OPS 445 Week 3 Comparing Collaboration Models Example

Who Decides the Next Order? Comparing Collaboration Models With Battery, Brake and Filter Suppliers at an Auto Parts Chain

[Student Name]

University of Phoenix

OPS/445: Strategic Supply Chain Design and Collaboration

Week 3 Assignment

[Instructor Name]

[Date]

Big River Auto Parts, its suppliers, programs and figures are composites written for a model paper.

Big River Auto Parts, the composite 220-store auto parts chain in Missouri, Arkansas and Kentucky, has redesigned its network and chosen new partners for shuttles and batteries. It buys from about 400 suppliers, most of them under ordinary purchase orders placed by its buyers. This paper compares collaboration models and decides how Big River should work with suppliers of four product groups.

A Continuum of Collaboration

Holweg et al. (2005) described supply chain collaboration as a continuum of strategies, distinguished by whether partners share information and whether they jointly plan replenishment, from traditional ordering through information exchange and vendor-managed replenishment to synchronized supply. Simatupang and Sridharan (2002) described collaboration as two or more independent firms working jointly to plan and execute operations with greater success than when acting alone, identifying elements such as aligned incentives, integrated decision making and information sharing. Barratt (2004) cautioned that collaboration is often discussed loosely and that it requires cultural elements such as trust, mutuality and openness, not only technology. The question for each product group is how far along the continuum to go.

Batteries: Vendor-Managed Inventory

The battery maker selected in Week 2 sees demand across many retailers and ties it to weather forecasts. Under vendor-managed inventory, it receives Big River's daily store-level sales and inventory and decides replenishment within limits: minimum and maximum stock by store and model, set jointly each season. The battery maker owns inventory in stores until sale. Big River's role shifts from deciding orders to monitoring the vendor's performance on in-stock rate and inventory levels. The main risk is a vendor loading stores with stock; the maximum limits and consignment ownership reduce it, since excess stock costs the vendor.

Brake Parts: Collaborative Planning, Forecasting and Replenishment

Brake pads and rotors are Big River's largest category, about $95 million a year, mostly from one manufacturer. Demand depends on Big River's own promotions and on new vehicle models entering the repair age, which the manufacturer knows more about. Neither partner alone has the full picture, so joint planning fits. The process starts with a joint business plan each year, including promotion calendars and new part introductions. Each month the partners share forecasts, compare them, investigate items where they differ by more than 15 percent and agree on an order forecast. Exceptions, such as a promotion that is selling faster than planned, trigger a call within two days. Big River places orders, but on a forecast both have agreed.

Brake parts need two sets of knowledge in one forecast: what Big River will promote and what cars are coming due for repairs.

Slow Specialty Parts: Consignment

Hub stores now hold about 80,000 part numbers, many of which sell once or twice a year. Big River negotiated consignment with three suppliers of slow parts, such as sensors and specialty hoses: the supplier owns the stock in hubs until a part is sold, and Big River pays on sale. In exchange, Big River commits to stock the supplier's full range in hubs and to share sales data weekly. This reduces Big River's investment in hub inventory by about $9 million.

Filters: Shared Forecasts

Oil and air filters are stable, high-volume items from two suppliers. Collaboration beyond sharing a rolling forecast would add cost without much benefit. Big River sends both suppliers a 13-week forecast each month, and suppliers confirm capacity.

Comparing the Models

Information shared: filters, forecasts only; consignment, weekly sales; brake parts, forecasts, promotions and exceptions; batteries, daily sales and inventory.

Decision rights: filters and brakes, Big River orders; batteries, the vendor decides within limits; consignment, Big River pulls from supplier-owned stock.

Requirements: accurate point-of-sale and inventory data for all; electronic data interchange or portal access for batteries and brakes; joint meetings for brakes.

Benefits: lower inventory and fewer stockouts for batteries; better forecasts and promotion execution for brakes; lower investment for consignment; supplier capacity planning for filters.

Risks: overstock by vendors, data errors, dependence on partners and the time cost of joint planning.

Data and Trust

All four models depend on accurate data. Big River's inventory accuracy at stores is about 92 percent; vendor-managed inventory and consignment require at least 97 percent, so cycle counting of batteries and consignment parts will increase. Trust is built gradually: each program starts with a pilot region, results are shared openly and both sides can exit with 90 days' notice.

What Changes for the Buyers

The buyers' jobs change most. Today four buyers spend most of their week placing orders. Under the new models, the battery buyer reviews the vendor's performance and adjusts limits each season rather than ordering; the brake buyer runs the monthly forecast comparison and exception calls; the specialty buyer manages consignment agreements and checks that suppliers keep hub stock complete. Training covers reading the vendor's reports, running a forecast review and negotiating limits. The buyers' measures shift from purchase price variance to in-stock rates, inventory turns and forecast accuracy.

Collaborative Transportation

One more model is worth noting for later: collaborative transportation management, in which shippers and carriers plan loads together. Big River's two distribution centers receive about 70 inbound truckloads a week from suppliers who each book their own carriers. Sharing order forecasts with suppliers and their carriers could combine partial loads from nearby suppliers, reducing freight cost; it is deferred until the first three programs are running.

Rollout Sequence

Batteries first, since the partner has a proven program and the payoff before winter is large. Consignment next, as hub stores open. Brake parts collaboration third, after a joint business plan is drafted for the coming year. Filters can start at any time.

Conclusion

Collaboration is not one program but a range of choices about information and decision rights. Big River will let its battery maker manage replenishment, plan brake parts jointly with its main manufacturer, put slow specialty parts on consignment and simply share forecasts for filters. Each model matches who knows most about demand and who should decide, and each depends on accurate data and trust built through pilots.

References

Barratt, M. (2004). Understanding the meaning of collaboration in the supply chain. Supply Chain Management: An International Journal, 9(1), 30-42. https://doi.org/10.1108/13598540410517566

Holweg, M., Disney, S., Holmström, J., & Småros, J. (2005). Supply chain collaboration: Making sense of the strategy continuum. European Management Journal, 23(2), 170-181. https://doi.org/10.1016/j.emj.2005.02.008

Simatupang, T. M., & Sridharan, R. (2002). The collaborative supply chain. International Journal of Logistics Management, 13(1), 15-30. https://doi.org/10.1108/09574090210806333