Manufacturers across North America are struggling with significant Supply Chain disruptions and challenges impacting their ability to meet customer and market demands.
These disruptions and challenges are also adding substantial time, cost, and inconvenience to the supply value chain. Manufacturers will have to look to technology (AI/IoT) to innovate their way rapidly out of the current environment.
In his 2016 book, Lean and Technology: Working Hand in Hand to Enable and Energize Your Global Supply Chain, author Paul Myerson laid out a clear case for the utilization of digital technologies to transition supply chains to be more lean, agile, and efficient. At the time, there were investments made in Industry 4.0, ERP systems, and other AI technologies, which, depending on the study, claimed benefits like 20-30% reduction in procurement costs, 50+% reduction in supply chain costs, revenue enhancements of 10-25%. Over the past five years, many of these benefits were realized or exceeded at companies which had programs in motion. The same is not true for all companies. Many, if not the majority of late adopters, continue to struggle to realize these levels of benefits.
As we have seen over the same timeline, significant global events have disrupted supply chains unlike any other time in recent history. More recent events include Winter Storm Uri (2020), Suez Canal obstruction by the cargo ship Ever Given (2020), Covid-19 Pandemic, and various other weather-related events creating disruptions lasting weeks or even months. These disruptions have had an upstream and downstream impact on global supply chains affecting customers and suppliers alike. The frequency of disruptions is likely to continue or increase due to climate effects, labor market shortages, and the continuing globalization of supply chains.
Many of the current challenges stem from the drive and desire to build the leanest possible value chains, which resulted in an unhealthy reliance on particular geographies or a select few suppliers. The disruptions have demonstrated “lean” supply chains lacked the agility to adapt to the frequency and severity of the disruptions, and many manufacturers looked to their data without any results. Big Data has often become just that – a lot of data collected from all corners of the enterprise but in a way not presented as information and knowledge biased toward serving customers. In some cases, the sheer volumes of data slowed the recovery time to filter through the noise.
In the end, the basic principles Oliver Wight identified in the late 1960s cannot be forgotten and are arguably more important in a lean environment. A robust S&OP process is essential in delivering low-cost supply chains and maintain increasingly higher levels of agility and customer service. If there is no reliable sales (demand) plan, no predictable supply plan, and no integration across organizational functions and value chain elements to deliver the plan, costs will increase, and customer satisfaction will wane. Together, these two effects will destroy profits and company value.
To win in the next decade, we feel that several key objectives must be executed without delay:
1. Enterprise data collection efforts should continue, but with clear deliverables biased toward supporting solid business processes capable of responding within the timeframes required.
2. Companies should revisit the basics to ensure that processes, organizational frameworks, management systems, business relationships, and cross-functional disciplines execute to Class A standards. These basic elements are the core operating system for any company and determine if the other “software” will run correctly.
3. Integrating Big Data and the core business processes should be a separate objective once the other two are available. The integration will not happen without work.
Given the current and anticipated challenging environments, organizations need to exhibit a real sense of urgency in identifying and addressing the obvious and not so obvious gaps in their supply chain. Utilizing the right approach aligned with readily available AI/IoT platforms, organizations can rapidly deliver the above objectives with minimal capital outlays.
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