When The Wheels Fall Off

Idiom: An unexpected problem arose, causing something to fail or go terribly wrong.

In 2017, when I moved, I bought an old car. For the prior ten years, as a city dweller in Philadelphia and Baltimore, I walked everywhere. A car is necessary for the suburbs, so I plopped 5K on the used car lot desk and rode off in a 2016 Lincoln Mercury. The car ran like a champ (even though the odometer registered at 153,000 miles). Not having a car for ten years, I laughingly told my friends, “I will drive this car until the wheels fall off.” In August 2021, after a long road trip, this happened. I rode across a train track and cracked the frame of the car. When the repair estimate was 5X the cost of the car, I wrote the dealer a check and drove off in a 2019 Lincoln Nautilus with 4,200 miles. Why do I tell you this story? I believe that it is an analogy for what is happening in today’s supply chain market. Let me explain.

Historically, most supply chain investments were for engines–bright guys built fabulous optimization code and plonked the software onto a relational database. The algorithms, tuned for enterprise data within functions, helped organizational leaders to improve their functional outputs. In traditional supply chain planning implementations, I count at least a dozen engines churning to improve outcomes. The problem? The engines largely operate in isolation:  they lack a seamless platform. For example, Distribution Requirements Planning (DRP) has very little to do with Transportation Planning (TMS). Revenue Management and Demand Planning do not align on market potential or baseline demand. (Employees can not see market potential. Most discussions are on historical views of order patterns. Orders do not represent market demand for many reasons that are beyond the scope of this post.) I could go on and on, but hopefully, you get the drift. There is no true end-to-end solution that enables bi-directional orchestration across deliver, make, and source processes. The optimization routines single thread through functions not enabling trade-offs across source, make, and deliver. Trade-offs include options like an alternate bill of materials, a shift in sourcing, or the move to outsourced manufacturing. In most organizations, I count at least twenty opportunities for bi-directional orchestration.

In addition, traditional planning implementations assume:

• Transportation is available, the focus needs to be on negotiating price and efficiently filling loads.
• Leadtimes, conversion rates, and cycle times are fixed parameters.
• If I do an excellent job at safety stock management, my company will have the right levels of inventory.
• Order and shipment patterns are a good proxy for future demand.

The wheels are falling off this bus. These assumptions are false. There is a need to redefine planning to be outside-in (using market data) and drive bi-directional orchestration to improve outcomes.

Today, only 3% of the back office employees can see the output of planning systems. There is a need to democratize data and enable what-if analysis for work teams. Planning as we need it needs to change.

In Figure 1, I show a Miro board activity that I like to do with groups. We start in a room surrounded by whiteboards, and we begin mapping the supply chain disruptions month by month. The next step is to ask, “Why did the wheels fall off the bus?” Followed by the question, “What decisions would we have liked to make if we had the market data? And, what data is available to help us make better decisions?”

Figure 1. Bi-directional Miro Board Activity

Why Should You Care?

Fifty-six percent of manufacturing companies managed the first half of the pandemic well, while 44% struggled. Buckle your seat belt. The second half of the pandemic will be worse, not better.  

Why do I believe this? I expect a dark winter. The Delta variant is problematic now, but there are more mutations to come, and it is likely, that a variant will soon be resistant to the current mRNA vaccines. Only 30% of the world’s population is vaccinated.

Plan for the supply chain trifecta. (Don’t make the mistake that you know the answer. The pending disruptions are not the old-fashioned version of risk management that floods your inbox.)

• Transportation Reliability. The global supply chain assumes wide availability of transportation. The slowdown in ocean transport is a rude awakening. Today, there are forty-five large ships off of the port of Long Beach. The queue is a record number. Expect the longer unloading times at ports to reduce fleet capacity by 10-20%, increase lead time by 20-30%, and double the ocean transport cost. Evaluate network design options to simplify sourcing and reduce the number of platforms.
• Labor Shortages. As more and more parents stay home to wrestle with the issues of daycare and education, expect more and more manufacturing disruption.
• Material Constraints. Transportation and manufacturing reliability compounds supplier issues.

What to do?

Call the cross-functional strategy whiteboard meeting, and map the issues over the last year. Ask the team to look forward to imagine the potential market issues. Ask your data scientists to help you augment existing systems.

1. Planning Master Data. Build a planning master data base and ask the data scientists to use machine learning to sense lead time and cycle time patterns. Feed these new values into existing planning systems.
2. Use Channel Data. Bring up a parallel demand management solution using market data (point of sale, distributor data, and market indicators) and look for trends. Map the demand and process latency for your organization, and sensitize the organization to the differences between market data patterns and traditional order signals. Run the new engines weekly and mine the data for trends. (Make this demand management an operational desktop tool and don’t tie it into traditional IT systems. This will help to ensure flexibility for what-if analysis.)
3. Build Transportation Reliability. Meet with all strategic transportation partners and ask how you can help. Start by forecasting transportation requirements by lane, and focusing on taking the steps to be a good shipper. Work together while knowing that transportation is probably going to be both your biggest constraint and cost. Improve payment terms to transportation providers.
4. Focus on the Form and Function of Inventory. Focus on improving inventory buffers. Analyze where inventory should be placed and in what form. Analyze this weekly initially and then when the process is stable, move to monthly. (Use technologies like Logility, LLamasoft (Coupa) and OMP to do this analysis.)
5. Align the Organization to Outcomes. Analyze the reasons for short shipments and continually align the organization to work together to improve the moments of truth. Substitute corporate dashboard metrics like margin, customer service, growth, and inventory health for functional metrics like OEE and Purchase Price Variance. Focus the functions on reliability by aligning to metrics like Forecast Value Added, First Pass Yield, Quality of Conformance in Manufacturing versus Rework, Schedule Adherence, On-time Inbound Shipments, First Pass Tender, etc.
6. Stop Major IT Projects. Align the organization to function without the noise of large IT projects.
7. Put Supplier Development Teams Into Action. Set up meetings with major suppliers. Analyze your performance to see how you can work better with key suppliers. Understand their capacity issues and align in Sales and Operations (S&OP) Planning.

Conclusion

When the wheels fell off my car, I just wrote the dealer a check and drove off with a new car. The pending supply chain disruptions will not be that easy to fix. We are heading into unprecedented times. Take action now.

Update on the Global Summit

This week, we will post all of the videos and PowerPoint from the Global Summit. These might help to sensitize your group on some of the reasons to change.