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2024-06-27Navigating ASPICE Compliance with Data-Driven Decisions
Author: Uwe Alfter
Navigating ASPICE Compliance with Data-Driven Decisions
Organizations often find themselves lost when trying to establish an ASPICE (Automotive SPICE) compliant development process. This challenge was the focus of our last discussion.
Today, we will shift our focus to a practical example of data-driven decisions in engineering quality assurance.
Engineering quality assurance gathers data from process compliance checks, work product reviews, and ASPICE assessments according to the quality assurance strategy. Findings from these activities are addressed with improvement actions, and quality assurance teams often pride themselves on their capabilities for process coaching. However, an observed issue is that quality assurance deciders tend to repeat the sequence of measurements in the same way every time, without considering historical data as valuable input for their strategy adjustments.
Let’s examine two trend charts: historical results from ASPICE assessments and work product reviews from the last quarter. Focus specifically on the SUP.8 findings and drill down to the next level of information.Analyzing
ASPICE Results
When isolating the ASPICE results, it becomes evident that BP.5, BP.6, and BP.7 are facing issues. The standard approach would be to define countermeasures for these findings, analyze and solve them, and then expect better results in the next ASPICE measurement.
Investigating Work Product Reviews
However, when we investigate the next level of work product reviews, we see that the recent reviews in SUP.8 are satisfactory. This raises a critical question: How can the ASPICE assessment have findings while the work product reviews show good results?
Rethinking the Approach
This discrepancy highlights the importance of not following a standard approach blindly. While the isolated ASPICE results suggest certain issues, the work product reviews indicate that these issues might not be as severe as initially thought. Or, perhaps the work product reviews are not identifying the issues correctly. It might be better to focus first on the work product checklists rather than solely on the assessment findings. Additionally, the interviewee might not have communicated the topics effectively during the assessment interview. In such cases, it might be more beneficial to coach the assessment participants rather than changing the content.
The goal here is not to solve this specific problem but to open your eyes and mind. Without considering the additional data from work product reviews, one might continue to follow the traditional path. However, integrating this data might lead to a slightly different and potentially more effective direction.
In conclusion, this example underscores the importance of using all available data to adjust quality assurance strategies. By doing so, organizations can avoid the pitfalls of repetitive and potentially ineffective measurement sequences and instead adopt a more nuanced and effective approach to ASPICE compliance.
Effective data management, with systemically collected data organized in powerful dashboards, is the key to success.
