Complete framework application for ITSM transformation project
Understanding how IT service customers interact with ITSM systems across all touchpoints
IT infrastructure requires proactive monitoring; systems show early warning signs of potential failures
Issue manifests (system down, slow performance); user recognizes need for IT support
User checks knowledge base, searches for solutions, or decides to contact help desk
User chooses self-service resolution, submits ticket, or calls support based on urgency
Ticket created and prioritized; resources allocated; timeline established
Support team acknowledges ticket; begins diagnosis and troubleshooting process
Issue is resolved; solution implemented; user functionality restored
Follow-up confirmation; satisfaction survey; documentation of resolution
Why does the customer engage? IT systems are critical for business operations. Downtime costs thousands per hour. Users need immediate, reliable support.
How do they order and pay? Submit tickets via portal, email, or phone. Priority queues determine response time. Premium SLAs available for mission-critical services.
What products/services provided? Incident management, problem resolution, change management, asset management, knowledge base access, proactive monitoring.
Identifying customer friction and willingness-to-pay drivers at each journey stage
| Stage | Pain Points | Impact | WTP Drivers |
|---|---|---|---|
| Latent Need | No proactive detection; issues discovered only after failure; reactive firefighting mode | HIGH COST Unexpected downtime, emergency responses |
Predictive analytics, proactive monitoring, automated alerts |
| Awareness | Users don't know if issue is local or systemic; unclear how to escalate; uncertainty about resolution time | FRUSTRATION Productivity loss, repeated attempts |
Instant status visibility, AI-powered diagnostics, transparent timelines |
| Search | Knowledge base outdated or hard to search; solutions not contextualized; high effort required | TIME WASTE 30+ min searching before ticket submission |
Intelligent search, personalized recommendations, guided troubleshooting |
| Decide | Unclear which option is best; lack of guidance on self-service vs escalation; no confidence in resolution path | POOR DECISIONS Unnecessary escalations or delayed reporting |
AI recommendations based on issue type, success probability scores |
| Order & Pay | Manual ticket categorization by operators; incorrect routing; priority assessment delays | INEFFICIENCY Operators spend 40% time on categorization |
Automatic ticket classification, intelligent routing, priority algorithms |
| Receive | Long wait for acknowledgment; no visibility into queue position; uncertain response time | ANXIETY Users repeatedly check status, call help desk |
Real-time status updates, estimated resolution times, proactive communication |
| Experience | Resolution quality varies by operator; inconsistent solutions to similar problems; lack of knowledge transfer | INCONSISTENCY Repeat issues, trust erosion |
Standardized workflows, AI-guided resolution, best practice suggestions |
| Post-Purchase | No follow-up on underlying issues; reactive fixes without root cause analysis; lessons not captured | RECURRENCE Same issues repeat 40% of the time |
Root cause analysis, preventive recommendations, continuous improvement tracking |
Mapping data triggers, frequency, richness, and improvement opportunities
Exploring deeper motivations (Why) and specific implementations (How)
In the eyes of the customer, the purpose of the relationship with our ITSM firm is to: "Ensure uninterrupted business operations through invisible, proactive IT support that prevents problems before they occur, allowing employees to focus on their work rather than technology obstacles."
Level 1: Fix IT issues when they break
Level 2: Prevent disruptions to productivity
Level 3: Enable organizational performance and growth
Level 4: Build competitive advantage through technology reliability
Level 5: Achieve strategic business outcomes with technology as an enabler, not a constraint
Implementation 1: 24/7 help desk with ticket management system
Implementation 2: Proactive monitoring with AI-powered predictive alerts
Implementation 3: Automated incident resolution and intelligent self-service
Implementation 4: Continuous learning system that improves with every interaction
Implementation 5: Strategic IT partnership with predictive analytics, capacity planning, and continuous optimization
Mapping pain points to Connected Strategy archetypes with required information
AI chatbots provide instant responses to queries 24/7. Virtual agents handle basic troubleshooting immediately without wait times.
Required Info: NLP training data, common issues database, response templates
Personalized troubleshooting recommendations based on user history, system context, and similar issue patterns.
Required Info: User behavior data, resolution success rates, contextual system info
Interactive workflows guide users through self-service resolution with step-by-step AI assistance and validation.
Required Info: Task completion rates, user skill levels, workflow success patterns
AI automatically categorizes, prioritizes, and routes tickets. Routine resolutions executed without human intervention.
Required Info: Historical ticket data, routing rules, automation playbooks, system integration APIs
Phase 1 (Q1-Q2): Automatic Execution for ticket routing + Respond-to-Desire chatbots for common issues
Phase 2 (Q2-Q3): Curated Offering with personalized recommendations + Coach Behavior for self-service
Phase 3 (Q4+): Full integration across all archetypes with predictive analytics and continuous learning
How the system improves through accumulated customer interactions
Basic AI learns common issues, ticket patterns, and initial user preferences
Routing algorithms improve with initial feedback; chatbot responses refined
Identify gaps in knowledge base; create targeted self-service content
10% reduction in manual categorization time; baseline metrics established
Understand peak demand periods, common failure modes, user frustration points
Personalized recommendations for frequent users; department-specific workflows emerge
Resolution time improves 25%; first-contact resolution increases to 45%
Proactive monitoring alerts for predicted failures; preventive maintenance workflows
20% operator time savings; 40% of routine tickets automated
Recognize need for predictive analytics, not just reactive support
User-specific success patterns identified; adaptive interfaces adjust to skill level
AI predicts issues before user awareness; proactive notifications prevent 30% of tickets
Capacity planning service based on usage patterns; optimization recommendations
30% time savings achieved; resolution speed increased 40%
Shift from problem-solving to performance optimization mindset
Fully personalized support experience; AI knows organizational context and history
50% resolution time reduction achieved; 62% first-contact resolution rate
Strategic IT consulting based on data insights; continuous improvement partnership
35% operator workload reduction; cost savings of 20% realized
Enable strategic business outcomes through technology reliability and innovation
The system doesn't just maintain performance—it gets exponentially better. Each interaction trains the AI, making predictions more accurate, automations smarter, and personalization deeper. By month 12, the AI prevents problems that users don't even know were coming, optimizes performance proactively, and provides strategic insights for business planning. This creates a sustainable competitive moat: the longer a customer uses the system, the more valuable it becomes, making switching costs prohibitively high.
Connected Strategy Framework • Complete Analytical Worksheets
← Back to Main PortfolioStrategic Management Project • Wharton Business School • July 2024