How do you incorporate feedback and learning into your dashboards and scorecards?

Organize regular 'Data Quality Workshops' with key stakeholders to scrutinize and validate your data. Use these sessions to refine data quality standards and rules, ensuring that your dashboard reflects the most reliable and accurate information.

One thing I find important when creating my own data dashboards to ensure data accuracy, is to rigorously test my assumptions about the data using specific curated edge cases (applies especially so for data dashboards with filters and search fields). Secondly, maintaining strict data quality standards (e.g. having clean data) by ensuring that the information we rely on is both reliable and consistent is also crucial.

Incorporating feedback and learning into dashboards and scorecards involves regularly updating metrics based on stakeholder input and organizational insights. Integrating mechanisms for collecting feedback, such as surveys or performance reviews, ensures relevance and accuracy of data. Analyzing trends and identifying areas for improvement allows for iterative refinement of key performance indicators. Incorporating qualitative data alongside quantitative metrics provides a holistic view of performance. Finally, fostering a culture of continuous improvement encourages ongoing learning and adaptation to drive better decision-making.

Regularly solicit feedback from users and stakeholders to identify areas for improvement and understand their specific needs. Iterate on your dashboards and scorecards based on this feedback, adjusting visualisations, metrics, and insights to better align with the evolving requirements and expectations of your audience.

In today’s data-driven environment, dashboards and scorecards are essential for tracking performance and outcomes. However, their true value is unlocked when they are treated as living tools, continuously refined through feedback and learning. At AccorInvest, we’ve embraced this philosophy by integrating feedback mechanisms directly into our dashboards. This allows us to capture real-time insights from a variety of stakeholders, including employees (Pulse survey), customers (GSS scores from our hotelguests), and external partners (STR data compset performance vs competition). Moreover, we leverage these insights to adjust our strategies and scorecards, ensuring they reflect the evolving priorities and success metrics of our business.

The second step in incorporating feedback and learning into your dashboards and scorecards is to engage your users and collect their feedback. Understanding who your users are, their needs and expectations, and how they use your dashboards and scorecards is crucial. You can gather their opinions, suggestions, and complaints through surveys, interviews, focus groups, or usability tests. Additionally, using analytics tools to track their behavior, interactions, and satisfaction provides valuable insights. Engaging users and collecting feedback will help you enhance the design, functionality, and usability of your dashboards and scorecards to better meet their requirements and preferences.

User engagement is critical in refining dashboards and scorecards. Actively seek feedback from the users of these tools to understand their needs and challenges. This could involve surveys, focus groups, or one-on-one interviews. Feedback should be specific to the usability, functionality, and relevance of the information presented. Use this input to make the dashboards more intuitive and aligned with user requirements, enhancing their overall effectiveness.

In my experience, optimizing user engagement in dashboards involves a multifaceted approach. Implement user feedback mechanisms, like surveys and polls, directly in the dashboard to gather specific insights on features and usability. Embrace an iterative design methodology, releasing versions with incremental improvements based on user testing and feedback analysis. Utilize analytical tools to track user behavior and employ A/B testing to compare and enhance different dashboard versions. Foster communication channels for user discussions and provide comprehensive training resources within the dashboard. Leverage machine learning for personalized user experiences, and conduct regular review meetings with stakeholders.

A UX colleague can assist you in setting up experiments and monitoring how users interact with your dashboard. UX validation tools can help you execute large-scale experiments and uncover your dashboards' improvement potential.

Schedule quarterly 'Performance Analytics Meetings' to delve into dashboard data. Use these sessions not just to review metrics, but to identify underlying trends and patterns. Translate these findings into actionable insights for strategic planning.

Performance evaluation using dashboards and scorecards should be a learning process. Analyze the metrics and indicators to understand the trends, successes, and areas for improvement. Use this analysis to educate and inform the team about best practices and areas that need attention. This ongoing learning process helps in aligning strategies with organizational goals and in making informed decisions.

In my experience, effective dashboards and scorecards require a strategic approach to performance evaluation and learning. Begin by defining measurable KPIs aligned with organizational goals, regularly updating them based on feedback and evolving priorities. Actively collect and analyze user feedback to inform iterative design and development. Provide user training and support, fostering a culture of learning within the organization. Integrate predictive analytics for future trend anticipation and benchmarking for comparative analysis. Ensure data quality through rigorous assurance processes, and promote transparency in reporting.

Beyond incorporating feedback from others and evaluating Ops performance through dashboards, Machine Learning can also be used to aid in this process to identify gaps that humans may miss out on or draw new / novel conclusions from the same dataset. Oftentimes people assume that Machine Learning requires coding and is complex, but there are free no-code tools that can be used to achieve this outcome, to gather insights to enhance operational efficiency.

Incorporating feedback and learning into dashboards and scorecards involves a few key steps: 1. Integrate Metrics: Include KPIs that measure both performance and learning outcomes. 2. Real-Time Data: Ensure the dashboard updates in real time to reflect the latest feedback for timely decision-making. 3. User Feedback: Embed mechanisms for collecting ongoing user feedback directly through the dashboard. 4. Learning Loops: Use scorecard data to identify areas for improvement and implement changes based on insights gained. 5. Review Cycles: Regularly review and adjust KPIs and learning goals to align with evolving business objectives and feedback. This approach fosters a continuous improvement culture, enhancing performance evaluation.

The fourth step in incorporating feedback and learning into your dashboards and scorecards is to plan and implement actions based on your findings. - Start by prioritizing issues, setting goals and strategies, and allocating resources and responsibilities. - Communicate the action plan to your team and stakeholders to secure their buy-in and support. - Use dashboards and scorecards to track the progress of your action plan and report on achievements and challenges. This approach will help improve operational performance, address problems, and achieve desired results.

Incorporating feedback and learning into dashboards and scorecards is crucial for growth. Here's how I do it: ??Regularly update metrics to reflect new insights. ??Create a section for feedback on each dashboard for visibility. For action planning and implementation: ??Set clear, achievable goals based on feedback. ??Assign tasks and deadlines to ensure accountability. ??Review progress in team meetings to keep everyone aligned. It's about making feedback a cycle of continuous improvement, leading to smarter decisions and better results.

Create a 'Dashboard Action Tracker' – a dynamic tool where you log, track, and manage improvements based on dashboard insights. Regularly review this tracker in team meetings, ensuring accountability and progress in addressing operational challenges.

Based on the insights gained from dashboards and scorecards, develop action plans to address identified issues or capitalize on opportunities. This involves setting specific, measurable, achievable, relevant, and time-bound (SMART) goals. Ensure that these plans are communicated clearly to all stakeholders and that there is a clear process for implementation. Regularly monitor the progress of these actions to ensure they are driving the desired outcomes.

When Operations is optimised for the team, buy-in would come very naturally especially if it incurs no additional costs to the company and in turn, saves time and energy for everyone. What I find is more important is that during the implementation of operational optimisation, apart from using dashboards to track performance, it is highly crucial to do a short sharing session or even a step-by-step guide to ensure that these new optimised processes is fully understood by all.

Implement a bi-annual 'Dashboard Evolution Session'. Review the relevance and effectiveness of your dashboards and scorecards. Update them to include new data sources, feedback, and learning outcomes. This keeps your tools dynamic and aligned with evolving business goals.

Regular review and revision of dashboards and scorecards are vital. This process should not only focus on the data presented but also on the format and layout of these tools. As business needs and environments change, the dashboards should evolve to reflect these changes. Incorporate new metrics or modify existing ones based on feedback and learning. This ongoing revision ensures that the dashboards remain relevant and effective.

With dashboards and scorecards, it's critical to constantly assess: "Is this information telling us what we need to know about our business?" This applies to all levels, from executive dashboards to front-line scorecards. If the audience at any level is confused or not getting the information they need to drive meaningful action, it's time to either: 1) Educate and coach, gathering their feedback in the process about how to improve the clarity of the tool, or 2) Revise the tool. Gathering continual feedback from dashboard/scorecard end-users is essential in ensuring that these tools provide the information needed to drive the results you're aiming for.

Adopt a mindset of continuous improvement in managing dashboards and scorecards. Use feedback and performance outcomes as a basis for ongoing refinement. Encourage a culture where feedback is actively sought and valued. Continuous improvement should focus on enhancing the user experience, data quality, and the overall utility of the dashboards in decision-making processes.

I am a firm believer in continuous improvement, and as long as a task feels too time consuming or "high effort, low reward/value", my mind is automatically pondering on the optimisations. These inspirations happen sporadically, especially as I research and learn about more tools, or even learn new features of my current tools (e.g. Slack workflow builder, Postman, Google sheets API integration, Metabase). I also always encourage open sharing of feedback and am receptive to it, so that I can further optimise what I have already optimised, helping my team be more operationally efficient and steer focus towards more value-adding work.

One can incorporate feedback and learning into their dashboards and scorecards by establishing feedback loops for data quality assurance, in order to promptly identify and rectify any data discrepancies, inaccuracies, or gaps in real time. By incorporating feedback and fostering continuous learning, you can enhance the effectiveness, usability, and impact of your dashboards and scorecards. This approach can drive continuous improvement and innovation within your organization, empowering teams to make data-driven decisions with confidence and agility.

Use A/B testing to evaluate the effectiveness of different dashboard features based on user feedback. In a marketing firm, we tested 2 versions of a campaign performance dashboard- one with detailed metrics & another with high-level summary. Feedback from marketing teams was collected on both versions & A/B testing showed clear preference for the detailed metrics version, leading to its implementation. Applying A/B testing for feature validation ensures that changes to dashboards & scorecards are data-driven and aligned with user preferences Employ advanced analytics to interpret feedback & generate actionable insights. In an energy company, we used text analytics to analyse feedback from engineers on our operational performance dashboards

In addition to the above points, consider integrating advanced analytics and AI tools to enhance the capability of your dashboards and scorecards. These technologies can provide deeper insights, predictive analytics, and trend analysis, further enriching the decision-making process. Also, invest in training for the users of these tools to maximize their understanding and effective use. This training should include not just how to use the tools but also how to interpret the data and apply it in their specific roles.

Keeping the cycle as short as possible. If a review and revision takes months to perform, we are following a wrong trajectory. Compare it with working capital cycle, the shorter the better.

One thing I find helpful is to always keep an open mind, and think out of the box. For instance, the simplest optimisation can be easily missed, and thus optimisation / improvements does not have to be something complicated or necessarily require coding (you have AI tools for that too). More importantly, data dashboards can also be improved through using data analytics to forecast trends and give actionable insights.