How do you validate your KPI data?

KPIs need to be dynamic as well. Targets need to be realistic and change when necessary. I have seen far too many instances during KPI discussions where sub-par results are blamed on "it's been a slow month". Slow months need targets too.

An important step is to establish a single definition for the KPI. Organizations have a tendency to allow units and leaders to interpret the inputs and output, which will inflate performance and mask underlying trends. KPIs are most powerful when they are consistent over time, highlighting strengths to be amplified and weaknesses to be corrected.

Is there an additional KPI that isn't being asked for, but may add value to your KPI report? Make an additional PPT slide with your additional data. Then either tack it in your PPT where relevant, or maybe even email it to affected teammates. You may have uncovered an upcoming issue before it happens.

Validating KPI data is like fine-tuning an orchestra. Start by ensuring data accuracy through reliable sources and consistent data collection methods. Cross-check data with multiple reports to spot discrepancies. Use statistical tools for outlier detection and anomaly identification. Regularly audit and verify data entries, and involve key stakeholders for feedback and validation. Employ benchmarking against industry standards to ensure relevance. Finally, automate data validation processes where possible to reduce human error. Remember, clean data leads to clear insights!

One of the main things I've seen glossed over is the word KEY! So many businesses I've seen aren't measuring what's important - so make bad decisions on irrelevant metrics. Or are measuring and tracking everything which hides the important variables behind a sea of data - again pushing bad decisions.

Are your data sources authoritative? If not, how do you know they are accurate. Stakeholders want to know that you're not feeding garbage to your dashboards.

To effectively measure KPIs, it's crucial to identify and scrutinize diverse data sources for their reliability, relevance, and compliance. This includes leveraging internal systems for direct operational metrics, utilizing customer feedback for user insights, employing web analytics for digital engagement, analyzing social media for audience interactions, referencing industry reports for benchmarks, and accessing public datasets for broader trends. Each source should be evaluated for its strengths and limitations, particularly in terms of data accuracy, timeliness, and applicability, to ensure they align with your strategic goals and adhere to data standards, thus laying a solid groundwork for accurate performance measurement.

Analyzing data sources is a critical step in ensuring the accuracy and reliability of KPIs. It's essential to evaluate the quality and relevance of each source, considering factors like credibility, timeliness, and completeness. By identifying strengths and weaknesses, you can prioritize the most suitable sources for your KPIs. Additionally, ensuring consistency and compliance with data policies is crucial for maintaining integrity and trust in your metrics. Overall, thorough assessment of data sources lays a solid foundation for reliable KPI measurement and informed decision-making.

Validating your data for one-offs and outliers is critical. Identify if there are seasonal outliers, data spikes due to special partnership/promotion, etc. Understanding the anomalies can help you determine and set realistic KPIs based on how many new partnerships or budget you would have to repeat the success.

It's good to verify your data periodically. Using known controls against planned variables can be helpful. Also, get a second opinion. I'll never discourage any teammate from checking behind me. In fact, I encourage it!