process mining supply chain

Leveling the Playing Field: Supply Chain in the Age of Amazon

Ready. Set. Shop. Every summer since 2015 Amazon has designated an “Amazon Prime Day” with savings and revenue that rival the frenzy surrounding Black Friday. In the span of two decades, Amazon has progressed from an online bookseller to the most dominant force in retail, delivering millions of items to customers at the right price and faster than anyone else.

Recently Amazon has even moved beyond retail and begun disrupting (and dominating) other industries, from cloud-based web hosting (AWS) to groceries (Whole Foods). But what is the key to Amazon’s success, enabling it to essentially create its own holiday and move such a massive volume of product with a consistent level of competence?

Supply chain efficiency has made Amazon a juggernaut

Supply chain professionals are desperate for visibility. While there are copious amounts of data available across supply chain functions, there is a severe lack of transparency because there’s just too much to weed through and process owners don’t know where to look.

One of the biggest components of Amazon’s success is superior supply chain efficiency. Standardized processes, flexibility, and high levels of automation reduce manual effort and lead to impressively short throughput times, which ultimately serve customers better.

Driven by commitment to operational excellence and focusing on the customer experience, Amazon spent millions on research and development to perfect its supply chain process. The bad news for your company: you probably don’t have the same resources as Amazon to catch up. The good news: your IT systems already contain all the data you need to help you streamline your processes.

How process mining enhances supply chain efficiency

To compete with supply chain juggernauts in the digital age, businesses need to embrace the latest technological supply chain advancements, or face extinction. Organizations looking to catch up to Amazon’s degree of efficiency finally have a solution: process mining.

Process mining uses the digital event logs in your company’s existing IT systems to create a visual reconstruction of your supply chain, and more importantly, the business processes within it. This allows decision makers to easily visualize and analyze cross-departmental processes like purchase-to-pay, order-to-cash, production and logistics, to achieve complete transparency into how these processes are working in real life.

On top of the data visualization component of process mining, the latest machine learning algorithms make proactive recommendations for process improvement by building on past use cases and acting as an automated business consultant. Think of the technology as a combination of an MRI and doctor for your supply chain, providing unbiased visibility and diagnostic capability, in real-time.

Leveling the playing field to stay competitive

Amazon has hovered like a dark cloud on the horizon for years, and now that the storm has arrived, it’s not just retailers who need to worry. Supply chain efficiency has been key to Amazon’s success, and that same success threatens to drive other businesses into extinction.

Identifying issues within core processes can be like finding a needle in a haystack. That’s where process mining technology comes into play, effectively removing the blinders and giving businesses unbiased visibility and proactive recommendations to improve margins and business agility while reducing operational costs.

There’s no getting around it. Your business is existing in the “Age of Amazon” for now and the foreseeable future. It’s time for you to embrace solutions that not only keep you in the game, but help you level the playing field.

Southard Jones --author image
Southard Jones
VP, Product Marketing (former)

Southard Jones is the former VP, Product Marketing for Celonis. Prior to Celonis, Southard held various executive product and marketing roles at enterprise software companies in the Business Intelligence, Analytics, and Data Science market, including Domino Data Lab, Birst, Right 90, and Siebel Analytics.

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