One surprising consequence of the pandemic is that my parents finally have a better understanding of what I do to earn a living. I started working in the supply chain management field over 20 years ago, but it has always been challenging to explain to others what that meant. Now that the term "supply chain" is frequently mentioned during daily government officials’ briefings on television, newspapers, radio and social media, a LOT more people better appreciate why supply chain management matters.
Since my April blog post "Keeping Supply Chains Running in Rapidly Changing Conditions," I have continued to have conversations with supply chain professionals in numerous manufacturing industries including polymers, specialty chemicals, building materials, consumer packaged goods and food and beverages. What I consistently heard during these discussions is that supply chain organizations are playing a key leadership role during the pandemic.
Supply chains are being tested as never before by this "black swan" event. Let me share what I have learned with respect to the tectonic shift that has occurred and the relative importance of certain supply chain capabilities and business processes.
Demand forecasting is considerably less accurate than before the pandemic
Being able to make good predictions related to future demands for goods and services is very important to supply chains. Even in normal times, many companies struggle to get accurate demand forecasts at an appropriate level of specificity to drive execution decisions. The problem most companies are reporting this spring is that the accuracy of their demand predictions has diminished significantly compared to predictions they were obtaining prior to the pandemic. Why? Because the models and advanced algorithms used for demand forecasting rely in good part on historical demand data and associated patterns.
Said differently, these algorithms were never designed to cope with a once-in-a-lifetime event like a pandemic. A May MIT Technology Review article, “Our Weird Behavior During the Pandemic Is Messing With AI Models,” delves deeper into this topic.
There are several interesting responses to this forecasting challenge. First, some companies have temporarily moved from sophisticated algorithms to much simpler methods (such as a simple three period average) or forecasting using the last period's actual demand (a technique known as "naïve" forecasting). Secondly, some companies are transitioning their more experienced demand planners to supply/demand scenario analysis teams where the business can gain tremendous value via scenario insights. These demand planners are tasked to engage at the periphery of their organization and markets to interact, listen and look for clues that will bring insights to key assumptions and underlying input data to use in both short- and medium-term demand outlook scenarios (a couple of quarters following the start of a recovery).
At some point in the future, manufacturers will find themselves operating in a new normal and gradually shift back to previous demand forecasting methods.
Supply/demand scenarios optimization and analysis have rocketed in importance
Most companies I have spoken to now have a team running and evaluating numerous supply/demand scenarios. I found one manufacturer’s scenario analysis approach particularly insightful. Their scenarios team had worked diligently to define a series of possible demand and supply scenarios. For each scenario, they documented key assumptions and the associated data input to update (transit times, available manufacturing lines capacities, raw materials prices, selling prices, etc.) in their supply chain optimization model. The scenarios evaluation team ran their optimization model for all possible combinations of supply and demand scenarios – close to 150 in total.
Their Aspen Supply Chain Planner solution models all of their manufacturing sites as well as their large and complex distribution network over a 12-month planning horizon. The team shared the financial and operational details (reports, charts) of the numerous scenarios with a broader set of stakeholders in their commercial, supply chain and manufacturing groups for further review to identify key issues and constraints.
This company highlighted the importance of data availability and data quality. Robust data governance processes (especially related to master data maintained in an ERP system) are critical enablers to employing these powerful and insightful optimization models.
Improving cash flow via manufacturing scheduling optimization is a priority
In my “2020 Supply Chain Management Trends to Watch” blog, I wrote about manufacturers becoming increasingly aware of a tremendous unrealized cashflow, customer service and topline revenue opportunity: manufacturing scheduling optimization. Many manufacturers still rely on spreadsheets for scheduling. High-fidelity tools offer insight into the best sequence of tasks within a given set of constraints, helping companies reduce inventories, increase on-time-in-full order fulfillment rates, and capture more revenue with higher production output. I’ll provide examples of how companies are optimizing their manufacturing schedules in a future blog post.
Keeping everyone aligned and on the same page is paramount to maintaining business continuity and safe, reliable operations
During the recent Q1 2020 earnings call season, many manufacturers indicated that anywhere from half to two-thirds of their workforce was now working from home. Maintaining effective communications, updating situational awareness about what is happening on the shop floor, making good decisions, and keeping supply chain and manufacturing team members working towards a common goal pose an even greater challenge in the current context.
Early Aspen Schedule Explorer adopters continue to share with us specific examples of situations and use cases making teams more productive, keeping teams informed and constantly aligned, and preventing misunderstandings that result in costly mistakes. We recently created an "Aspen Schedule Explorer Best Practices Adoption Guide" with examples of 20 use cases to document how people across many roles (plant managers, unit leaders, shift supervisors, raw materials planners, maintenance managers, chemists, operators, process engineers, production engineers, operations managers, logistics coordinators, process order coordinators, production preparation, S&OP planners) at early adopter customers are more productive and realizing value from this collaborative web platform.
AspenTech remains committed to helping all our customers succeed through improved supply chain planning, scheduling and ongoing alignment with manufacturing operations execution. If you have questions regarding any of our solutions, you can contact us any time via our customer support site, or email email@example.com.