Celestica recently published the following article, ‘Staying Ahead of Today’s On-Demand Market: Push Versus Pull Strategies.’ The author, Robert Rejano, Processes and Applications Advisor, Celestia, discusses the key differences between push and pull strategies and their impact on the supply chain.Our partner
Rejano asks ‘So why does technology even matter when supply chain principles haven’t really changed in decades?” We explore the answer.You can start the show… whenever you’re ready
Using an interesting analogy centered on the rapidly changing television industry, Rejano suggests push strategies are akin to old analog rabbit ears – you can watch the programs you’re interested in, but only when the network decides to air them. Pull strategies are more like today’s on-demand options. Think digital video recording (DVR) and online streaming. They allow you to choose what you want to watch, and when you want to watch it. Bullwhip Effect When it comes to supply chain strategy, push strategies enable planned material delivery so production can meet a specified demand within a defined schedule. Planning is optimized to cascade independent demand down to the dependent levels through MRP. That demand is then handed off to the next supplier and so on and so forth. Each node’s MRP is optimized independently, which is known as single-stage optimization. Push strategies work when demand is predictable, but there are challenges when forecast accuracy is poor, whether due to the customer’s ever-changing mind or a failure in your own S&OP. This can lead to what is known as the bullwhip effect. As customer demand is conserved at the node that made contact with the end user, that node will tone up or down the demand the OEM plans based on historical experience. When the next supply node performs the same demand adjustment, the resulting modified demand is amplified. Multi-Echelon Supply Chain A multi-echelon supply chain is defined as a network of multiple tiers of supply nodes. Demand flows upstream from the end user through to the last supplier and supply flows downstream from the last supplier through to the end user. Some of the risks inherent in this strategy are poor cash flow performance, holding costs, lost capacity due to production of undesired product, and poor on-time-delivery to request (OTD-R) performance. Push Model
- Production approximation based on anticipated demand
- Slower reaction to demand change
- Higher inventory
- Inventory management through firefighting
- OTD-R across all products low
Advanced optimization tools have opened the door for pull strategies to excel in today’s fast-paced business environment. A pull-driven supply chain uses a series of pull signals to trigger replenishment of stock, starting from the customer order pull and cascading from there. Each node has a calculated reorder point (ROP). The bullwhip effect seen in push models is mitigated by the fact buffers are optimized as a total system, so small demand does not become amplified. One of the challenges of pull strategies is companies have invested heavily in their ERP systems, which don’t handle ROP well without customization. Another challenge is the requirement for subject matter experts to fully optimize the system. Single-Use Kaban In consumption-based pull strategies, there are instances when a ROP is sized to exclude certain spikes. The single-use Kaban (SUK) allows replenishment beyond normal levels for a specified defined period. It can also be used for infrequently ordered or special-order items. Pull Model
- Production precision based on actual consumption
- Agile enough to keep up with changing demand
- Lower overall inventory
- Waste reduction
- Inventory management through visual/systematic process
- On-time-delivery to request across all products high
Ultimately you need to make a decision on your replenishment strategy based on the maturity of your supply chain. Regardless of pull or push, there are key factors that allow the system to be successful.
- Identify root cause of forecast accuracy issues – at the root of many inventory and OTD-R issues is inaccurate forecasting. A systematic, data-driven process for monitoring and improving performance is paramount.
- Plan for every part – through proper segmentation, every item, from customer-facing product down to sub-assembly and component should have a supply strategy that drives to the right level of exception management.
- Manage exceptions – processes need to be enabled that allow the supply chain team to plan the majority of the items with minimal intervention, allowing for strict focus on super A-class items, critical components and unplanned shortages.
- Enable an agile supply chain – depending on the length of the S&OP cycle and the amount of time it takes to propagate demand from customer-facing nodes down to lower-tier suppliers, decisions made today may take weeks before they are realized at the lower levels of the supply network. Eliminating this lag enables a true demand-driven supply chain while optimizing inventory levels.
In an environment where delivery and inventory are key indicators of success, having the ability to optimize the entire supply chain based on defined service levels and acceptable cost of inventory, plan top down and bottom up, see the possible risks, and make quantitative and qualitative decisions based on those risks, is key. That’s why it isn’t difficult to see why the use of pull strategies is on the rise. You can view the whitepaper in its entirety on the Supply Chain Expert Community.
Looking for more great information from Celestica? Check out these other blogs in our series:
[Video] Celestica’s Top Priorities for Improving Forecast Accuracy
How to Turn Your Supply Chain into an Innovation Engine
Forecast Accuracy: Keep Your Demand Management Process Honest
Control Tower Success: Six Critical Steps to Ensure Your Project Thrives
Is Poor Inventory Performance Holding You Back?
What If You Could Take The Guesswork Out Of Forecast Planning?
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