Consultancy evaluation · Step 2 of 5
See where your business benefits
Assess where AnalyticsCreator could improve delivery capacity, consistency and commercial performance, without reducing the role of your consultants or weakening the customer relationship.
The commercial question
Can you deliver more without turning your expertise into a commodity?
The business case for AnalyticsCreator is not simply that it can generate technical assets faster. The more important question is whether it allows your consultancy to use scarce engineering capacity more effectively while maintaining delivery quality, customer ownership and professional service value.
The strongest fit is usually found where teams repeatedly solve similar engineering problems across different customers, but still need each solution to reflect the customer’s architecture, business rules and operating environment.
AnalyticsCreator can standardise and generate repeatable engineering work. Your consultants remain responsible for discovery, architecture, business logic, implementation, testing and the customer relationship.
The main business levers
Where value may appear in your consultancy
The exact benefit depends on your project mix, team structure, delivery standards and commercial model. These are the principal areas to assess.
Deliver more with the team you already have
Reduce the amount of repetitive modelling, coding, documentation and technical alignment performed manually by experienced engineers.
Apply shared delivery standards
Use common modelling, historisation, naming, deployment and documentation approaches across consultants and customer projects.
Protect effort from avoidable rework
Reduce the effort required to reconcile database, pipeline, semantic, deployment and documentation assets when the design changes.
Reduce dependency on a few senior people
Capture design decisions and delivery logic in structured metadata so that knowledge is less dependent on individual memory or undocumented project conventions.
Create a stronger basis for ongoing work
Maintain a reusable design foundation that can support extensions, migrations, managed services, documentation and future customer change requests.
Keep the solution in the customer environment
Deliver native technical assets that run within the customer’s Microsoft environment without requiring a separate AnalyticsCreator production runtime.
Across the project lifecycle
Where the benefit enters the delivery process
Architecture and design
Start from a structured model and agreed delivery standards rather than translating requirements separately into each technical layer.
Engineering
Generate repeatable technical assets while engineers focus on architecture, transformation logic and customer-specific requirements.
Delivery and change
Regenerate dependent assets when the design changes, reducing manual reconciliation between layers and documentation.
Ongoing services
Reuse the governed model as a basis for enhancements, support, migration, documentation and further customer development.
What changes in the work
Less low-value repetition. More focus on expert services.
The purpose is not to remove consulting work. It is to shift effort away from tasks that are difficult to differentiate and towards work for which customers need your experience.
Work that can become more repeatable
- Creating standard warehouse structures
- Repeating common loading and historisation patterns
- Maintaining alignment between technical layers
- Recreating documentation after changes
- Applying naming and modelling standards manually
- Rebuilding similar delivery assets across projects
Work that remains consultancy-led
- Customer discovery and stakeholder alignment
- Architecture and technology selection
- Business definitions and transformation logic
- Security, testing and operational design
- Adoption and change management
- Managed services and ongoing customer development
Commercial assessment
Questions to test in your own delivery model
A credible business case should be based on your actual project economics rather than a generic productivity claim.
- How much senior engineering time is currently spent on repeatable implementation work?
- How often do similar technical patterns recur across customer projects?
- How much non-billable rework is caused by changes between models, pipelines, semantic layers and documentation?
- How long does it take a new consultant to understand and work safely within your delivery standards?
- Are fixed-price projects exposed to margin loss when the design changes late in delivery?
- Could additional delivery capacity be converted into more projects or shorter lead times?
- Could a maintained metadata model support follow-on, migration or managed-service revenue?
- Is customer ownership strengthened by delivering native assets without a proprietary production runtime?
Licence cost is only one side of the calculation. The other side includes engineering capacity, project duration, rework, onboarding, consistency, margin exposure and the value of future customer services.
Reasons not to proceed
Where the business case may be weak
AnalyticsCreator will not be equally relevant to every consultancy or every project. A rational evaluation should also identify where the expected benefit is limited.
Every engagement is entirely different
The benefit is reduced where projects contain few reusable patterns and almost no repeated engineering structures.
Your delivery is outside the Microsoft data stack
The strongest fit is for consultancies delivering data warehouse and analytics solutions within Microsoft environments.
Projects are too small to justify structured engineering
Very small, one-off reporting projects may not provide enough delivery complexity or reuse to support a meaningful business case.
The question is whether your consultancy performs enough repeatable Microsoft data engineering work for a shared, metadata-driven design foundation to create measurable commercial value.
