Successful platform engineering initiatives include effective measurement and feedback processes. This article explores the evolution of these processes, from ad hoc and inconsistent data collection to more structured and aligned approaches that accurately measure success and incorporate user feedback. By engaging stakeholders, analyzing feedback, and documenting learnings, organizations can make sure that their platform engineering efforts are data-driven and responsive to user needs.
Focus areas include feedback processes, analyzing and synthesizing feedback, engaging stakeholders, and documenting learnings.
Ad hoc
Measurements are gathered inconsistently, often in custom ways, with no clear alignment between these metrics and the organization’s broader goals. As a result, outcomes and success measures are fragmented and lack consistency across capabilities. User feedback, if collected at all, is informal and anecdotal, leading to decisions based on incomplete or irrelevant data, which in turn results in misguided priorities and fails to capture the true impact on productivity or business value.
Measure success: The customer’s approach to measuring return on investment (ROI) is fragmented and inconsistent. They often rely on basic, activity-based metrics such as the number of bugs fixed or lines of code written, which offer limited insight into the platform's broader impact on organizational goals. As a result, the platform’s cost is frequently weighed against these superficial metrics, making it difficult to accurately assess its true value. Furthermore, feedback from users is rarely aligned with the platform's development processes, leading to reactive, ad-hoc changes that fail to fit within the platform's overall strategy or long-term goals.
Establish feedback collection processes: Feedback is collected informally, often in response to specific issues or requests.
Analyze and synthesize feedback: Feedback is rarely analyzed in-depth. Decisions are made based on
anecdotal evidence or incomplete data, often leading to reactive changes.
Engage stakeholders in feedback loops: Minimal engagement with stakeholders; feedback is often gathered from a limited group of users.
Document and share learnings: Little to no documentation of feedback processes or outcomes. Lessons learned aren't systematically captured.
Structured Processes
Basic feedback mechanisms, such as periodic surveys or user forums, are established to capture user experiences in a more organized way. This more structured approach helps to ensure that the feedback collected is comparable over time, making it easier to identify trends, measure progress, and make data-driven decisions that align with strategic goals. However, while these processes are a step forward, they often vary between teams, leading to inconsistent data collection and analysis. The focus of feedback collection tends to be on general performance metrics, like delivery times or system
uptime. While these metrics provide some insight into process efficiency, they primarily measure activities rather than user or business outcomes. The challenge in this phase is that, despite having some structured processes in place, feedback often remains surface-level and disconnected from the broader platform strategy.
Measure success: Measurements are becoming more organized, focusing on process efficiency metrics such as the number of deployments or adherence to timelines. While these metrics provide some insight into the platform’s efficiency, they still focus on activities rather than outcomes. Customers may start comparing platform costs to benefits like reduced backlogs or improved deployment times, but these comparisons remain limited in scope and don't fully reflect the value generated in terms of business outcomes. Additionally, while feedback is beginning to be considered in development planning, alignment with the platform's overall strategy remains inconsistent, leading to ad-hoc changes that may not support long-term goals.
Establish feedback collection processes: Basic feedback channels are established (examples: periodic surveys or user forums). The process is more consistent, but still varies between teams. Feedback focuses more on monitoring overall metrics, such as current delivery times or recovery speeds, rather than deeply understanding user needs or business impact.
Analyze and synthesize feedback: Feedback is categorized and some preliminary analysis is done, but it
remains mostly informal.
Engage stakeholders in feedback loops: Dedicated individuals or teams start to manage the feedback
process, involving more users but still on a limited scale.
Document and share learnings: Initial documentation of feedback processes is created, but it isn't
comprehensive or consistently used across the organization.
Consistent
Organizations at this level have an intentional goal to verify platform products meet the needs of their market of internal users. Actionable, structured collection of user feedback is valued. Dedicated teams or individuals might be assigned to gather feedback, ensuring a more consistent approach. Feedback channels, such as surveys or user forums, are standardized, and feedback is categorized and prioritized. Beyond user feedback, there's also an expectation that user experiences are instrumented to generate usage data over time.
Challenges remain in translating feedback into actionable tasks. While there's a growing repository of user data, the organization might need help effectively understanding and integrating this feedback into a platform roadmap. It can be challenging to ensure that users see tangible outcomes from their feedback while also balancing the demands of short-term efficiency with the need for long-term value creation.
Measure success: At this stage, the customer begins to focus on outcome-based metrics, such as developer productivity, time-to-market, and customer satisfaction. These metrics provide a clearer understanding of the platform’s impact on organizational goals. The customer can now compare the platform’s costs with tangible benefits like increased efficiency and better alignment with strategic goals, resulting in a more meaningful assessment of ROI. Feedback is also consistently integrated into platform development planning, ensuring alignment with both strategic goals and user needs. However, there may still be challenges in directly linking these metrics to financial performance.
Establish feedback collection processes: Feedback collection is formalized and standardized across the organization. Clear processes are defined for gathering both explicit and implicit feedback. The focus of feedback shifts towards gaining a deeper understanding of user needs, alongside tracking key metrics.
Analyze and synthesize feedback: Systematic analysis of feedback using both qualitative and
quantitative methods. Standard metrics (examples: DORA or SPACE) are used to evaluate progress and outcomes.
Engage stakeholders in feedback loops: Regular feedback review sessions are held with cross-functional
teams. Stakeholders are actively involved in interpreting feedback and making decisions.
Document and share learnings: Comprehensive documentation of feedback processes, outcomes,
and lessons learned is maintained and shared across
Insights
At this stage, organizations have established robust feedback mechanisms and value-centric measurements that focus on strategic insights and business outcomes. Data is meticulously collected and
analyzed to yield actionable insights that guide platform operations and align with desired results, such as revenue growth, cost savings, and customer retention. Dedicated teams or tools are employed to
ensure that feedback is a strategic asset, regularly reviewed and integrated into platform roadmaps. Advanced analytics are used to precisely evaluate the impact of platform engineering on business success, making ROI assessments more accurate. However, challenges remain in continuously refining the measurement
framework to ensure that value-centric metrics are consistently and accurately captured and reported.
Measure success: The organization adopts value-centric metrics that directly correlate with business success, such as revenue growth, cost savings, and customer retention. Advanced analytics are used to assess the precise impact of platform engineering on these outcomes, leading to a more comprehensive evaluation of ROI. Feedback is fully integrated into the platform development process, driving continuous improvement and ensuring alignment with both short-term and long-term goals. The customer compares the platform’s costs with measurable improvements in business performance, ensuring investments are justified by tangible results.
Establish feedback collection processes: Integrated feedback mechanisms are embedded into the development and operational processes. The focus of feedback evolves to deeply understand why and how users interact with the platform, identifying key areas for improvement.
Analyze and synthesize feedback: Feedback is correlated with performance metrics to drive strategic improvements.
Engage stakeholders in feedback loops: Stakeholders from across the organization, including executives and end-users, are deeply involved in the feedback process. Collaboration is structured to avoid silos.
Document and share learnings: Dynamic, real-time documentation is maintained, with updates reflecting ongoing feedback and lessons learned. Documentation is accessible to all stakeholders.
Proactive
Feedback and measurements are deeply integrated into the organization’s culture. The entire organization, from top-level executives to engineers organization-wide, recognizes the value of data collection and feedback on product evolution. There's a democratization of data, where various stakeholders, including platform users and business leaders, are actively involved in identifying hypotheses for platform improvements, providing feedback during the design process, and then measuring the impact post delivery. All of these measurements are considered when planning platform initiatives. Success is measured not just by current outcomes but by the platform's ability to anticipate and adapt to future challenges and opportunities.
Not only are standard frameworks applied, but there's an understanding that measuring from multiple angles creates a more holistic picture. There's an investment in understanding how qualitative measures change as quantitative ones are improved. There's a focus on identifying leading measures which can allow anticipation of features that would support user needs, alleviate their challenges, and stay ahead of industry trends and business requirements.
Measure success: The organization applies predictive analytics and advanced metrics to anticipate future needs and opportunities. Success is measured not only by current outcomes but also by the platform's adaptability to future challenges, ensuring long-term relevance and success. Feedback is seamlessly integrated into the platform’s development process, allowing for proactive adjustments based on both current and predicted future user needs. This enables the organization to accurately predict the ROI of platform investments by comparing costs with both present and anticipated future benefits, such as staying ahead of industry trends and meeting evolving business requirements.
Establish feedback collection processes: Integrated feedback mechanisms are embedded into the development and operational processes. The focus of feedback evolves to deeply understand why and how users interact with the platform, identifying key areas for improvement.
Analyze and synthesize feedback: Feedback is integrated into a continuous improvement cycle.
Engage stakeholders in feedback loops: A culture of feedback is established across the organization, with stakeholders actively contributing to and benefiting from the feedback process. Feedback is democratized, with input from all levels.
Document and share learnings: Dynamic, real-time documentation is maintained, with updates reflecting ongoing feedback and lessons learned. Documentation is accessible to all stakeholders.