Process mining: Empowering retailers to compete in the Amazon age
By Bastian Nominacher, Co-CEO and Co-Founder, Celonis
Over the past 20 years, Amazon has transformed itself from an online bookseller to the most dominant force in retail, delivering millions of items to consumers at low cost and faster than anyone else. And, in the wake of Amazon’s success, consumer expectations are changing. People now expect more choice of product, more convenience and full visibility from the moment they place an order. They want up-to-date information on stock levels, warehouse departure timestamps and delivery confirmation.
This demand is causing a revolution in thinking and retailers are altering their logistics practices in response. Next-day delivery requires faster inventory turnaround-times and bigger logistical networks need higher levels of stock at more distribution centres. Therefore, any retail business looking to compete with Amazon needs to ensure it has even more visibility into its supply chain than its customers to remain one step ahead.
Perfecting the supply chain
With standardised processes, high levels of automation and rapid delivery times, Amazon is driven by commitment to operational excellence and focusing on the customer experience. It has spent billions on R&D over the past 20 years to perfect its supply chain, and is going from strength to strength, recently beating revenue estimates in its latest financial results.
Looking at the wider industry, skyrocketing amounts of data are increasing retailers’ need to streamline their processes. More data has been created in the last two years than the previous 5,000 years of humanity, and while retail businesses are sitting on a wealth of information because of this, they don’t know how to make sense of this data without the right technology in place.
Identifying issues within core processes can be like finding a needle in a haystack, but emerging analytics solutions have enabled retailers to make more informed decisions, sifting through the massive amounts of data being collected to uncover hidden patterns, correlations and customer preferences. A key limiting factor of traditional analytics, however, is that they’ve always required the retailer to have a hypothesis about where they want to look and what they want to investigate. In response, new categories of big data analytics, such as process mining, are starting to emerge that are helping retail businesses to pinpoint inefficiencies within their core business processes and along the supply chain.
Transforming supply chain visibility
Powered by artificial intelligence and machine learning, process mining technology uses the digital traces left behind by every IT-driven operation in a retail company and provides complete transparency into how processes are operating in real life. This means having access to a visual reconstruction of the entire organisation’s business processes. Using this insight, they can analyse how well their logistics and supply chain operate from order entry all the way to delivery. Process owners can see how efficient (or inefficient) their distribution network is, and identify any causes of delays. Larger systemic weaknesses in order processing can be pinpointed, and granular details like manufacturing data and invoice tracking can be drilled into.
Improving customer experience in the Amazon era
Many retailers are challenged with establishing a stable supply chain that ensures fast, on-time and in-full delivery to customers. When companies can’t deliver on their promised delivery dates, the impact is clear: customers grow increasingly frustrated, often airing their complaints on social media, and damaging the brand’s reputation in the process. But there are many potential root causes along the supply chain that drive up long wait times.
Imagine a retail company that has a global audience base, a large number of product variations and local market requirements – the task of identifying the exact problem and understanding the root causes for late delivery could be enormous. There could be issues in production, logistics, or the order handling process, driven both by internal and external factors: a production plant with quality issues could cause a lot of rework, a logistics provider could deliver too late or an order could be stuck in an internal approvals process.
Eventually, the problem becomes visible when customer satisfaction goes down and churn increases, but management wouldn’t have any idea of the scope and impact of the specific bottlenecks unless they were first aware that they should be looking for it. To address this, retailers are turning to process mining as a means of reducing inefficiencies and monitoring compliance, production and supplier performance to cut throughput times.
Amazon’s dominance in the market should act as a wake-up call for other retail businesses. Supply chain efficiency has been key to the giant’s success and that same success is threatening to drive other retailers into extinction. But new analytics solutions like process mining are empowering organisations to uncover and repair hidden inefficiencies, working in real-time to provide better visibility into the entire supply chain. Ultimately, retailers that take control of their processes are those that will be able to give their customers what they want, when they want, and level the playing field with giants like Amazon.