More and more businesses are undergoing a digital transformation of their supply chains. As companies transform along this process, they move from an inside-out focus to an outside-in focus, which allows them to sense, respond and act more effectively to improve the customer experience, bottom-line profits and customer satisfaction.
Next-generation technologies are built such that data is captured, cleansed, linked, visualized and finally powered with machine learning algorithms, leading to holistic decision-making capabilities with customer centricity.
Making the digital pivot to an outside-in supply chain requires next-generation thinking. Traditional thinking for supply chain processes involves a linear approach with inside-out processes, focus on efficient organizational silos, use of transactional batch data centered around history, slant towards response and process standardization. Next-generation thinking is based on outside-in processes designed for structured or unstructured data that move at different speeds. Next-generation thinking shifts from traditional response driven-systems to sensing-driven systems with more intelligence. Business processes are modeled through decoupled services that scale on demand.
As part of the digital transformation, companies will connect to their supply chain trading partners using many-to-many networks. Here each partner brings their own data in their own format — whether its unstructured data, real-time data streaming, PDFs, etc. With a digital supply network, data is captured from supply chain trading partners across each transaction, communication and collaboration. Manual processes, such as submitting a purchase order, are automated, with paper or email translated to appropriate formats where the document can be shared with others electronically. All data is rationalized and is correlated across business processes. Once linked, the data is converted to valuable information bringing extended capabilities for visibility. Finally, with rationalized data, active collaboration and constant visibility, companies can identify patterns that can be used to feed machine learning algorithms to create higher-order problem-solving capabilities.
Digital channels that supply information to the network include trading partners, industry hubs, GPS data, risk data providers, weather information, internet of things, blockchain and more. While networks can easily aggregate data from multiple sources, correlate it and offer visibility, it is also important for companies to seek the network effect. Companies need to identify many-to-many interoperable networks that can help them reach their threshold sooner than later. Once this network of trading partners is actively collaborating, there are more avenues for creating value-add services. The digital channels need to be modeled in a way they can be augmented, extended or replaced based on the dynamic nature of customer-centric strategies.
Businesses should strongly consider embarking upon the digital journey by identifying and prioritizing avenues to maximize customer delight. While the path begins with digitization, it is important to not lose sight of the end goal and employees should be motivated to continuously extend automation boundaries. Traditional information silos need to be broken down and new channels need to open up for structure-agnostic data processing. With sufficient data comes the need to clean and rationalize so as to create value through visualization and learning.
Companies need to complement their enterprise technologies with those provided by many-to-many networks and powerful data platforms. It is imperative for networks to interoperate with other networks so that they can in turn serve their trading partners faster and better in realizing their ultimate goals with attaining digital transformation.
Arun Samuga is chief technology officer for Elemica.
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