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Navigating the complexities of big data with Intelligent Data Orchestration.
Supply chain leaders today are faced with two major challenges. Achieving visibility across multi-stakeholder networks and deriving actionable insights from data. In fact, 87% of businesses have low business intelligence and analytics maturity – this is especially true in supply chain. Of course, the two challenges are linked, and in this blog, we set out why and how leaders can leverage visibility and actionable insights to improve both operational performance and analysis across their networks.
As supply chains grow ever more complex and multi-faceted, leaders have been looking for ways to gain visibility at a granular level. What makes achieving visibility so challenging in today’s supply chains is the number of independent organisations involved in each intricate network. Supply chains are typically made up of several organisations, each performing a specific function that, when combined with others, makes up the network that facilitates the movement of goods from A to B.
Each organisation generates a huge amount of data at specific points within the supply chain. Capturing and combing this data is, of course a major challenge given the organisations are independent entities, separate from one another. Hence single domain like technologies such as GPS and RFID tagging can generate data outside of each organisation’s jurisdiction (single domain as one organisation owns the tech, captures the data etc.).
However, as those businesses that have invested heavily into these types of technologies have found, they only solve part of the challenge. They might well provide tracking and condition data at consignment level, but the data is still siloed from the other sources. This makes the realisation of value difficult as, in isolation, users only get part of the story.
Of course, from an operational perspective, relatively siloed data can be of benefit. For example, tracking a pallet of goods enables real-time ETA’s to be generated and communicated etc. But deriving root cause analyses historically often requires many more data points and relationships between them to unlock the insights required.
To achieve truly transformational insight and visibility sustainably, the impasse that currently prevents data across the various separate organisations from being shared must be unlocked.
At Entopy, we have looked at this challenge. Rather than focusing on how we can enable a single domain to get visibility across the network (i.e. the deployment of new technology), we have set about finding solutions for how data can be captured and combined across multiple organisations whilst addressing the key challenges that prevent this today.
The Entopy platform enables data to be captured in a highly targeted way, using defined policies to govern interactions with each domain. Data is orchestrated to form a ‘Digital Twin’ of a consignment, enabling analysis and insights to be drawn at a granular level. Each ‘Twin’ records the consignment lifecycle, providing a rich data foundation for future root cause analysis and identification of pinch points.
We call it Intelligent Data Orchestration.