Consultancy evaluation · Step 5 of 5
Start with one project
Select a bounded first project, define what success means and use real delivery work to prove the technical and commercial fit of AnalyticsCreator.
The purpose
Prove the decision through delivery, not another presentation
The first project should provide enough real engineering work to test AnalyticsCreator properly, while remaining small enough to control risk and learn from the result.
It should not be a disconnected technical experiment. The project should reflect the type of Microsoft data solution your consultancy regularly delivers and include the people who would use AnalyticsCreator in practice.
The goal is to determine whether AnalyticsCreator improves your actual delivery process, fits your architecture and creates enough measurable value to justify wider adoption.
Project selection
What makes a suitable first project?
Select a project that represents your normal delivery work without making the first attempt dependent on the most complex customer situation in your pipeline.
Similar to your normal customer work
The architecture, data sources and delivery requirements should resemble projects your consultancy expects to repeat.
A clearly defined scope
Select a manageable set of sources, models, transformations and outputs with an agreed beginning and end.
Results can be compared
The team should be able to compare effort, quality, consistency and change handling with its normal delivery approach.
Includes repeatable engineering work
The project should contain enough modelling, loading, historisation, deployment or documentation work to test the value of structured generation.
Within the technical fit
The target architecture should fall within the supported Microsoft delivery scope established during the technical evaluation.
Low operational risk
Avoid making the first project dependent on an urgent production deadline, unresolved architecture or unusually complex customer politics.
Project suitability
Good candidates and poor candidates
A strong first-project candidate
- Uses a familiar Microsoft data architecture
- Includes recurring warehouse and integration patterns
- Has accessible source metadata and requirements
- Has a defined model, output and delivery boundary
- Includes engineers who may use AnalyticsCreator again
- Allows effort and quality to be measured
- Has an engaged customer or internal stakeholder
- Can tolerate a structured learning process
A weak first-project candidate
- Is already in delivery crisis
- Depends on unresolved technology decisions
- Uses an architecture outside the supported scope
- Contains almost no repeatable engineering patterns
- Has incomplete or constantly changing requirements
- Has no technical owner available for evaluation
- Cannot provide access to required metadata
- Treats the exercise as an isolated product demonstration
Project scope
Define the test before the work begins
The first project should have a written scope that establishes what AnalyticsCreator will be used for, what remains outside the evaluation and which outputs will be reviewed.
Select the inputs
Agree the source systems, metadata, tables and business requirements that will form the project boundary.
Define the design
Confirm the target architecture, modelling approach, layers, historisation and transformation requirements.
Agree the outputs
Identify which database, integration, semantic, deployment, lineage and documentation assets will be generated and reviewed.
Measure the result
Compare the generated solution, delivery effort and change process against agreed technical and commercial success criteria.
Success criteria
Decide what must be proven
Success criteria should cover both the technical result and the effect on delivery. Avoid defining success only as generating code or completing the project.
Architecture fit
The model and generated assets follow the agreed architecture, layering and technology choices.
Output quality
Engineers consider the generated assets understandable, maintainable and suitable for customer delivery.
Delivery consistency
The implementation follows agreed modelling, naming, historisation, deployment and documentation standards.
Change handling
A representative design change can be made and dependent assets can be updated without excessive manual reconciliation.
Engineering effort
The team can identify which repetitive tasks were reduced and where expert engineering effort was still required.
Consultant adoption
The delivery team can understand the model-first process and sees a practical route to using it on future projects.
Customer ownership
The generated solution can be deployed and operated in the customer environment without an AnalyticsCreator production runtime.
Commercial relevance
The result provides credible evidence of improved capacity, margin protection, risk reduction or future service potential.
Measurement
Capture evidence, not impressions
Record the starting assumptions before the project begins. This makes the final decision less dependent on whether the team simply liked the product or enjoyed the demonstration.
- Estimated effort using the current delivery method
- Actual effort spent designing and generating the solution
- Time spent on custom logic outside generated patterns
- Number and type of technical assets produced
- Effort required to implement a representative change
- Manual reconciliation avoided between technical layers
- Documentation and lineage produced from the design
- Time required for an additional consultant to understand the project
- Technical issues or unsupported requirements discovered
- Expected commercial value if the approach is reused
A faster build is valuable only when the result also meets the required architecture, quality, maintainability and customer ownership standards.
Roles and responsibilities
Involve the people who will make the wider decision
Commercial owner
Confirms why the project matters, what commercial value is expected and what evidence is required for a wider investment decision.
Technical decision-maker
Validates the modelling approach, generated architecture, technical boundaries and compatibility with delivery standards.
Hands-on user
Builds the project, assesses the workflow and records where AnalyticsCreator improves or complicates normal engineering work.
Delivery owner
Protects the agreed scope, monitors effort and ensures the evaluation does not become an open-ended technical exercise.
Solution stakeholder
Confirms that the generated solution, documentation and ownership model meet the practical needs of the customer environment.
Product and enablement support
Supports initial setup, product understanding and the correct use of relevant modelling and generation capabilities.
Project approach
Keep the first engagement structured
Confirm the candidate
Review the architecture, scope, data availability, delivery risk and reason for selecting the project.
Establish the baseline
Record the expected effort, existing process, project assumptions and agreed technical and commercial measures.
Deliver the scope
Use AnalyticsCreator for the agreed design and generation work while recording custom engineering, issues and decisions.
Review and decide
Compare the result with the success criteria and decide whether to stop, refine the approach or adopt it more broadly.
Final decision
Define the possible outcomes before the project starts
The fit is proven
The project demonstrates acceptable technical output, measurable delivery value and a credible route to wider use within the consultancy.
The fit is promising but incomplete
The project identifies value but also reveals gaps in scope, training, internal standards or technical understanding that should be addressed first.
Use it only for specific project types
AnalyticsCreator may create value for certain Microsoft architectures or delivery patterns without being suitable for every consultancy engagement.
The case is not proven
The technical fit, commercial return or adoption effort does not justify continued investment under the conditions tested.
The purpose of the first project is to create enough evidence for a responsible decision. It should not be designed so that wider adoption is the only acceptable outcome.
First-project checklist
Are you ready to begin?
- A representative project or customer use case has been identified.
- The architecture falls within the supported technical scope.
- The source metadata and requirements are sufficiently available.
- The project boundary and expected outputs are documented.
- Technical and commercial success criteria have been agreed.
- A baseline for effort and the existing delivery approach has been recorded.
- A hands-on engineer and technical decision-maker are involved.
- The commercial sponsor understands what the project must prove.
- The delivery risk is suitable for a first engagement.
- A review and adoption decision will take place after completion.
The question is whether you have a suitable project through which AnalyticsCreator can be evaluated in real delivery, with enough structure to measure both the technical result and the commercial effect.
