Tool Mapping Guide
How to use this guide
- Identify which practices you are implementing or improving
- Review the tool categories relevant to those practices
- Evaluate tools against your organization's Four Dimensions: technology fit, team skills, vendor relationships, and data requirements
- Start with tools you already have (guiding principle: "Start where you are")
ITSM Platforms (Multi-Practice)
These platforms support multiple ITIL practices in a single solution.
| Platform | Primary Strength | Practices Covered | Typical Organization |
|---|---|---|---|
| ServiceNow | Enterprise ITSM + ITAM + CMDB | Incident, Problem, Change, Service Desk, CMDB, Knowledge, SLM | Large enterprise (1,000+ IT staff) |
| Jira Service Management | Agile + ITSM integration | Incident, Problem, Change, Service Request, Knowledge | Mid-size, engineering-centric |
| Freshservice | Fast setup, modern UX | Incident, Problem, Change, Asset, Service Catalogue | SMB to mid-size |
| BMC Helix | Enterprise, AI-powered | Incident, Problem, Change, CMDB, SLM, Knowledge | Large enterprise |
| ManageEngine ServiceDesk Plus | Cost-effective, on-premises option | Incident, Problem, Change, Asset, CMDB | Mid-size, budget-conscious |
| Ivanti Neurons | Automation + discovery | Incident, Problem, Change, Asset, Endpoint | Mid-size to enterprise |
💡
Selection guidance: Your ITSM platform is the most consequential tool decision. Evaluate based on: (1) practices needed today, (2) integration with existing tools, (3) total cost of ownership, (4) ability to grow with maturity, and (5) vendor lock-in risk.
Practice-by-Practice Tool Mapping
Incident and Problem Management
| Tool Category | Examples | Purpose |
|---|---|---|
| Alerting and on-call | PagerDuty, Opsgenie, VictorOps | Route alerts to the right person; on-call scheduling |
| Communication (war room) | Slack, Microsoft Teams, Zoom | Major incident communication and swarming |
| Status pages | Statuspage, Instatus, Cachet | Communicate service status to users |
| Post-incident analysis | Jeli, Incident.io, FireHydrant | Structured post-incident reviews and learning |
Monitoring and Event Management
| Tool Category | Examples | Purpose |
|---|---|---|
| Infrastructure monitoring | Datadog, Zabbix, Nagios, Prometheus | Server, network, and infrastructure health |
| Application performance (APM) | Datadog APM, New Relic, Dynatrace | Application-level performance tracking |
| Log management | Splunk, Elastic (ELK), Grafana Loki | Centralized logging and search |
| Real user monitoring (RUM) | Google Analytics, Datadog RUM, Sentry | User experience from the consumer's perspective |
| Synthetic monitoring | Pingdom, Checkly, Grafana Synthetic | Proactive testing of service availability |
| AIOps | BigPanda, Moogsoft, Datadog AI | AI-powered event correlation and noise reduction |
Change Enablement
| Tool Category | Examples | Purpose |
|---|---|---|
| CI/CD pipelines | GitLab CI, GitHub Actions, Jenkins, Azure DevOps | Automated build, test, and deployment |
| Infrastructure as Code | Terraform, Pulumi, AWS CloudFormation | Automated infrastructure provisioning |
| Feature flags | LaunchDarkly, Unleash, Flagsmith | Controlled feature rollout and rollback |
| Policy-as-code | Open Policy Agent, Sentinel, Kyverno | Automated governance and compliance checks |
Service Configuration and Asset Management
| Tool Category | Examples | Purpose |
|---|---|---|
| CMDB/discovery | ServiceNow CMDB, Device42, Lansweeper | Discovery and tracking of configuration items |
| Software asset management | Flexera, Snow Software, ServiceNow SAM | License management and compliance |
| Cloud asset management | AWS Config, Azure Resource Graph, GCP Asset Inventory | Cloud resource tracking |
Knowledge Management
| Tool Category | Examples | Purpose |
|---|---|---|
| Wiki/documentation | Confluence, Notion, GitBook, Nextra | Internal documentation and knowledge base |
| Video knowledge | Loom, Scribe, Tango | Step-by-step guides and tutorials |
| AI-assisted search | Guru, Glean, Microsoft Copilot (M365) | AI-powered knowledge discovery |
Financial Management and FinOps
| Tool Category | Examples | Purpose |
|---|---|---|
| Cloud cost management | Kubecost, Vantage, CloudHealth, AWS Cost Explorer | Cloud spend visibility and optimization |
| IT financial management | Apptio, ServiceNow ITFM | IT cost allocation and chargeback |
| License optimization | Flexera, Snow Software | Software spend optimization |
Service Level Management
| Tool Category | Examples | Purpose |
|---|---|---|
| SLO/SLI tracking | Datadog SLOs, Nobl9, Blameless | Define and track service level objectives |
| XLA/experience measurement | Nexthink, 1E, Lakeside | Experience Level Agreements (digital experience) |
| Survey/feedback | Qualtrics, SurveyMonkey, Typeform | Customer and user satisfaction measurement |
Architecture Management
| Tool Category | Examples | Purpose |
|---|---|---|
| Enterprise architecture | LeanIX, Ardoq, Mega HOPEX | Architecture modelling and decision support |
| Diagramming | Miro, Lucidchart, diagrams.net | Architecture visualization |
| API management | Kong, Apigee, AWS API Gateway | API lifecycle management |
Project and Portfolio Management
| Tool Category | Examples | Purpose |
|---|---|---|
| Project management | Jira, Asana, Monday.com, Microsoft Project | Task and project tracking |
| Portfolio management | Planview, ServiceNow PPM, Clarity | Portfolio-level prioritization and resource allocation |
| OKR tracking | Gtmhub (Quantive), Weekdone, Perdoo | Objectives and Key Results tracking |
AI-Specific Tools for DPSM (2025-2026)
ITIL v5 introduces the 6C AI Capability Model. Here is how each capability maps to available tools:
| AI Capability | Purpose | Tool Examples |
|---|---|---|
| Creation | Generating content, code, configurations | GitHub Copilot, Amazon CodeWhisperer, ChatGPT |
| Curation | Organizing, classifying, categorizing data | AI-powered ticket classification (ServiceNow AI), intelligent routing |
| Clarification | Extracting insights from complex data | Splunk AI, Elastic AI Assistant, Grafana AI |
| Cognition | Decision-making and pattern recognition | AIOps (BigPanda, Moogsoft), predictive analytics |
| Communication | Interacting with users in natural language | Virtual agents (ServiceNow Virtual Agent, Freshservice Freddy AI) |
| Coordination | Orchestrating complex workflows | Automation platforms (ServiceNow Flow Designer, n8n, Zapier) |
⚠️
AI governance note: The ITIL v5 book emphasizes that AI tools must be governed. Before deploying AI tools, assess: data quality, bias risks, compliance requirements, and human oversight needs.
Tool selection decision framework
| Criterion | Questions to Ask | Weight |
|---|---|---|
| Business fit | Does it solve the problem we have? Not the one the vendor describes? | High |
| Integration | Does it connect with our existing tools? API availability? | High |
| Maturity match | Is it appropriate for our maturity level? (Enterprise tools for Level 1 maturity often fail) | High |
| Total cost | Licensing + implementation + training + ongoing maintenance? | Medium |
| Vendor stability | Is the vendor likely to exist in 5 years? Open-source alternative? | Medium |
| Lock-in risk | Can we export our data? Is the format open? | Medium |
| Team skills | Can our team operate it without external consultants? | Medium |
Related pages
- Automation Tools (Appendix D reference)
- AI Governance (6C Model)
- Templates (practical templates for each practice)
- Practice Cards (34 practice quick reference)
- Platform Engineering (platform strategy)