Performance measures are analyzed to understand the performance of a solution when compared to the value that it provides to the organization.
To analyze the solution’s performance measures, the business analyst needs to completely understand the value that the solution can provide.
The solution’s performance results would include data on performance measures variables such as the goals and objectives of the organization, key performance indicators (KPIs), the risk level of the solution and the risk tolerance of the organization.
Once this information is gathered, then it can be analyzed to understand how well the solution is performing when compared to the business needs that it was implemented to fulfill.
So how do you analyze the solution’s performance measures ?
There are five elements which can help with the performance measures analysis and they are :
1. Solution Performance versus Desired Value: the process starts with analyzing the performance measures that have been collected so that you can understand the solution’s value.
A solution might be performing very well for example an online ordering system, but it might also provide lower than expected value when compared to the business requirements that it is meant to fulfill.
While a low performing but potentially valuable solution, for example a time carding system, might be inefficient but it can also be enhanced to increase its performance level.
If the performance measures are not detailed enough to help the stakeholders determine the solution value, then the business analyst would have to either collect more performance measurements or treat the lack of measures as a solution risk.
2. Risks: the next step in the process is to analyze the solution’s risks.
The solution’s performance measures may expose new risks to the solution performance and the organization.
So these risks need to be identified and managed like any other risks.
3. Trends: then you would need to identify trends in the solutions performance.
Once the performance data is collected, the business analyst needs to analyze this data while considering the time period in which the data was collected to safe guard against anomalies and skewer trends.
The data collected should also include a large enough sample size over an adequate time period to provide an accurate picture of the solution performance which can be used to make decisions.
Any noticeable and repeated trends, such as an increase in errors at certain times or a change in process speed when the volume is increased should be noted.
4. Accuracy: then you would need to ensure that the performance measures used are accurate.
The solution’s performance measures need to be accurate to ensure the validity of their analysis, so the business analyst needs to test and analyze the data collected by the performance measures to ensure that they are accurate.
To be considered accurate and reliable, the results of performance measures should be reproducible and repeatable.
5. Performance Variances: the final step is to identify variances.
Any variance between the expected and actual performance of the solution should be considered when analyzing solution performance.
A root cause analysis may be necessary to determine the underlying causes of significant variances within a solution.