- Single-Sourcing means obtaining your data from one primary vendor.
- Multi-Sourcing means leveraging multiple vendors, often to broaden coverage, improve data accuracy, or reduce dependency risk.
The best option depends on your business goals, data needs, internal capabilities, and appetite for complexity.
Key Factors to Consider When Choosing a Sourcing Model
1. Cost Model: Transactional vs. Licensed
Your sourcing approach will influence—and be influenced by—your cost structure.
- Transactional pricing offers flexibility and pay-as-you-go control, which can be beneficial when testing or scaling gradually.
- Licensed models provide predictable recurring pricing but typically require long-term commitments.
Multi-sourcing may increase costs due to multiple vendor contracts, while single-sourcing can offer volume-based savings.
2. Data Access: Resident vs. API-Based
How you receive and manage data materially affects your operations.
- Resident data (e.g., delivered files or bulk datasets) provides full control and can support complex internal processing.
- API-delivered data enables real-time access and simplifies integration but may introduce latency or dependency on vendor uptime.
Multi-sourcing increases integration complexity, so ensuring consistent access methods across providers is essential.
3. Overlap and Redundancy Between Data Sets
When using multiple sources, the degree of overlap becomes critical.
- Strong overlap allows teams to compare datasets and choose the strongest value.
- Minimal overlap may mean you’re paying for unique data from multiple providers—but also managing very different inputs.
Understanding how each vendor constructs and updates its data helps you avoid redundancy and maximize lift.
4. Vendor Quality: Reliability, Timeliness, and Ease of Engagement
Every vendor relationship is different. When evaluating providers, consider:
- Reliability – How often is data delivered correctly and on time?
- Timeliness – How quickly does the provider incorporate updates or corrections?
- Ease of doing business – Are they responsive? Flexible? Transparent?
With multi-sourcing, managing vendor relationships becomes more complex, but it can also reduce the risk of dependency on any single provider.
5. Testing and Measuring Lift
Effective data strategy requires rigorous validation. Whether you use one source or many, testing should determine which data produces the best outcomes.
- Lift-over-control testing allows you to compare one source against another—or against your current baseline—to quantify incremental value.
- Multi-sourcing inherently provides more opportunities for controlled comparisons, whereas single-sourcing may limit benchmarking.
The real goal is not simply acquiring data, but ensuring it outperforms alternatives.
Conclusion
Choosing between single-sourcing and multi-sourcing is not just a technical decision—it’s a strategic one. It affects your budget, data reliability, operational workload, and ultimately the quality of your analytics and decision-making.
A thoughtful evaluation of cost model, access method, vendor quality, and testing strategy will help you determine the right approach. Whether you need the simplicity of a single provider or the robustness of multiple sources, aligning your data sourcing model with your business objectives is key to a successful and scalable data strategy.