BUS 721 Week 1 Operations and Corporate Strategy Example

Competing on Delivery Instead of Price: Aligning Operations With Corporate Strategy at a Semi-Custom Cabinet Maker

[Student Name]

University of Phoenix

BUS/721: Issues in Optimizing Operations

Week 1 Assignment

[Instructor Name]

[Date]

Tri-State Cabinet Company and all figures are composites written for a model paper.

Tri-State Cabinet Company, a composite manufacturer of semi-custom kitchen and bath cabinets, operates plants in York, Pennsylvania, Hagerstown, Maryland and Winchester, Virginia, with 1,600 employees and $280 million in revenue. For decades it competed on price, selling to home centers and regional distributors. Two years ago, leadership chose a new strategy: win large home builders by delivering complete cabinet orders in three weeks, on time, every time. Lead times remain near six weeks and on-time delivery is 84 percent. A strategy can change in a boardroom in a day, but the plants that must deliver it were designed over decades for a different goal. This paper analyzes the alignment between Tri-State's corporate strategy and its operations.

Operations Strategy Defined

Operations strategy consists of the long-term decisions about capacity, facilities, process technology, supply networks, workforce, quality systems and planning that determine what an operation can do well. Hayes and Wheelwright (1984) argued that manufacturing could be a competitive weapon rather than a neutral cost center, but only if these decisions were made deliberately to support how the firm chose to compete. These decisions should follow from the competitive priorities the corporate strategy emphasizes.

Competitive Priorities and Trade-Offs

Operations can compete on cost, quality, delivery speed and reliability or flexibility. Classic operations strategy argued that plants must focus, because excelling at all priorities simultaneously is difficult. Boyer and Lewis (2002) surveyed plant managers and found evidence that trade-offs among priorities remained real in many plants, even as some leading firms appeared to improve multiple priorities together.

Cumulative Capabilities

The sand cone model holds that durable gains come in layers, with quality laid down first and dependability, speed and flexibility and cost efficiency each resting on the layer beneath (Ferdows & De Meyer, 1990). In this view, trade-offs can be reduced over time if capabilities are built in the right order.

Tri-State's Current Operations

Plants are designed for long production runs of standard door styles and finishes to minimize setup costs, a sensible choice under the old price-based strategy. Orders are batched by style, and builder orders mixing many styles wait until each batch runs, sometimes for two weeks or more. Finishing lines are shared, and rework from finish defects runs about 7 percent, mostly from uneven stain color and dust in the topcoat. Scheduling is done separately at each plant, and components often ship from different plants on different days.

Misalignment One: Capacity and Batching

Long batches lower unit cost but lengthen lead times and make complete orders hard to assemble quickly. The new strategy calls for smaller batches or cellular production for builder orders, accepting higher setup costs.

Misalignment Two: Quality

Rework disrupts schedules and delays orders. Under the sand cone model, dependable delivery depends first on quality. Tri-State cannot deliver reliably while 7 percent of finished units need rework.

Misalignment Three: Planning and Scheduling

Each plant schedules independently, so builder orders that need components from two plants arrive incomplete. Integrated planning across plants is needed.

Misalignment Four: Information Systems

A 20-year-old enterprise system cannot show order status across plants in real time, and data on delays are compiled manually each month, too late to act on. Leaders lack the information to manage delivery.

Misalignment Five: Measures and Incentives

Plant managers are rewarded on cost per unit, which encourages long batches. Measures do not include on-time complete delivery, the strategy's central priority, so plant managers who shorten batches to help delivery are penalized on their scorecards.

Quantifying the Gap

The gap between strategy and performance can be measured. Builders expect complete orders in three weeks; Tri-State averages 41 days from order to complete delivery, with a range from 22 to 68 days. Of every 100 builder orders, 84 arrive on the promised date, and 11 of those are missing at least one cabinet, so only 73 arrive complete and on time. Two large builders have told sales representatives they will move work to a competitor offering 15-day delivery unless performance improves within a year.

Customer Perspective

Interviews with purchasing managers at six builders show that delivery reliability matters more to them than price within a range of about 5 percent. A missing cabinet can delay a home's completion and the builder's sale. Builders also value accurate order status, which Tri-State cannot provide today, since status questions are answered by phone after checking with each plant.

Competitors' Operations

The competitor offering 15-day delivery runs dedicated cells for builder orders, finishing cabinets in small batches by order rather than by style, and keeps component inventory for the most common sizes. Its unit costs are reportedly higher, but its prices are similar because it wastes less on rework and expediting. This comparison suggests the trade-off between cost and speed may be smaller than Tri-State's plant managers believe.

The Order of Change

The sand cone model suggests fixing quality before pushing for speed. If Tri-State shortens batches while rework stays at 7 percent, faster schedules will be disrupted more often. The first priority is therefore quality at the finishing lines, followed by integrated scheduling and then batch size changes.

Evaluating the Diagnosis

The diagnosis rests on internal data and interviews with 30 managers. It may underweight external factors, such as supplier delays for hardware and glass. Research findings on trade-offs come from samples of many industries, and their applicability to semi-custom manufacturing should be tested.

Workforce Implications

Moving from long batches to order-based production changes work on the plant floor. Operators accustomed to running one style for days would switch more often, requiring faster setups and broader skills. Supervisors would manage flow rather than volume. These changes require training, revised pay incentives for plant teams and involvement of experienced operators in designing new layouts, or the strategy will stall at the point where it meets daily work.

Supply Network Implications

Hardware, glass inserts and specialty wood come from outside suppliers, and late deliveries of these items hold up complete orders. Aligning operations with a delivery strategy extends to suppliers: shorter lead times, consignment stock for common hardware and shared forecasts for builder demand.

An Agenda for Optimization

The course will address the misalignments in turn: business intelligence to see delivery performance, enterprise resource planning to integrate planning across plants, lessons from implementation research, process improvement to raise quality and shorten flow and data-driven decision making to sustain improvement.

Research Questions

The case raises questions for research: whether semi-custom manufacturers can achieve delivery speed without large cost penalties, whether the sand cone sequence holds in multi-plant settings and how incentive changes affect plant managers' batching decisions.

Conclusion

Tri-State's strategy now emphasizes delivery speed and reliability, but its operations were built for low cost. Research on trade-offs and cumulative capabilities suggests that building quality first, then dependable delivery, is the path to alignment. Five misalignments in capacity, quality, planning, information and incentives define the optimization agenda for the weeks ahead.

References

Boyer, K. K., & Lewis, M. W. (2002). Competitive priorities: Investigating the need for trade-offs in operations strategy. Production and Operations Management, 11(1), 9-20. https://doi.org/10.1111/j.1937-5956.2002.tb00181.x

Ferdows, K., & De Meyer, A. (1990). Lasting improvements in manufacturing performance: In search of a new theory. Journal of Operations Management, 9(2), 168-184. https://doi.org/10.1016/0272-6963(90)90094-T

Hayes, R. H., & Wheelwright, S. C. (1984). Restoring our competitive edge: Competing through manufacturing. Wiley.