• Written by Muhammed Abdulla NC, CEO

A dusty spreadsheet on a category manager's desk, untouched for months, tells the story of a common struggle in the automotive industry: measuring the return on investment (ROI) of interventions aimed at improving efficiency and reducing costs. The complexity of tiered supply chains, tight takt times, and long programmes makes it difficult to isolate the impact of a specific change.

What automotive makes harder

The automotive industry's unique characteristics, such as supplier escalations, engineering change propagation, and warranty root cause analysis, introduce additional layers of complexity when trying to measure ROI. Supplier escalations, for instance, can lead to a ripple effect throughout the supply chain, making it challenging to identify the root cause of a problem. Engineering change propagation can also have far-reaching consequences, affecting multiple components and systems.

Warranty root cause analysis is another area where the automotive industry's complexity shines through. With multiple stakeholders involved, including suppliers, manufacturers, and dealers, identifying the root cause of a warranty claim can be a daunting task. This complexity makes it essential to have a clear understanding of the relationships between different components and systems in order to accurately measure ROI.

Leading measures you can actually observe

Despite the challenges, there are leading measures that can be observed and used to estimate the impact of an intervention. A shift supervisor, for example, can check the maintenance log to see if a specific change has led to a reduction in downtime. Similarly, a category manager can compare the performance of different suppliers to determine if a change in sourcing has led to cost savings.

These leading measures can provide valuable insights into the effectiveness of an intervention, but they must be carefully selected and monitored to ensure that they are relevant and accurate. By focusing on these observable measures, it is possible to build a clearer picture of the ROI of a specific change, even in the complex automotive industry.

Why aggregate outcome metrics move for unrelated reasons

Aggregate outcome metrics, such as overall production costs or quality ratings, can be influenced by a wide range of factors, making it difficult to determine the impact of a specific intervention. Changes in market demand, supplier pricing, or regulatory requirements can all affect these metrics, even if the intervention itself has no direct impact. This means that aggregate outcome metrics can move for unrelated reasons, making it challenging to accurately measure ROI.

For instance, a decrease in production costs may be attributed to a change in supplier pricing rather than an improvement in efficiency. Similarly, an improvement in quality ratings may be due to changes in regulatory requirements rather than an improvement in manufacturing processes. By understanding the potential influences on aggregate outcome metrics, it is possible to develop more nuanced and accurate measures of ROI.

Baselining before rollout rather than reconstructing it after

Baselining before rollout is a crucial step in measuring ROI, as it provides a clear understanding of the current state of affairs. By establishing a baseline before implementing a change, it is possible to compare the before and after states and determine the impact of the intervention. This approach also allows for the identification of potential issues and areas for improvement before they become major problems.

In contrast, reconstructing a baseline after rollout can be a difficult and inaccurate process. It may be challenging to recreate the exact conditions that existed before the change, and there may be multiple factors that have influenced the outcome. By baselining before rollout, it is possible to avoid these challenges and develop a more accurate understanding of the ROI of a specific intervention. For more information on how to baseline before rollout, visit our resources page.

What this does not do

Measuring ROI in the automotive industry is not a one-size-fits-all solution. It requires a deep understanding of the specific challenges and complexities of the industry, as well as the unique characteristics of each organization. While the approaches outlined above can provide valuable insights into the effectiveness of an intervention, they may not be applicable in all situations.

Furthermore, measuring ROI is not a substitute for other forms of analysis and decision-making. It is essential to consider multiple factors and perspectives when evaluating the impact of a change, and to be aware of the potential limitations and biases of any measurement approach. If you have questions about how to apply these principles in your organization, contact us to discuss your specific needs and challenges.