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5 Key Themes: Navigating the future of Supply chains – Part 2

Gabby Thomlinson
Feb 16, 2024

In this 2-part thought leadership piece, discover how Capgemini has supported supply chain professionals to leverage real-time data, transform collaboration, upskill their workforce, harness AI and cognitive technology, and embrace sustainability practices to create a future-ready supply chain.

Supply chain leaders must stay ahead of the curve to ensure their organisations thrive. Capgemini has identified five key themes that will shape the future of the end-to-end supply chain.

Part-1 explored the pursuit of resilience and agility, seamless collaboration, and future-fit employees. Please see here to read. Read Part-2 below to examine AI-enabled supply chains and sustainability at the heart of supply chain processes.

In a rapidly changing world, supply chain leaders must stay ahead of the curve to ensure they thrive. Capgemini has identified five key Supply Chain themes, with supporting future initiatives, that will be on the minds of retail and consumer product leaders in the years to come.

These are:

  1. The Pursuit of Supply Chain Resilience and Agility
  2. Seamless End-to-End Collaboration
  3. A Future Fit Employee Ecosystem
  4. Supply Chain Enabled by AI and Cognitive Technology
  5. Sustainability and Circularity at the Heart of Supply Chain Processes

Following on from Part-1, we will exemplify these themes through a User Journey of a Supply Chain leader of the future, who is dealing with a scenario of skyrocketing demand.
The user journey continues on to examine the final two key themes: how AI and cognitive technology, and an embrace of sustainability practices can create a future-proof supply chain. 

4. Supply Chain Enabled by AI and Cognitive Technology

Today, the adoption of Machine Learning (ML) and Artificial Intelligence (AI) technologies has resulted in significant changes to ways of working across many businesses. ML and AI have empowered businesses to automate routine tasks, rapidly analyse vast amounts of data, and derive actionable insights for enhanced decision-making. This has led to improved productivity, streamlined operations, and the ability to unlock previously unattainable value.  

As adoption of AI and ML continues to accelerate, supply chain professionals will have an opportunity to adapt their ways of working to focus on higher value activities. This includes strategic decision-making, complex problem-solving, and building strong relationships with suppliers and partners. Supply chain professionals will shift their roles from transactional and operational, to strategic and analytical. Supply Chain Teams being supported by technology that enables these strategic insights and analysis allows them to build closer supplier  and customer relationships based on a clear data picture. Organisations should seek to support this shift as broadly as possible.

To support the integration of AI and ML tools, the identification of the right tools for the organisation is required. Advanced technologies such as cloud-based platforms, Internet of Things (IoT) sensors, and AI-driven analytics, allow real-time information sharing and analysis to become the norm across the entire supply chain network. In the future, integrating IoT sensors will enable supply chain leaders to leverage emerging technologies such as Digital Twins, adding simulation and prediction capabilities to a business as usual driven by machines, but managed strategically, through AI and ML tools. This is even more important in an increasingly unpredictable, less stable world.

Organisations are increasingly adopting flexible planning tools, where systems “speak one language” through standard protocols and a centralised data repository. The development of these advanced technologies will also enable centrally based supply chain teams to be able to work with multi-tier suppliers seamlessly to meet everchanging customer demands. These planning tools offer an operational advantage, and in the future, can be connected into Supply Chain Digital Twins, which offer simulative and predictive capability. This unlocks further insight and analysis, with AI and ML technology supporting people, rather than people-supported technology.

Organisations that have not yet started their journey with the AI and ML tools should look for the right business cases to suit them and their specific needs; a key focus should be to understand the data they will need to ingest and whether that data is available. Starting with a small minimum viable product (MVP) allows businesses to effectively identify whether the capabilities exist in their organisation and how effective the models in reaching their goals. 

Capgemini is actively involved in ML and AI transformations, both in planning, and along the end-to-end supply chain. This includes the study and implementation of forecasting tools that ingest varied data sources, both structured data (such as sales data or inventory), unstructured data (such as customer reviews and social media) and driving value out of new technologies such as Digital Twin and Generative AI. We upskill teams to understand the associated benefits that are unlocked and how to train and improve algorithms going forward, and how teams might leverage the capabilities of ML and AI.

Future supply chain leader: “Technology enabled our supply chain quickly detected the demand spike through advanced AI and cognitive technology. These powerful tools analysed real-time data, enabling us to identify the emerging trend and its magnitude. With this insight, we swiftly mobilised our resources and automated processes to meet the surging demand. AI adjusted production, optimised inventory, and synchronised supply and logistics operations; all whilst allowing us to see the volume and value conversions.” 

5. Everything should have Circularity and Purpose at the Heart of it.

The planet is under enormous pressure, and it is imperative that business decisions are driven with circularity at the heart. Most large corporations are making positive commitments towards important sustainability goals, and this should be supported by a consistent change in business culture. To support these goals at Capgemini, we ensure every action we propose to our clients is scrutinised under a green lens, to support the most sustainable and impactful decision-making.

As discussed in the section “A Future Fit Employee Ecosystem” supply chain professionals will need to become proficient in ML and data analysis. These technology developments support accurate, insight driven forecasts to reduce waste and promote sustainability. Using the latest technology can improve forecasting to reduce the levels of excess inventory and so, decrease the amount of waste resulting from excessive production. Furthermore, product innovation should be underpinned by the net-positive impact of the new product, this means ensuring circularity is embedded in the design.

Furthermore, companies will have to prove their commitment to their sustainability pledges if they wish to retain and attract top talent. Corporations should go beyond making pledges and begin to embed a new culture of circularity into their ways of working. 

From the inception of a project, Capgemini measures carbon impact, and we commit to projects with sustainability as the centre focus, such as net zero strategy or sustainable operations. In supply chain projects we consider the benefits sustainable changes can make, such as improved materials and resources planning and usage, as well as reduced transportation through improved route planning.

Supply chain leader: “Amidst the surge in demand, we prioritised sustainability by implementing eco-friendly transportation practices and adopting lean manufacturing principles. We optimised our supply chain to reduce carbon emissions, minimise waste, and maximise resource efficiency. By sourcing materials responsibly and adopting circular economy principles, we minimised our environmental footprint while meeting the increased demand”.

To summarise…

To conclude, leveraging AI and cognitive technology amplifies the capabilities of supply chain processes, offering unprecedented levels of efficiency and adaptability. Sustainability and circularity remain at the heart of these processes and underline the responsibility and opportunity for organisations to contribute positively to the environment and societal change.

The 5 key themes outlined in both parts of this series collectively pave the way for a future-proof supply chain, to become stronger and more adaptable. If supply chain leaders were to embrace developments, they would commit to creating a resilient, collaborative, and sustainable future. By aligning with these key themes, supply chain leaders can confidently navigate the uncertainty and position their organisations for sustained success in the evolving landscape of tomorrow.

As we navigate the future of the supply chain, it is evident that the landscape is evolving at an unprecedented pace. The five key themes identified by Capgemini – Supply Chain Resilience and Agility, Seamless End-to-End Collaboration, a Future Fit Employee Ecosystem, Supply Chain Enabled by AI and cognitive Technology, and Sustainability and Circularity – stand as guiding beacons for leaders in this dynamic environment.

Within Capgemini’s Supply Chain expertise, we possess extensive experience in supporting organisations transform their entire end-to-end supply chain.  We bring industry specific experience, and we pride ourselves in identifying key value unlocks across the whole end-to-end supply chain to support leaders in ensuring resilience and sustained success.

In case you missed it, please see the first three themes explored here in Part-1 of the Themes of the Future for Supply Chain Leaders; Part-1 examines the themes of resilience and agility, seamless collaboration, and a future-fit employee ecosystem.

Meet out Authors

Gabby Thomlinson

Senior Manager, Supply Chain, Intelligent Industry

Marcella Saads de Carvalho Ferreira

Senior Manager, Supply Chain, Intelligent Industry

Robin Sharma

Managing Consultant, Supply Chain, Intelligent Industry