Supply Chain optimisation is a huge contributor to an organisation achieving accelerated profitable growth. The key to improving the Supply Chain is to get value from the growing amount of data collected from the many different systems and siloed applications and consolidating these inputs into a single, real time source of trusted information.
The main cause here are the low levels of digital maturity present at many organisations. This regularly leads to the use of manual interventions, risking significant and continuing damage from supplier disruptions that weren’t able to be foreseen. Speedy remediation is also inhibited by poor data capabilities, strategy and governance. Business users aren’t empowered to make effective decisions and organisations may consistently underperform on key performance metrics such as fulfilment, forecasting, OTIF, OSA as a result.
Fresh approaches seek to address these challenges, such as the enterprise data warehouse, which provides a structured and curated view of important business data for reporting and analysis. CRM, ERP and operational data can all be fed into the warehouse technology, which is good at copying over and organising data to meet specific uses.
Data governance is a necessary element of this, establishing policies so business users can trust the insights in front of them. Data quality is vital, and so is latency and lineage – data being real time and traceable back to its source.
To achieve this is very complicated for IT teams because of the fragmentation of data sources used in today’s supply chains – and of course, the volume.
Today’s supply chains need to be fast and flexible. This means that relying on the enterprise data warehouse won’t give the level of operational decision intelligence needed for truly effective supply chain orchestration.
An organisation manufacturing and supplying goods to the consumer retail market, for example, is likely to have a huge amount of information to process in near real-time. This includes suppliers’ production and delivery data, materials or ingredients prices, logistics operations, weather event data, macro-economic indicators, political and labour market information.
A newer architectural approach – the data fabric – provides these advanced predictive and prescriptive analytics capabilities by ingesting and processing all an organisation’s data, including data in the warehouse. But rather than creating yet another silo or moving masses of data around, causing delay, disruption, and risk, it enables organisations to conduct real-time analysis while leaving the data where it is. This complements existing data environments (such as the data warehouse) and can process data from and feed back to (if required), commonly-used supply chain applications.
For IT departments, this approach avoids the burdens of managing another database, saves time through automation and introduces rigorous data governance. It’s a low-code approach that enables self-service by business users who can retrieve the information they want without additional requests for the time of IT professionals. This doesn’t, however, open the door to data anarchy – IT and data stewards assert centralised control to maintain all-important governance of the data.
In this new approach, a purpose-built data solution takes care of piping in data; validating, harmonising, normalising and reconciling to surface a single source of real time information in a decision-intelligence data platform. InterSystems Supply Chain Orchestrator is an example of a such a Decision Intelligence Data Platform..
The InterSystems Supply Chain Orchestrator data platform automates all the onerous data management tasks from ingestion to governance, quality control, preparation, applications, insights and provision of decision intelligence, providing all data consumers with the self-service insights they need to improve their KPI metrics and optimise supply chain operations.
The big advantage for IT is that high levels of automation results in no disruption to or increasing requirement of their work, including management of the data warehouse. IT is free to concentrate on the significant day-to-day and longer-term priorities that must be addressed in a large and complex organisation with a supply chain spanning many borders.
By implementing InterSystems Supply Chain Orchestrator organisations that lack digital maturity can rapidly and painlessly obtain data-driven decision intelligence. With these new capabilities, all data consumers have access to the most effective tool for fulfilment optimisation and fast, agile inventory management.
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