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Achieving Supply Chain Resilience with Process Intelligence

Andrew Pery

August 18, 2020

Blog cover | ABBYY Blog Post

We are all familiar with the proverb “necessity is the mother of invention.” In an interdependent global economic environment, anticipating unexpected risks is built into the DNA of every organization, large and small.

But nothing could have prepared us for the pervasive impact of this pandemic. According to a survey by the Institute of Supply Management, 75% of companies are reporting significant supply chain disruptions, which is unprecedented in modern times. Just in time inventory and dependence on lowest cost suppliers, the hallmark of modern supply chain management, now represents risks to businesses.

The pandemic is necessitating a fundamental re-architecting of supply chains: 

“How should we retool our supply chain to protect against shocks while staying competitive on cost and value? For years, ‘faster, cheaper and more efficient’ has been the supply chain manager’s mantra. Quick delivery, lean operations, and a widely distributed footprint have been the top priorities. But in a matter of a few short weeks, the global coronavirus panic demonstrated starkly that many management teams have vastly underestimated the value of supply chain resiliency and visibility.” 

Achieving supply chain resilience requires consideration of a number of strategic initiatives:

  1. Mitigating supply chain risks by developing alternative sources of supply and ensuring minimum inventory levels in the event of unforeseen shocks and disruptions, even if it means higher inventory holding costs; 
  2. Shifting the sourcing of components and manufacturing of products essential for business continuity to minimize geo-political risks and shocks to the supply chain. This may necessitate re-thinking the merits of a more localized supply chain, which may result in higher operating costs, but which guards against critical inputs to manufacturing processes; 
  3. Increased investments in supply chain process optimization in order to gain better visibility to end-to-end supply chain processes, how they perform, where process bottlenecks may exist, their degree of variability, and enabling  organizations to make informed decisions to remediate supply chain process efficiencies based on observed facts; and 
  4. Automating highly labor-intensive and inefficient document-centric processes associated with the flow of goods. Transportation constitutes as much as 50% of logistics spending. A significant component relates to documentation processes that span certificates of origin, certificate of insurance, packing lists, dangerous goods forms, bills of lading, and customs clearing documentation. Inefficiencies and errors associated with documentation can be time consuming, labor-intensive, and costly. Demurrage charges may be incurred when shipments are not taken delivery of due to inaccurate or incomplete documentation.   

Addressing these strategic imperatives requires a holistic approach to achieving a resilient supply chain.   The foundation is the creation of  “a digital twin” of the supply chain and investing in control tower solutions for end-to-end visibility across the supply network.”   

ABBYY Process Intelligence enables your organization to discover, visualize, and analyze supply chain data from both digital and physical sources. When properly ingested, merged, and analyzed, this wealth of data can be used to discover patterns and insights that illuminate paths for achieving optimum supply chain performance by building a virtual model of your processes that: 

  • Visualize the flow of your work through supply chain process stages and see the delays, bottlenecks, and outliers; 
  • Rapidly reveal how every occurrence of every process is executed, including even the most ad-hoc, variable workflows; 
  • Simply and quickly pinpoint the root cause of non-compliant, unusual, or high-cost supply chain processes; 
  • Automatically generate a foundation for data-driven decisions with quantifiable process metrics, including cost, duration, and volume; 
  • Help you understand exactly how your supply chain processes affect compliance and service delivery. You gain full transparency and actionable insight for optimizing processes, making decisions, and improving results; 
  • Identify and automate manual processes, delivering faster time to value on your process improvement initiatives; and 
  • Use early stage data to predict process outcomes and proactively plan or act. 

study by Bain and Company re-enforces the importance of investing in technologies that "empower organizations to proactively anticipate the impacts of disruptions by harnessing machine learning and artificial intelligence for predictive and prescriptive analytics."  The ability to make proactive decisions is dependent on an understanding of how supply chain processes work by uncovering process execution bottlenecks that drive supply chain inefficiencies. 

Recently, ABBYY hosted a webinar with two information management and supply chain experts who shared their collective experience and best practices relating to achieving supply chain resilience. Added key takeaways are summarized in an article published by Deep Analysis

  • “Leverage business insight from data analysis and process intelligence by using process mining to find insights into newer, better, and faster ways to work in the midst of disruption;” 
  • “Digitize labor-intensive, inefficient, paper-based processes;” and 
  • “Use agile approaches to quickly implement low-code case management (including document management, digital decisioning, and digital process automation). This can automate to eliminate manual steps, activities, and processes while also eliminating physical documents that clog the system.” 
Digital Transformation Process Mining Transportation & Logistics
Andrew Pery ABBYY

Andrew Pery

Digital transformation expert and AI Ethics Evangelist for ABBYY

Andrew Pery is an AI Ethics Evangelist at intelligent automation company ABBYY. His expertise is in artificial intelligence (AI) technologies, application software, data privacy and AI ethics. He has written and presented several papers on the ethical use of AI and is currently co-authoring a book for the American Bar Association. He holds a Masters of Law degree with Distinction from Northwestern University Pritzker School of Law and is a Certified Information Privacy Professional (CIPP/C), (CIPP/E) and a Certified Information Professional (CIP/AIIM).

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