Context
- Product: Natural Capital
- Company / Environment: NTT Data
- Market / Industry: Sustainability, Environmental Consulting, Green Deal
- Product Stage: Discovery and Delivery (MVP)
Problem Statement
Green Deal clients needed a tool to financially measure the impact of their activities on nature and translate complex regulatory and sustainability requirements into actionable digital workflows.
Specifically, they required:
- A clear way to define, create, and manage geospatial (GIS) data
- The ability to generate shape files directly within the platform
- Guidance through complex environmental and regulatory processes
- Guidance through measurements on impacts and ecosystem services
Before this product, much of this work was:
- Manual (Excel)
- Fragmented across tools
- Highly dependent on external GIS experts and shape files
Goals & Success Criteria
User Outcomes
- Users can create and manage shape files directly in the platform
- Users are guided step by step through complex sustainability workflows
- Reduced dependency on external GIS tools and experts
Business Outcomes
- Increased value proposition for Green Deal clients
- Differentiation through integrated GIS capabilities
- Strong foundation for future sustainability-related products
Constraints
Technical
- No existing GIS capabilities in the platform
- Complex integration of geospatial logic into a SaaS product
Business
- MVP needed to demonstrate clear value quickly
- High expectations due to strategic importance of sustainability
Legal / Regulatory
- Limited internal knowledge of environmental regulations
- Green Deal compliance requirements
Time / Team
- Development team based in Spain
- Newly created testing and development team in India
- Distributed teams across time zones
Personal
- No prior experience in:
- GIS systems
- Nature-related business domains
- Environmental regulations
Discovery & Insights
Key Insights
- GIS capabilities were not “nice to have” but core to the product value
- Users struggled most with knowing what to do next, not just with tools
- Existing GIS solutions were powerful but inaccessible to non-experts
Invalidated Assumptions
- That users would prefer exporting data to external GIS tools
- That basic GIS visualization would be sufficient for an MVP
Evidence Used
- Stakeholder interviews
- Early user discussions
- Workshops with domain experts
- Internal reviews with sustainability teams
Options Considered
- Pros: Faster initial delivery
- Cons: Reduced control, fragmented user experience, high licence cost
Option B: Minimal GIS Visualization Only
- Pros: Lower complexity
- Cons: Did not solve core user problem
Option C: Native Shape File Creation and Guided GIS Workflow
- Pros: High value, strong differentiation
- Cons: High complexity and learning curve
Decision & Rationale
We chose Option C: building native GIS capabilities into the platform.
Despite the complexity, this option:
- Delivered the highest user and business value
- Positioned the product as a true end-to-end solution
- Reduced long-term dependency on external tools
The decision required embracing uncertainty and learning rapidly.
Delivery Summary
What Was Built
- MVP with integrated GIS functionality
- Ability to create and manage shape files directly in the platform
- Guided user flows to support non-GIS experts
- Collaboration between Spain-based development and India-based testing teams
What Was Intentionally Not Built
- Advanced GIS expert features
- Full regulatory automation
- Extensive customization options
Results
Quantitative
- MVP delivered with core GIS value demonstrated
- Positive internal and client feedback on differentiation
Qualitative
- Stakeholders recognized the strategic importance of the solution
- Users valued guidance as much as functionality
What Worked Well
- Close collaboration between distributed teams
- Continuous alignment between business and technical constraints
- Strong focus on MVP value rather than completeness
What Didn’t Work
- Underestimated learning curve of GIS concepts
- Initial communication gaps between distributed teams (spanish vs english)
- Discovery required more time than initially planned
Key Learnings
- Domain ignorance can be mitigated with strong discovery practices
- High-value features often sit at the intersection of complexity and differentiation
- Guidance and UX matter as much as technical capability
What I’d Do Differently
- Invest earlier in GIS and regulatory domain learning
- Introduce domain experts earlier into discovery
- Formalize knowledge sharing between teams sooner
Final Takeaway
When building in unfamiliar domains, clarity of problem and focus on user value matter more than prior expertise.
Strong discovery, intentional MVP scope, and continuous learning can turn complexity into competitive advantage.
Architecture & Workflow Diagram
```mermaid
flowchart TD
U[“Green Deal User (Consultant / SME)”]
P[“Natural Capital SaaS Platform”]
G["Guided Workflow Engine
- Regulatory steps
- User guidance"]
GIS["GIS Integration Layer
- Map visualization
- Geometry validation"]
SHP["Shape File Creation Engine
- Polygon creation
- Attribute mapping"]
OUT["Sustainability Outputs
- Reports
- Compliance artifacts"]
U --> P
P --> G
G --> GIS
GIS --> SHP
SHP --> OUT