Guest contributor |
Microsoft’s cloud business is experiencing explosive growth, and our Cloud Supply Chain (CSCP) organisation is responsible for enabling the infrastructure underlying this growth.
Our mission is to deliver the world’s computer with an industry-leading supply chain. CSCP is responsible for strategic sourcing, customer demand forecasting, capacity planning and management, supply chain planning and execution, capacity provisioning, and the decommissioning and dispositioning of more than 300 data centre assets worldwide.
A large portion of core business functions at CSCP are powered by enterprise resource planning (ERP) systems like SAP, running on Microsoft Azure; for example, financial reconciliation, spare, forward stocking location, building planning and general planning unit. We adopt a suite of SAP tools and services that have a tight integration into our system. We use ERP central component to manage processes, global trade services, master data governance, customer service for full device tracking in warranty and spare, business integrity screening, integrated business planning and Ariba for partner collaboration.
Look across our cloud supply chain, most core business requirements have been loosely met by systems of record such as SAP and Microsoft Dynamics. The challenge has been getting a shared view of data beyond one-up and one-down value chain relationships and getting visibility into our n-tier supply chain.
In today’s supply chain, the data flow is sequential. We rely on trusted partners to ‘pass on data’. Reconciling data across those parties, gaining visibility to goods in custody and in movement, and understanding the complex multi-party relationship of those goods, invoices, purchase orders and rebates are critical to our business. Transparency and visibility for these processes have been difficult due to the siloed nature of systems among supply chain participants. Everyone is solving a system problem within the walls of their enterprise. As a result, there is no shared view of data across multiple tiers of the supply chain, and it is challenging for multiple parties to collaborate on the same set of business objects. Therefore, it requires a massive effort to reconcile these disparate data siloes and connect fragmented processes. The lack of visibility really hinders our agility, operational and cost efficiency.
In the future, it would be ideal to have a robust business application layer running on top of an n-tier capable transaction layer that creates trust in the data. This is where we incorporate various existing ERP functionalities with a distributed ledger, bringing suppliers, manufacturers, logistics providers and other key supply chain participants to a single data platform. Purchase orders, invoices, goods in transit and goods in custody are all captured and shared as a single source of truth. We essentially created an orchestration that helps us to gain transparency and end-to-end visibility.
Supply chain managers frequently need to answer these questions: ‘where are my goods?’, ‘has the transaction been invoiced?’, ‘has the invoice been paid?’ and ‘where is the documentation – the purchase orders and invoices – associated with these goods?’. These can now be easily answered by the distributed system we built with tight integration into ERP and a high degree of automation.
Any supply chain has numerous data fields. The more you can get a common view of data, the less reconciliation you have to do. Now that we are privy to data around the transactions among our n-tier suppliers, getting this detailed data in nearly real time allows us to make funding decisions that are faster and more granular. We used to manage our cash on a month-to-month basis for some of our businesses. Now, with the transnational level of control, we can be a lot more responsive to events as they happen, rather than waiting until the closing of the books. Procure-to-pay cycle time has been significantly reduced. Creating a shared view of data in multi-tier supply chain like this is powerful because it makes us proactive rather than reactive. Today, we are tracking billions of dollars of commodity goods on our distributed network in production, the economic benefits created by our transformation are also at the significant scale.
We will have more updates on this converged ERP and distributed ledger technology (DLT) platform as our transformation journey progresses. We will be onboarding more suppliers, verifying the ERP integration patterns and opening our platform to more ecosystem partners. We envision enabling end-to-end traceability all the way from mine to data centre and beyond to recycling. We aim to harness the full potential of our data, transforming it into actionable insights to optimise strategic sourcing, inventory management, and forecasting while driving operational efficiency, reducing costs, and enhancing the agility and resilience of our supply chain.
Moving forward, we plan to apply our technologies to tackle world traceability legislation challenges such as forced labour, minerals and materials, national security, governance and sustainability. These were key topics discussed at Sapphire, SAP’s annual conference, and this is a concern for every part of our business at Microsoft, across our industry and beyond. The future of sustainability starts with digital innovation. We’re going to use Uyghur Forced Labor Prevention Act (UFLPA) as an anchor use case to build on top of our distributed platform.
This is a rapidly evolving space with more than 20 new pieces of legislation announced recently. Goods are being detained at the border in North America and Europe. None of us are immune. We must act now to develop the capabilities required by regulations to ensure visibility across our entire upstream supply chain, from the source of raw materials.
Industry leaders are recognising the urgency. Most CEOs believe trade regulations are a key challenge to their business. More than half are already in action enhancing their data collection capabilities and 20 per cent of executives see this as their number one priority. The distributed solution we built enables us to reach out to our tier-n, but some of the data challenges remain.
This is also a great use case for AI. By connecting with human rights risk data providers and standardising data for traceability, there is opportunity for innovation around AI-based data fusion platform where compute and storage are secure and large dataset fusion is possible. Risks maybe be inferred by AI in a multi-dimensional vector space of time, geography and distance from a hypothetical origin. With the help of generative AI and large language models, insights can be extracted from meta data to drive actions and manage supply chain risks.
Nayana Singh is senior director of supply chain innovation and product at Microsoft.
A snapshot of Singh’s insight was part of the industrials and manufacturing feature in the Winter 2024 issue of Technology Record. Don’t miss out – subscribe for free today and get future issues delivered straight to your inbox.