Metrics are an essential part of reporting. Metrics provide an easy performance overview. Just like determining which data is relevant, the first task is to determine which metrics should be established. Dashboards with near real-time metrics should be made available for management to quickly identify trends. For operational activities dashboards can also be made to spot operational issues. In this stage, the focus should be on easily accessible metrics, which can later be replaced by more advanced derived metrics backed by analytical models. Overall there is a focus on current performance, not yet on long-term progression.
Determine critical metrics.
Create basic dashboards with the most important metrics.
In this stage, basic metrics are collected and displayed in dashboards. Because you are collecting metrics for a longer time you can now also track KPI's over time. This provides additional insight over the progression of the organization. Make sure to fully realize what drives the KPI. KPI's are the outcome of a process. Focusing on a correct process will provide long-term results, while artificially inflating KPI's only serves the short-term. You now also have the capability to create KPI's backed by analytical models. For a customer lifetime value (CLV) analysis you need a lot of historical knowledge. If you can create an analytical model that predicts the customer lifetime value for a new customer, you can estimate how much you can spend to attract this customer. The CLV can also serve as a KPI that can be tracked.
Define more advanced KPI's.
Track KPI's over time; focus on long-term results.
Create analytical models to back analytical KPI's.
Reports are now standardized and dashboards are available to management. Derived KPI's, backed by analytical models, are proven to be very valuable indicators. The next step is to move this process to real-time operations. Real-time dashboards reveal operational insight, a real-time state of operations. Anomalies are quickly detected and resolved. Continue to show how KPI's evolve over time. It can be a powerful argument for continuing the investments in analytical efforts.
Define and show operational metrics in real-time.
Create a process to rapidly detect and deal with defects, anomalies, and trends.
Instead of focusing on data that is externally oriented, e.g. data about customers or prospects, you can also collect data that is internally oriented, toward your own processes. These metrics can be used to steer the company, and improve the quality of the processes. Quality management concepts, such as Six Sigma, heavily rely on accurate collection of metrics. Amazon uses analytics to perfect their logistics processes, and they collect a lot of data to do so. But, you can also look on how we can collect data to analyze employee performance. Are there predictors for future performance, or if an applicant will be a good hire? Google is known for quantifying their performance management program. The important thing to ask right now is how you can correctly measure these kinds of metrics. Collecting data is one thing, but collecting the right data can be hard. A mix of domain knowledge and statistical knowledge is necessary to come up with the right kind of metrics.
Collect metrics about internal processes if you have not done so already
Steer and optimize based on internal metrics
Look for new opportunities to apply metrics and performance management
Metrics are being collected everywhere in the organization, and are being actively used to improve products and processes. KPI's are standardized across the organization. Advanced analytical KPI's are used for strategic goals, and are leading indicators for company performance. They allow organizations to better focus their efforts and measure the success. New KPI's may be introduced that are more in line with the redefined business model of the organization. KPI's have the ability to clearly communicate and incentivize priorities within the organization. Metrics are also being used more broadly to track internal processes and goals, such as employee performance or satisfaction. Metrics found from methods such as cohort analysis can be useful to measure the progress of new ventures. \textit{Innovation accounting} is a technique to measure the success of new ventures instead of relying on traditional accounting methods, which may not be suitable for measuring the success of new innovation.
Standardize KPI's across the organization
Track new ventures using innovation accounting methods, instead of traditional metrics