Cost and Margin Driver Analysis

Cost and margin driver analysis is essential to determining sources of competitive advantage by revealing information about how a company can optimize its activities. This analysis determines relative resource attractiveness by examining cost drivers and it determines growth and profitability potential by examining margin drivers.

Cost Drivers

The relative resource attractiveness is determined by the analysis of the cost drivers, including:

• Critical mass (economics of scale)
• Technology
• Complexity (e.g. products/technologies/lot sizes)
• Utilization (shared resources)
• Experience
• Factor costs
• Management effectiveness

Margin Drivers

Superior growth and profitability is determined by the margin drivers, including:

• Customer mix
• Customer retention
• Perceived customer value (application/quality/price)
• Product mix (hardware/projects/service)
• Product innovation cycle
• Sales force/service quality

Methodology

1. Preform a cost driver analysis. Identify drivers for each activity beginning with the activity that generates the highest cost. Evaluate the structural drivers (scale, complexity, scope, etc.). Evaluate exceptional drivers. Develop relationships between drivers and costs
2. Perform a margin driver analysis. Identify drivers for each activity: customer mix, customer retention, customer value, product mix, product innovation cycle, and service quality.
3. Identify relative advantages/weaknesses. Benchmark drivers against competitors’ for each activity to identify where the company has a competitive edge or demonstrates a weakness, such as control, improved value to customers, or ability to reconfigure the supply chain.

Notes

• Each activity may have more than one cost driver
• Selecting the appropriate cost driver is dependent on the situation and the decision being made
• Developing the relationship between cost and the driver requires significant amount of data
• In identifying relationships between costs and drivers, one can take two approaches:
1. Develop a hypothesis and then test it by collecting appropriate data. This approach is suitable in situations where data is scarce and data collection is expensive (in time and cost)
2. Obtain all data available and assess different relationships to see which is the most significant, using PC based tools. This approach is suitable in situations where significant amounts of data are already available. Knowledge of data mining techniques might be helpful here. Regression analysis is another option

Strengths

• Produces a truer measure of margins and costs
• Considers revenue generating operations as well as costs
• Considers all cost and margin drivers, not just volume

Weaknesses

• External analysts will find it difficult to obtain the data about various activities and drivers unless the individuals have significant industry experience and data
• Data collection might be quite difficult, especially with antiquated systems