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Optimize Your Application Maintenance Estimation (AME) Process
Augment your traditional estimation with parametric estimation to reduce surprises.
This research is designed for an Application Development Manager who:
• Has to defend maintenance budgets to business executives.
• Needs to understand the gaps that currently exist in his or her unbalanced estimation process.
• Wants to know what metrics to measure prior to a wider rollout.
• Requires an understanding of the various expert and parametric estimation techniques to make an informed decision.
Schools of thought:
Parametric estimation: Use of analytic formulas to derive estimation.
Expert estimation: Use of analogy and experience to derive estimation.
Hybrid (our recommendation): Combination of at least one parametric and expert to balance the approaches.
Drivers/Trends/Change:
Applications are getting more complex for future estimation.
Velocity of development teams is increasing while the number of resources is not rising as quickly.
Users are demanding quality apps.
Value Creation:
For the development team: Having the right funding will enable enough time and budget to do it right.
IT: Ability to clearly set expectations and justify costs to the business.
Business: Improving overall quality of produced deliverable.
Understand the Project Rationale A historic portfolio is essential in establishing your estimation model. It will allow you to assess your first
pass draft estimation against known values to establish early confidence.
Structure Your Application Maintenance Estimation Optimization Team Development team estimators and process analysts should exhibit some
manner of subject matter expertise and authority. Otherwise, the estimates will not be justifiable to the business. The right people must be
involved in the optimization effort for the result to have credibility.
Analyze Your Current Process Gaps Inevitably a single mode estimation approach will lead to inaccuracies that are difficult to catch early.
Optimize Your Estimation Process This exercise is a model training initiative. You are trying to create a model using historic information to
help make a future informed decision. If your historic project data is not clean, this step will not automatically rectify the meta issue around
quality.
Implement Your New Estimation Process A gradual rollout for estimation will help ensure that any conflicts will not arise at one time and
overwhelm the operational team. By focusing on a smaller set of projects, any estimation discrepancies can be managed in a controlled manner.
Measure Ongoing ValueAny maintenance project that was a significant outlier in your trends can be the symptom of a bigger problem. Take the
time to address these outliers in terms of risk for future maintenance projects. Inject a modified risk assessment into your new maintenance
estimation process.
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process
Optimize the Application Maintenance Estimation (AME) Process

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Optimize the Application Maintenance Estimation (AME) Process

  • 1. Optimize Your Application Maintenance Estimation (AME) Process Augment your traditional estimation with parametric estimation to reduce surprises. This research is designed for an Application Development Manager who: • Has to defend maintenance budgets to business executives. • Needs to understand the gaps that currently exist in his or her unbalanced estimation process. • Wants to know what metrics to measure prior to a wider rollout. • Requires an understanding of the various expert and parametric estimation techniques to make an informed decision. Schools of thought: Parametric estimation: Use of analytic formulas to derive estimation. Expert estimation: Use of analogy and experience to derive estimation. Hybrid (our recommendation): Combination of at least one parametric and expert to balance the approaches. Drivers/Trends/Change: Applications are getting more complex for future estimation. Velocity of development teams is increasing while the number of resources is not rising as quickly. Users are demanding quality apps. Value Creation: For the development team: Having the right funding will enable enough time and budget to do it right. IT: Ability to clearly set expectations and justify costs to the business. Business: Improving overall quality of produced deliverable. Understand the Project Rationale A historic portfolio is essential in establishing your estimation model. It will allow you to assess your first pass draft estimation against known values to establish early confidence. Structure Your Application Maintenance Estimation Optimization Team Development team estimators and process analysts should exhibit some manner of subject matter expertise and authority. Otherwise, the estimates will not be justifiable to the business. The right people must be involved in the optimization effort for the result to have credibility. Analyze Your Current Process Gaps Inevitably a single mode estimation approach will lead to inaccuracies that are difficult to catch early. Optimize Your Estimation Process This exercise is a model training initiative. You are trying to create a model using historic information to help make a future informed decision. If your historic project data is not clean, this step will not automatically rectify the meta issue around quality. Implement Your New Estimation Process A gradual rollout for estimation will help ensure that any conflicts will not arise at one time and overwhelm the operational team. By focusing on a smaller set of projects, any estimation discrepancies can be managed in a controlled manner. Measure Ongoing ValueAny maintenance project that was a significant outlier in your trends can be the symptom of a bigger problem. Take the time to address these outliers in terms of risk for future maintenance projects. Inject a modified risk assessment into your new maintenance estimation process.