Success Metrics
There are two formatting options available. The traditional desired outcome statement is a structure used in the Outcome-Driven Innovation methodology. Since many stakeholders - especially when involved with marketing or UX teams - push back on the awkward nature of desired outcomes statements since people don’t talk like that, the alternative is a natural language structure that gets to the heart of the outcome and tries to avoid tasks and activities where feasible.
This catalog contains 20 potential metrics using each formatting option. You will likely need to reduce this set for a survey. The number of statements that have been generated is arbitrary and can be expanded to accommodate your needs.
Desired Outcome Statements (ODI)
- Minimize the time it takes to identify potential improvement areas, e.g., user interface enhancements, faster processing, etc.
- Minimize the time it takes to assess current solution's performance limitations, e.g., speed bottlenecks, capacity issues, etc.
- Minimize the time it takes to evaluate customer feedback for upgrade relevance, e.g., feature requests, usability concerns, etc.
- Minimize the time it takes to prioritize upgrade features based on impact and feasibility, e.g., cost-benefit analysis, technical complexity, etc.
- Minimize the time it takes to align upgrade objectives with business goals, e.g., market expansion, customer satisfaction, etc.
- Minimize the time it takes to research emerging technologies for potential integration, e.g., AI capabilities, cloud computing, etc.
- Minimize the time it takes to estimate resource requirements for the upgrade, e.g., budget, manpower, equipment, etc.
- Minimize the time it takes to formulate a risk management plan for the upgrade process, e.g., mitigation strategies, backup plans, etc.
- Minimize the time it takes to establish key performance indicators for the upgrade, e.g., system uptime, user adoption rates, etc.
- Minimize the time it takes to ensure compatibility with existing systems and infrastructure, e.g., software dependencies, hardware constraints, etc.
- Minimize the time it takes to forecast the upgrade's impact on current operations, e.g., downtime, training needs, etc.
- Minimize the time it takes to develop a communication plan for stakeholder engagement, e.g., regular updates, feedback channels, etc.
- Minimize the time it takes to outline a detailed implementation timeline, e.g., milestones, deliverables, deadlines, etc.
- Minimize the likelihood of overlooking legal and compliance requirements, e.g., data privacy laws, industry regulations, etc.
- Minimize the time it takes to identify potential third-party collaborations or partnerships, e.g., technology vendors, service providers, etc.
- Minimize the likelihood of underestimating the technical challenges during the upgrade, e.g., system integration issues, compatibility problems, etc.
- Minimize the time it takes to evaluate the long-term sustainability of the upgrade, e.g., future-proofing, scalability, etc.
- Minimize the time it takes to assess the potential for customer disruption during the upgrade, e.g., service interruptions, learning curves, etc.
- Minimize the time it takes to develop contingency plans for unexpected challenges, e.g., budget overruns, delays, technical setbacks, etc.
- Minimize the time it takes to gather and analyze competitive intelligence to inform the upgrade, e.g., market trends, competitor strategies, etc.
Customer Success Statements (PJTBD)
- Identify potential improvement areas, e.g., user interface enhancements, faster processing, etc.
- Assess current solution's performance limitations, e.g., speed bottlenecks, capacity issues, etc.
- Evaluate customer feedback for upgrade relevance, e.g., feature requests, usability concerns, etc.
- Prioritize upgrade features based on impact and feasibility, e.g., cost-benefit analysis, technical complexity, etc.
- Align upgrade objectives with business goals, e.g., market expansion, customer satisfaction, etc.
- Research emerging technologies for potential integration, e.g., AI capabilities, cloud computing, etc.
- Estimate resource requirements for the upgrade, e.g., budget, manpower, equipment, etc.
- Formulate a risk management plan for the upgrade process, e.g., mitigation strategies, backup plans, etc.
- Establish key performance indicators for the upgrade, e.g., system uptime, user adoption rates, etc.
- Ensure compatibility with existing systems and infrastructure, e.g., software dependencies, hardware constraints, etc.
- Forecast the upgrade's impact on current operations, e.g., downtime, training needs, etc.
- Develop a communication plan for stakeholder engagement, e.g., regular updates, feedback channels, etc.
- Outline a detailed implementation timeline, e.g., milestones, deliverables, deadlines, etc.
- Avoid overlooking legal and compliance requirements, e.g., data privacy laws, industry regulations, etc.
- Identify potential third-party collaborations or partnerships, e.g., technology vendors, service providers, etc.
- Avoid underestimating the technical challenges during the upgrade, e.g., system integration issues, compatibility problems, etc.
- Evaluate the long-term sustainability of the upgrade, e.g., future-proofing, scalability, etc.
- Assess the potential for customer disruption during the upgrade, e.g., service interruptions, learning curves, etc.
- Develop contingency plans for unexpected challenges, e.g., budget overruns, delays, technical setbacks, etc.
- Gather and analyze competitive intelligence to inform the upgrade, e.g., market trends, competitor strategies, etc.
Test Fit Structure
Apply this to Customer Success Statements only. Everything should fit together nicely. Here’s an article where I introduced the concept. Feel free to devise your own version for Desired Outcome Statements as this does not apply to their format directly.
As a(n) [end user] + who is + [Job] you're trying to [success statement] + "faster and more accurately" so that you can successfully [Job Step]