- Staying with the status quo (with improvements)
- Customizing technology your organization already owns
- Changing processes or applying people differently
- Working with external consulting firms
- Purchasing new technology solutions
- Hybrid approaches combining multiple strategies
When to Use This Template
Use the Solution Options document when:- Senior leadership has requested a rigorous evaluation of different approaches
- You need to justify technology spending against alternative solutions
- You want to demonstrate thorough due diligence in the problem-solving process
- Multiple stakeholders have different opinions about the best approach
- You need to present options with clear, comparable criteria for decision-making
Template Structure
1. Executive Summary
A concise overview of:- The problem being addressed
- Key solution options considered
- High-level comparison of options
- The recommended approach with brief justification
2. Problem Statement Review
A recap of the problem definition including:- Core business challenge
- Current state and its limitations
- Quantified impact of the problem (e.g., cost, time, quality issues)
- Expected benefits of addressing the problem
3. Solution Options Analysis
For each viable option (typically 3-4 options), provide: Description and Approach- Clear definition of the solution
- How it addresses the core problem
- Key components or requirements
- Implementation costs
- Ongoing operational costs
- Expected ROI and payback period
- Time to value
- User experience impacts
- Strategic alignment
- Organizational fit
- Competitive advantages
- Timeline and major milestones
- Change management needs
- Training requirements
- Internal staff commitments
- External resources needed
- Skills and expertise required
- Systems or processes that must be in place
- Organizational changes required
- Other project dependencies
- Key risks for each option
- Probability and impact assessment
- Mitigation approaches
4. Comparison Matrix
A color-coded table comparing all options across key decision criteria:- 🟢 Green: Meets or exceeds requirements
- 🟡 Amber: Partially meets requirements or has notable concerns
- 🔴 Red: Does not meet requirements or has significant risks
- Cost (implementation and ongoing)
- Implementation timeline
- User adoption likelihood
- Feature coverage
- Integration complexity
- Scalability
- Support requirements
- Strategic alignment
5. Recommendation and Rationale
A clear recommendation supported by:- Summary of why the recommended option is superior
- Key decision factors that influenced the recommendation
- Acknowledgment of trade-offs made
- Next steps to move forward
Best Practices
- Be comprehensive but concise: Include enough detail to support decision-making without overwhelming readers.
- Use objective criteria: Ensure your comparison criteria are clear, measurable, and consistently applied across all options.
- Include the status quo: Always include the option of maintaining current systems (potentially with improvements) as a baseline for comparison.
- Consider hybrid approaches: Sometimes the best solution combines elements from multiple approaches.
- Quantify where possible: Use data and metrics to support your analysis rather than relying solely on subjective assessments.
- Acknowledge uncertainty: Where precise data isn’t available, provide ranges or estimates and note assumptions made.
- Align with organizational priorities: Ensure your evaluation criteria reflect your organization’s strategic priorities and constraints.
Example Solution Categories
When developing your options, consider these common solution categories:Internal Development Solutions
- Pure internal development
- Hybrid internal/external development
- Internal capability enhancement
Technology Purchase Solutions
- Off-the-shelf software
- Customized vendor solutions
- Platform-based approaches
- Multi-vendor integration
Partner-Based Solutions
- System integrator engagement
- Consulting firm collaboration
- Vendor professional services
- Multiple partner coordination
Process/People Solutions
- Workflow optimization
- Team restructuring
- Training and upskilling
- Managed services
Hybrid Approaches
- Combinations of above approaches
- Phased implementation strategies
- Pilot programs
- Proof of concept approaches
Example: AI Data Preparation and Integration Solution
Below is an example of a Solution Options document for an enterprise looking to improve their AI data preparation and integration capabilities:AI Data Solution Options Document
AI Data Solution Options Document
DRAFT: Solution Options for AI Data Integration and Preparation Platform
Executive Summary
This document evaluates four approaches to address Global Financial Corp’s data preparation and integration challenges that are currently limiting our AI implementation initiatives. Our analysis shows that:- Current manual data preparation methods are causing a 4-month backlog in AI projects
- Data scientists spend 70% of their time on data preparation instead of model development
- Three AI initiatives have failed to move beyond proof of concept due to data quality issues
Problem Statement Review
Global Financial Corp is struggling to scale AI initiatives due to inefficient data preparation and integration processes. Specifically:- Data resides in 16 different systems with inconsistent formats and quality
- The current manual ETL process takes 3-6 weeks per data source
- Data scientists lack self-service access to prepared data assets
- Regulatory compliance requires detailed data lineage which is currently tracked in spreadsheets
- Poor data quality has resulted in 3 failed AI pilots and $1.2M in wasted investment
- Reduce data preparation time by 70%
- Allow 5x more AI use cases to be deployed annually
- Improve model accuracy by 30% through better data quality
- Generate an estimated $4.7M in annual business value from accelerated AI adoption
Solution Options Analysis
Option 1: Build Custom Internal Data Platform
Description and Approach Build an in-house data lake and ETL framework using open-source technologies (Apache Spark, Airflow, and Delta Lake) on AWS infrastructure, with custom-developed data quality and governance tools.Quantitative Analysis- Implementation costs: $2.2-2.8M
- Annual operating costs: $850K
- ROI: 70% over 3 years
- Time to value: 12-18 months
- Complete customization to our specific needs
- No vendor lock-in
- Intellectual property ownership
- Builds internal expertise
- Requires significant engineering resources
- Phased deployment over 15 months
- High complexity to build governance and lineage features
- 6 data engineers full-time for 12 months
- 2 data architects for solution design
- 1 project manager
- 3 DevOps engineers
- Cloud infrastructure upgrades
- New data governance policies
- Specialized skill acquisition
- Resource competition from other strategic projects
- Mitigation: Dedicated team with backfill for existing roles
- Technical complexity exceeding initial estimates
- Mitigation: Agile development with regular deliverables
- Knowledge concentration in few key engineers
- Mitigation: Documentation requirements and knowledge sharing
Option 2: Commercial Data Integration Platform (Databricks)
Description and Approach Implement Databricks Lakehouse Platform with Delta Lake, featuring pre-built connectors, automated data quality monitoring, and integrated ML capabilities to create a unified data environment.Quantitative Analysis- Implementation costs: $1.2-1.5M
- Annual licensing: $720K
- ROI: 135% over 3 years
- Time to value: 6-8 months
- Pre-built data quality and governance capabilities
- Regular platform updates and improvements
- Familiar interface for existing Spark users
- Strong AI/ML integration features
- Phased implementation over 7 months
- Connector development for legacy systems
- Training for data engineering team
- 3 data engineers for 6 months
- 1 data architect
- 1 project manager
- Databricks professional services
- Cloud platform agreement amendments
- Security approval for SaaS solution
- Revised data governance framework
- Vendor lock-in concerns
- Mitigation: Ensure data export capabilities and open formats
- Integration with legacy systems
- Mitigation: Proof of concept with two most challenging systems
- Cost management for scaling usage
- Mitigation: Implement consumption monitoring and governance
Option 3: Managed Data Service Provider
Description and Approach Engage Accenture’s Data Integration Managed Service to handle all data preparation and integration needs, with their team building and operating a custom solution on our behalf.Quantitative Analysis- Implementation costs: $800K-1M
- Annual service costs: $1.8M
- ROI: 95% over 3 years
- Time to value: 4-5 months
- Minimal internal resource requirements
- Access to specialized expertise
- Fast implementation
- Flexible scaling
- Service transition over 4 months
- Potential culture change for data teams
- Clear SLAs and performance metrics required
- 1 vendor relationship manager
- 1 data architect for oversight
- Internal SMEs for knowledge transfer (part-time)
- Security and compliance oversight
- Vendor security clearance
- Data access policies
- Knowledge transfer from current teams
- Vendor performance not meeting expectations
- Mitigation: Detailed SLAs with penalties
- Loss of internal knowledge and control
- Mitigation: Shadow team for knowledge retention
- Data security concerns with external access
- Mitigation: Enhanced monitoring and access controls
Option 4: Enhanced Current Process with Specialized Staff
Description and Approach Maintain current systems but establish a dedicated data preparation team, implement better tools for existing processes, and develop standardized approaches without major architectural changes.Quantitative Analysis- Implementation costs: $350K
- Annual operating costs: $1.25M
- ROI: 60% over 3 years
- Time to value: 2-3 months
- Minimal disruption to current operations
- No new technology to learn or integrate
- Iterative improvement approach
- Maintains current security model
- Team hiring and onboarding: 2-3 months
- Process standardization: 1-2 months
- Documentation development: 1 month
- 7 new data specialists
- 1 data preparation team manager
- Process improvement consultant (3 months)
- Training for existing teams
- HR approval for new headcount
- Process standardization acceptance
- Department budget adjustments
- Difficulty finding specialized talent
- Mitigation: Contract-to-hire approach
- Limited scalability as AI initiatives grow
- Mitigation: Quarterly capacity planning
- Process improvements insufficient for needs
- Mitigation: Establish objective milestones with fallback plan
Comparison Matrix
| Criteria | Custom Solution | Databricks | Managed Service | Enhanced Process |
|---|---|---|---|---|
| Implementation Time | 🔴 | 🟡 | 🟢 | 🟢 |
| Total Cost | 🟡 | 🟡 | 🔴 | 🟢 |
| Data Quality Improvement | 🟢 | 🟢 | 🟢 | 🟡 |
| Scalability | 🟢 | 🟢 | 🟢 | 🔴 |
| Self-service Capability | 🟢 | 🟢 | 🟡 | 🔴 |
| Data Governance | 🟡 | 🟢 | 🟢 | 🟡 |
| Resource Requirements | 🔴 | 🟡 | 🟢 | 🟡 |
| Risk Level | 🔴 | 🟡 | 🟡 | 🟢 |
| AI/ML Integration | 🟡 | 🟢 | 🟡 | 🔴 |
| Security & Compliance | 🟢 | 🟡 | 🟡 | 🟢 |
Recommendation and Rationale
We recommend proceeding with Option 2: Implementing the Databricks Lakehouse Platform for the following reasons:- Balanced approach: Provides the best combination of implementation speed, cost, and capabilities
- Superior ROI: Highest projected 3-year ROI at 135%
- AI/ML integration: Native features support our strategic AI initiatives
- Time to value: Moderate implementation timeline with rapid initial results
- Scalability: Can grow with our expanding AI program
- Initiate vendor discussions and detailed technical assessment
- Develop implementation plan with milestones
- Create resource allocation request for implementation team
- Schedule executive briefing on recommended approach
Related Templates
- Problem Statement - Define the challenge you’re trying to solve
- Requirements Document - Document detailed requirements once a solution approach is selected
- Vendor Selection Matrix - Compare specific vendors once you’ve decided to purchase technology
Requirements Document Template
Ready to document your requirements list? Use our Requirements Document template to clarify what you need this solution to do.