Value Creation in Digital Supply Chain

Global economies have entered a new era characterized with volatility from supply chain disruptions, geopolitical tensions, and evolving consumer and sustainability needs. Technological advancements also accelerated and present many digital options available to businesses, in particular to advance the supply chain. It is widely agreed that there are many benefits to be derived from a digital supply chain. Value is created at across various aspects like strategic resilience, supply chain automation, customer-centricity and optimized operations. Organisations have to be judicious in deploying innovative solutions to reap value from digitalization that often require large investment and commitment. Organisations can look to the markets for varying digital solutions to suit their business. These solutions range from cloud-technologies to suite and best-of-breed IT solutions that layer onto legacy systems to even robotics and advanced analytics.

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Predictive Analytics

Predictive data analytics may harness cognitive computing, Artificial Intelligence (AI) and Machine Learning (ML). This enables forward-looking sensing and outcome simulation capabilities. It also improves decision-making through enhanced visibility like highlighting organisational gaps. Advanced data analytics may predict impact from supply disruptions due to extreme weather conditions or market events. Some solutions map entire value chains up to Tier 4 suppliers, generating knowledge graphs of supplier relationships, key sub-tier flows. It can simulate forecast knock-on impacts of global events and the outcomes of possible response strategies. Source-to-Contract (S2C) processes for procurement become more predictive by calculating landed cost differences across products, input costs, country viability and risk across alternate regions. This gives insight for better decisions or even gives professionals an edge in commercial negotiations. Predictive analytics utilizing Internet-of-Things (IoT) in manufacturing equipment may also provide prognostic insight. This maintains high performance and component lifespan to pre-emptively initiate maintenance before total system failure, reducing risk of worse downtime.

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Customer-Centricity

Customer-centricity focuses on customer experience and responding to such demand accordingly, which increases customer lifetime value, customer satisfaction, and profitability for the firm. Digital tools enable firms to identify, correlate and act upon demand requests in planning, manufacturing and scheduling to create value. A way is through digitalized or personalized consumer experiences to alter retail experiences. The use of advanced spatial computing is evident when fashion giant Bloomingdales’ collaborated with technological firm, Emperia to create a virtual store in the Metaverse for immersive shopping. This enabled augmented reality interaction of prototyped products to seek customer review prior to redesign and manufacturing. In other use cases, hyper-precise AI modelling in healthcare personalized patients’ treatment scenarios through digital twin technology. This allowed professionals to replicate a patient’s health data and enable a supply of treatments based on consumer needs. However, firms should note that metaverse solutions require high hardware investment on smart sensors to capture and feed data. Data governance, management and integration are crucial aspects to prevent platforms from becoming dated, all while managing data ownership and privacy.

Optimized Operations

Through AI-enabled automation software, fully autonomous operations are possible for non-critical and routine purchases via procure-to-pay (P2P) processes in procurement. This can free up human capacity for deployment to other more value-additive tasks. Smart contracts can act on timely alerts and data from past negotiated agreements’ commercial terms. Software can sort fragmented or unstructured data for efficient procurement evaluations. Distributed Ledger Technology (DLT) such as blockchains can improve supply chain visibility and traceability even beyond tier 1 suppliers. Use cases include validating bilateral and regional trade documentation e.g. customs declarations and product licences for data standardization. In logistics, automation drives efficiency in many areas. Examples include high-speed product picking, sorting and order fulfilment, planning of transportation pick-ups, optimising transport routing and scheduling warehouse operations. Advanced analytics via AI-enabled technological company Adiona to aid innovative last mile delivery solutions by helping firms route optimisation decisions.