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SUPPLY CHAIN ADVANCED ANALYTICS

 

Embedded Supply Chain Advanced Analytics

The supply chain is going through the most transformational phase of its existence and is set to continue with the adoption of advanced analytics.  Supply Chain advanced analytics are vital to deliver fact-based decision supporting business insights at the right time.

Supply Chains never stop.  Every supply chain planning decision every made has suffered from plan decay.  Plan decay is the period of time between capturing data and executing a decision based on that data.  In traditional systems plan decay was many days.  It could take a long time to capture the data, cleanse the data, generate plans, identify exceptions and events, obtain consensus, and finally execute the plan.  Plan decay reduces the relevancy and effectiveness of planning decisions.

DynaSys Supply Chain Advanced Analytics aims to eliminate plan decay.  Modern Supply Chains have access to unpresented volumes of data via the adoption of the IoT.  This data comes in many forms, structured and unstructured, relevant and irrelevant, high quality and noise.  DynaSys Supply Chain Advanced Analytics is capable of digesting millions of data points capturing outliers, trends, and step-changes; only some of this will result in actionable insights.

 

 

 

Advantages of Using Advanced Analytics

Companies are no longer treating their data as an IT necessity and expense, but as a valuable asset from which to leverage actionable business insights. Such insights can be used to grow the business, exploit opportunities and mitigate risk in this disruptive age. Strong advanced analytics and end-to-end stakeholder collaboration forms are the basis of modern supply chain planning technology. As digitalization continues to disrupt, supply chain technology must be hyper-connected, highly-automated, and produce actionable business insights that promote the value of the enterprise and ensure business continuity.
 
  • Fact based decisions.  The numbers do not lie.  This provides planners with decision making confidence.
  • Intuition.  There are many ways to present the facts.  DynaSys Advanced Analytics uses a range of different methods to not just provide the numbers, but more importantly, answer the question being asked.
  • Actionable insights from large data volumes.  Extract rapid value from data without extensive intervention.
  • Real-time.  Eliminate plan decay by being alerted instantaneous to exception and alerts.  This makes a supply chain more agile and able to respond to threats and opportunities.
  • Smarter decisions. Machine learning provides predictive models that can help a company plan for various changes in the supply chain environment.  This provides a faster more accurate output for lesser input.

 

Supply Chain Analytics White Paper

As supply chain analytics have matured along the journey from descriptive to prescriptive, it has taken on a new role.  The methods of presenting exceptions, trends, and insights have evolved.  

 

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