Managing the Long Tail of the Supply Chain Part 4: Five Takeaways
Our last three posts covered the key messages of the recent Consumer Goods Technology (CGT) web seminar about long tail demand called “Driving Results despite Item Complexity”.
Blog 1: Lora Cecere discussed the drivers of increasing demand volatility, the pain and risk it causes for most companies and the roadblocks they hit when they try to use traditional demand forecasting approaches.
Blog 2: Pat Smith provided examples of the growth of long tail across multiple industries, and showed how companies are meeting this challenge.
Blog 3: Charles Blevins, Supply Chain VP at Dart Container, described Dart Solo Cup’s journey in addressing a “long tail” that brought Dart 99.6% service levels with 20% inventory reductions.
This fourth and final post will summarize five key takeaways in dealing with the long tail:
1. Now Almost Everyone has a “Long Tail
In industries such as e-commerce, consumer goods, food and beverage, electronics, aftermarket, and industrial distribution, companies are seeing 50% and more of their revenue coming from long tail demand items. This shift is driven by:
- Expanding SKU proliferation to meet customer needs
- Demand for rapid responsiveness and high levels of customer service
- Need for an omni-channel response, due to the growth of Amazon & on-line channel selling
2. ERP and Traditional Approaches don’t work in the Long Tail
ERP solutions and traditional supply chain planning solutions are not well suited for complexity of the long tail. When demand is variable and intermittent, classic forecasting and inventory models do not perform well – many consider items with very low demand rates “unforecastable.” To cope, supply chain managers resort to managing with offline spreadsheets and “rules-of-thumb”. This results in lots of manual effort, low service levels, and a reactive approach that leads to the wrong items in inventory.
3. Specific Planning Solutions are Needed
Mastery of the long tail requires an approach designed to manage the complexity caused by volatile demand (“lumpy demand”) and demanding service levels. This includes:
- Demand modeling: Understanding of unique demand distributions of each SKU-Location at the order line level. Traditional “single number” forecasts and forecast accuracy metrics are nearly meaningless in the long tail environment.
- Service Level Planning: Inventory optimization must incorporate the understanding of demand distributions and a model of the supply chain configuration and its variability. These are combined with business-driven service level objectives for product and customer groupings to ensure customer expectations are met with the optimal mix of inventory.
- Execution to Plan: Replenishment plans must incorporate an understanding of high demand volatility to provide degrees of freedom for replenishment, along with intelligent and exception-driven alerts. Traditional single number DRP approaches are doomed to fail in this environment.
4. Despite Long Tail Challenges, Companies can still Generate Excellent Results
As Charles Blevins said in the web seminar, Dart Solo Cup achieved excellent performance by transitioning from a traditional supply chain solution to one designed for their supply chain complexity. Dart is not alone. Other companies such as Lennox have generated similar well-publicized results.
5. There is a Rapid Path to Value
Not sure where to start? Supply chain consultant Lora Cecere offered the following advice to people who want to get out of “Excel ghettos where lots of people are touching data but not improving it”:
“I encourage people to do pilots to test the effectiveness of current advanced planning systems for the tail – To be able to look at safety stocks, to be able to look at demand sensing and forecasting, be able to look at how to design that and compare it to current systems.”
This is part 4 of a series of 4 blog posts on the Managing the Long Tail of the Supply Chain topic. Below are all four blog posts:
- Part 1 – Managing the Long Tail of the Supply Chain
- Part 2 – Pareto is Dead
- Part 3 – How Dart Achieved a 99.6% Service Level
- Part 4 – Five Takeaways