Designing an Operating Model for CJA Success
In the third session of our CJA VRA Series, learn why establishing a cohesive operating model to support your measurement program is so critical in avoiding future resourcing challenges, enhancing efficiencies, and maximising your ability to scale.
Key Discussion Points
- Developing an effective team operating model strategy within your measurement program that aligns with your strategic goals
- How a clearly defined operating model ensures alignment and efficiency maximising the value from your measurement program long-term
- Guidance on how your measurement program can work cross-functionally with your organisation to achieve common goals and objectives
Build Effective Governance Cadence
Establishing a structured governance cadence ensures smooth operations and alignment:
- Annual Strategy Meetings Focus on identifying value drivers, updating KPIs, and reviewing roadmaps.
- Quarterly Analytics Reviews Refine roadmaps, assess progress, and plan enterprise enablement.
- Monthly Leadership Check-ins Address escalations, review objectives, and track KPIs.
- Bi-Weekly Discussions Resolve blockers, prioritize tasks, and monitor risks.
- Daily Working Team Activities Handle day-to-day operations and ensure progress.
Tailor this cadence to your organization’s needs to maintain alignment and foster collaboration across teams.
Map Critical CJA Roles
Understanding the key roles in Customer Journey Analytics (CJA) is essential for success.
- Product Owner This person is responsible for managing the roadmap, which is like a plan for how the analytics system will grow and improve over time. They also handle access (who can use the system) and governance (making sure the system is used properly). Their main job is to ensure everything aligns with the business’s goals.
- Data Architect Think of this role as the designer of the data system. They create data models (blueprints for organizing information), oversee ingestion processes (how data is brought into the system), and make sure the data is accurate and reliable.
- Digital Analytics Manager This role focuses on reporting. They lead efforts to create reports that summarize the data, maintain data integrity (making sure the data is correct and trustworthy), and ensure the insights from the data can be used to make decisions.
- Subject Matter Experts These are the analysts and consumers who work directly with the data. They generate reports and analyze customer behaviors to uncover patterns and trends.
Extended roles, such as data scientists and enterprise architects, bring specialized skills for more advanced analytics tasks. Mapping these roles helps ensure all aspects of the analytics process are covered and highlights any gaps in the team. Sometimes, one person might take on multiple roles depending on their skills, so flexibility is important for success.