs for digital sovereignty and technological independence.

In summary, developing a European GPU is not merely a technological endeavor but a strategic move towards securing Europe’s position in the global tech landscape, paving the way for technological sovereignty and innovation. This will ensure Europe can continue to enjoy the current and next wave of exceptional technologies that have the ability to change the world in which we live and work.

This is the first in a short three part blog series that explores supply chain resilience – why it matters and how it can be achieved.

In this blog, you will learn about the importance of order management to supply chains, and how the order management process can be improved.

Taking ‘just in time’ for granted

Just in time supply chains appear to be very straightforward. You simply order a product from anywhere in the world and it arrives in a few days (or hours, in some cases).

This incredible convenience (and the customer expectations around it) did not exist just a few decades ago – and is something that many of us take for granted today. But such speed and convenience take a lot of planning and continual work behind the scenes – this is called ‘order management’.

Meet the supply officer (SO)

Indeed, to achieve this efficiency, the role of the SO – who handles much of the administration around the movement of goods (ie. order management) – is critical. For example, an SO will properly configure all parameters in the company’s logistic system. This includes master data management – which is related to any information required to pass an order. eg. the supplier’s name, price, logistic conditions, etc. They will also manage the nominal flow of parts and information which represent up to 90% of the transaction, but only one third of the workload.

In fact, SOs spend about two thirds of their time managing non nominal activities, like collaborating with suppliers to confirm quantities and delivery dates, or reconsolidating documents (eg. purchase orders against delivery notes) – thus minimizing impacts on deliveries. This may not seem particularly important, but these small tasks must be done (and done properly) in order for supply chains to properly operate – regardless of their size, and if they operate on the just in time model.

Of course, much of this concerns the movement of goods from warehouses to the end customer. However, another increasingly important aspect of order management is an understanding of ‘reverse logistics’ – namely the work required to bring back products to suppliers and organize repairs. This often requires a different order management process – for example, a much less automated workflow – because it can be difficult to forecast where parts will fail, or be broken. Reverse logistics can also entail additional negotiation with suppliers – but is critical to extend the lifetime of products and maintain customer satisfaction.

What we learned about better order management

From our experiences delivering supply chain services for multiple clients in multiple sectors over the years, we have learned a lot and created some unique capabilities:

• Managing the complete portfolio of suppliers with an end to end vision. This allows us not only to manage day to day activities, but to set commitments that your suppliers will keep to, and minimize missing parts
• A Supply Officer framework that describes a global order management task in 30 individual activities. We can either manage one supply chain task (for example, good receipt disputes), or your entire supply chain
• Up to 30% demonstrated cost savings by using our service when compared to the more common ‘Time and Material’ approach
• A range of dashboards and tools to enhance your ways of working, and offer you a complete view of the performance of your supply chain and order management process

In conclusion

Supply officers could be thought of as unsung heroes of the supply chain. Improved technology and procedures for order management can help them to be more effective, consequentially increasing the resilience of your supply chains – for example, by better utilizing available resources and streamlining operations. 

In the second of this three-part blog series, you’ll learn about Supply Chain Quality Management – what it is, how it works and why it matters.

Struggling with on time delivery or supplier visibility? We can help. Capgemini has helped a range of companies across industries and countries to improve their order management processes and strengthen their supply chains. Choose a world leader – find out how we can help you – contact our expert.