Steve Jennis, another edge, is that my Level 5 algorithms provide an unbiased breakdown of which ProcureTech solution providers are best matched to deliver a collective result.
Consider this: a ProcureTech solution ecosystem assessment with no restrictions on provider participation, meaning we remove the barriers resulting from who has the biggest marketing budget.
It isn’t about marketing reach or the size of a ProcureTech solution provider’s sales force. It is now about the depth of experience, including historic archives, and expertise regarding how procurement and supply work within a real-world Agent-based Metaprise ecosystem.
I could have done the following RAM 2025 partial Level 1 analysis with any combination of suppliers. In this instance, I chose ORO Labs and the providers from the 2024 ProcureTech 100 list.
MODEL 1 of 6 – Expand to 12
Interpretation:
- Shared region in the center highlights common orchestration value when combined with ORO Labs.
- Each also offers unique, non-overlapping strengths, making them complementary rather than redundant.
- This trio forms a strong modular backbone for dynamic procurement orchestration and intelligence enablement.
MODEL 2 of 6 – Expand to 12
Top Complementary Providers
From the Top 100 ProcureTech providers, the following are selected for their synergy with ORO Labs, based on their strengths in addressing enterprise needs. Providers of niche tools (e.g., MainStem) are excluded due to low relevance (Hansen Fit Score: 51.0).
- ConvergentIS:
- Why It Complements ORO Labs:
- SAP Integration: Native SAP integration (Hire Rio platform) simplifies connectivity with SAP systems, reducing integration complexity by up to 80% via a clean core strategy (Prior Research, February 28, 2025).
- Functional Fit: Automates procure-to-pay (P2P) workflows, including invoice matching and vendor metrics, suitable for regulated industries.
- Scalability/Adoption: Simplified Requisitioning app offers mobile, no-training UX (email, Teams, Slack), targeting 80% adoption for large supplier bases.
- AI/Automation: Enhances ORO Labs’ orchestration with P2P automation and human-in-the-loop data validation for master data hygiene.
- Value Add: Provides cost-effective P2P automation, complementing ORO Labs’ broader orchestration and improving user adoption.
- Tealbook:
- Why It Complements ORO Labs:
- SAP Integration: Integrates supplier data with SAP systems, enhancing ORO Labs’ data orchestration (Prior Research, April 29, 2025).
- Functional Fit: AI-driven supplier discovery and ESG data management support compliance and sustainability goals in regulated sectors.
- Scalability/Adoption: High-quality supplier data streamlines onboarding for thousands of suppliers, reducing errors.
- AI/Automation: Complements ORO Labs’ AI with supplier intelligence, improving data hygiene via automated validation.
- Value Add: Enhances ORO Labs’ supplier management with clean, ESG-focused data, reducing fraud and compliance risks.
- Ivalua:
- Why It Complements ORO Labs:
- SAP Integration: Configurable source-to-pay (S2P) platform integrates with SAP S/4HANA, complementing ORO Labs’ orchestration layer.
- Functional Fit: Strong in supplier management, ESG, and compliance, used by Pfizer for regulated industries.
- Scalability/Adoption: Unified codebase supports large-scale operations, with AI-driven UX improving adoption (Hansen Fit Score: 86.5).
- AI/Automation: Agentic AI (e.g., negotiation bots) enhances ORO Labs’ intent recognition and supplier recommendations.
- Value Add: Provides comprehensive S2P capabilities, strengthening ORO Labs’ governance and analytics.
Optimal Combination: ORO Labs + ConvergentIS + Tealbook
Why This Combination Works Best:
- Integration Complexity: ConvergentIS’s native SAP integration simplifies connectivity with ERP systems, while ORO Labs orchestrates workflows across platforms. Tealbook ensures clean supplier data, reducing integration errors.
- Master Data Hygiene: Tealbook’s AI-driven validation complements ORO Labs’ intent recognition and ConvergentIS’s human-in-the-loop checks, ensuring high-quality data for analytics.
- Low Adoption Risk: ORO Labs’ no-code, user-friendly platform (used by Bayer, GSK) and ConvergentIS’s mobile UX drive 80% adoption for large user and supplier bases. Tealbook streamlines supplier onboarding, reducing resistance.
- Governance Gaps: ORO Labs’ compliance automation, ConvergentIS’s 3-way matching, and Tealbook’s ESG data ensure regulatory adherence in industries like energy or pharmaceuticals.
- Synergy: ORO Labs orchestrates end-to-end workflows, ConvergentIS enhances P2P efficiency, and Tealbook provides supplier intelligence, creating a cohesive stack.
Business Outcomes (for a generic enterprise with $50M spend, 9,000 suppliers, 35,000 users):
- FTE Reduction: ConvergentIS automates P2P tasks, saving 2–3 FTEs ($200K–$300K/year at $100K/FTE). ORO Labs’ workflow automation saves 50–100 hours/CPO ($75K–$150K/year for 10 CPOs) (Prior Research).
- Cost of Goods Savings: ConvergentIS delivers 1–3% spend savings ($500K–$1.5M/year). ORO Labs reduces maverick spend by 2–4% ($1M–$2M/year). Tealbook optimizes supplier selection, adding $200K–$500K/year.
- Regulatory/ERP Compliance: ORO Labs’ AI enforces compliance, ConvergentIS automates audits, and Tealbook ensures ESG compliance, saving $100K–$250K/year in penalties (Web ID: 2, 8, 10, 17).
MODEL 3 of 6 – Expand to 12
Based on ORO Labs’ strategic positioning as an AI-powered procurement orchestration platform, the following combinations of suppliers would deliver optimal synergy, addressing integration complexity, scalability, and innovation:
Top Recommended Combinations
Why These Combinations Excel
- SAP Ariba Integration
- Proven integration via SAP Store (2023).
- ORO resolves Ariba’s UX friction, reducing training time by 70% while maintaining governance.
- Outcome: 40% faster requisition-to-PO cycles.
- Deloitte Partnership
- Deloitte’s procurement advisory arm (allied with DPW/ProcureTech) accelerates ORO deployments at scale.
- Joint solutions for ESG compliance and M&A due diligence.
- Outcome: 50% faster ROI realization in regulated sectors (e.g., GSK, Roche).
- GEP/Ivalua Synergy
- Complementary strengths: ORO’s agent-based workflows + GEP/Ivalua’s spend analytics create closed-loop procurement intelligence.
- Outcome: 30% reduction in maverick spend via real-time policy enforcement.
Combinations to Avoid
- ORO + Legacy Monoliths (e.g., Coupa): Overlaps in orchestration capabilities; Coupa’s credit model conflicts with ORO’s value-based pricing.
- ORO + Niche Point Solutions: Fragments data flow, undermining ORO’s core orchestration value.
MODEL 4 OF 6 – Expand to 12
The optimal combination would be:
- ORO Labs + SAP Ariba + ConvergentIS – Comprehensive AI orchestration with enterprise platform and integration expertise
- ORO Labs + Coupa + Everstream Analytics – AI orchestration with spend management and risk intelligence
This leverages ORO Labs’ GenAI capabilities while ensuring robust enterprise integration and comprehensive data feeds.
RAM 2025 (PARTIAL) LEVEL 1 ANALYSIS
Using the RAM 2025 Partial Level 1 analysis, for example, expanding from 4 of 6 Core Models to 12 models, the above output demonstrates the complexity of selecting the right combination of ProcureTech solution providers for your organization. However, even at this early stage, when you have only a partial view, core patterns are taking shape.
In a real-world situation, Level 1 would be expanded to include 12 core models before going to Levels 2 through 5, at which point the optimal recommendation would be made within an accuracy range of 80% to 87.5%. In a relatively short time, the accuracy rate will approach the 97.3% level of the RAM 1998 model.
However, even at this very early stage, it creates avenues of consideration that may have been overlooked but are worth exploring.
Of course, one of the key elements of a successful analysis process is the depth of Procurement Insights’ proprietary archives.
30
**ONE IMPORTANT FINAL POINT**
The above results will vary depending on the practitioner client being considered. In short, even companies within the same industry sector will likely have different ProcureTech solution provider combinations.
Procurement Insights
What Is Your Best ProcureTech Combo (A Preliminary Partial Level 1 Analysis)
Posted on June 29, 2025
0
Steve Jennis, another edge, is that my Level 5 algorithms provide an unbiased breakdown of which ProcureTech solution providers are best matched to deliver a collective result.
Consider this: a ProcureTech solution ecosystem assessment with no restrictions on provider participation, meaning we remove the barriers resulting from who has the biggest marketing budget.
It isn’t about marketing reach or the size of a ProcureTech solution provider’s sales force. It is now about the depth of experience, including historic archives, and expertise regarding how procurement and supply work within a real-world Agent-based Metaprise ecosystem.
I could have done the following RAM 2025 partial Level 1 analysis with any combination of suppliers. In this instance, I chose ORO Labs and the providers from the 2024 ProcureTech 100 list.
MODEL 1 of 6 – Expand to 12
Interpretation:
MODEL 2 of 6 – Expand to 12
Top Complementary Providers
From the Top 100 ProcureTech providers, the following are selected for their synergy with ORO Labs, based on their strengths in addressing enterprise needs. Providers of niche tools (e.g., MainStem) are excluded due to low relevance (Hansen Fit Score: 51.0).
Optimal Combination: ORO Labs + ConvergentIS + Tealbook
Why This Combination Works Best:
Business Outcomes (for a generic enterprise with $50M spend, 9,000 suppliers, 35,000 users):
MODEL 3 of 6 – Expand to 12
Based on ORO Labs’ strategic positioning as an AI-powered procurement orchestration platform, the following combinations of suppliers would deliver optimal synergy, addressing integration complexity, scalability, and innovation:
Top Recommended Combinations
Why These Combinations Excel
Combinations to Avoid
MODEL 4 OF 6 – Expand to 12
The optimal combination would be:
This leverages ORO Labs’ GenAI capabilities while ensuring robust enterprise integration and comprehensive data feeds.
RAM 2025 (PARTIAL) LEVEL 1 ANALYSIS
Using the RAM 2025 Partial Level 1 analysis, for example, expanding from 4 of 6 Core Models to 12 models, the above output demonstrates the complexity of selecting the right combination of ProcureTech solution providers for your organization. However, even at this early stage, when you have only a partial view, core patterns are taking shape.
In a real-world situation, Level 1 would be expanded to include 12 core models before going to Levels 2 through 5, at which point the optimal recommendation would be made within an accuracy range of 80% to 87.5%. In a relatively short time, the accuracy rate will approach the 97.3% level of the RAM 1998 model.
However, even at this very early stage, it creates avenues of consideration that may have been overlooked but are worth exploring.
Of course, one of the key elements of a successful analysis process is the depth of Procurement Insights’ proprietary archives.
30
**ONE IMPORTANT FINAL POINT**
The above results will vary depending on the practitioner client being considered. In short, even companies within the same industry sector will likely have different ProcureTech solution provider combinations.
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