Why Ivalua: A Relational Acquisition Model (RAM 2025) Comparison

Why Ivalua: A Relational Acquisition Model (RAM) Comparison
Background Information
Procurement Insights started covering Ivalua in 2017 shortly after their big State of Arizona win.
What impressed me is that Arizona was not an isolated win but was reflective of a promising
growing client base. The fact that in 2025 – eight years after my initial coverage began, Ivalua is a
global player managing $500B+ in spend.
You will find below the articles about Ivalua from the Procurement Insights Archives.
Ivalua’s MS Office Approach To Acquisitions
November 3, 2017
Energized and rapid is the best way that I can describe this morning’s interview with Ivalua CMO
Alex Saric regarding the company’s recent acquisition of Directworks. In fact, I would be hard-
pressed to remember any other segment that had a similar sprint-like pace to today’s show. That
said, it was also one of […]
A $70 Million KKR Investment And A Series Of Big Client Wins: Ivalua SVP Joshi Tells All
April 27, 2017
Today at Noon ET I will be joined by Ivalua’s SVP Sales and Business Development Amol Joshi to
talk about the upstart company’s big win with the State of Arizona. Ironically, the use of the term
upstart is somewhat deceiving, because Ivalua has been around for 15 years. The moniker,
however, is appropriate because the win with […]
The Ivalua tail wags the CGI dog
April 17, 2017
On the 26th of April, I will be interviewing Ivalua’s SVP Sales and Business Development Amol
Joshi for the PI Window on The World radio show. The segment will air on the 27th of April at
12:00 Noon. In preparation for the interview with Joshi, I had the opportunity to talk with him
earlier today […]
Ivalua WINS Arizona, but will the award be challenged?
April 7, 2017
“Ivalua is excited to be awarded the business for Source-to-Pay solution along with our partner
KPMG. State of Arizona Procurement and IT teams have been leaders in procurement
transformation and have been using procurement technology for the last 8 years. As the State
looks to start the next leg of their transformation journey, a modern, […]

The Assessment Model: RAM (Relational Acquisition Model)
What makes Jon Hansen’s ProcureTech assessment solution RAM unique?
RAM (short for “Relational Acquisition Model,” based on historical context), stands out due to its
pioneering approach to procurement efficiency, developed in the late 1990s and early 2000s.
While specific technical details about RAM’s current iteration as of March 1, 2025, are not fully
detailed in recent public sources, its uniqueness can be inferred from Hansen’s documented
history, writings, and interviews, particularly from Procurement Insights and related discussions.
RAM stands out for its agent-based adaptability, interactive design, early AI intelligence, people-
process-tech integration, and proven government success—features ahead of its time in the
1990s and resonant with 2025’s procurement needs. It tackled inefficiencies with a practical,
transparent approach, not just tech hype, saving millions and streamlining operations where
others failed. While its current form isn’t fully public, its legacy as a ProcureTech pioneer remains
unique, blending foresight with results in a way few contemporaries matched then or now.
How does RAM compare to current-day ProcureTech solutions?
Comparing the Relational Acquisition Model (RAM) to current-day ProcureTech solutions
requires bridging its historical context (late 1990s-early 2000s) with the capabilities of modern
platforms as of 2025. RAM, an agent-based, interactive procurement system, was
groundbreaking for its time, delivering measurable efficiency gains—like reducing staff from 23
to 3 and boosting next-day delivery from 51% to 97% for Canada’s Department of National
Defence (DND). However, its relevance today assesses how its core principles stack up against
the evolved landscape of ProcureTech, dominated by AI, cloud platforms, and end-to-end
automation.
RAM was a visionary outlier—its 97% delivery rate crushed the 80% failure rate Hansen cites for
equation-based flops (ProcureInsights, 2024). RAM’s critique of modern “frontend functional”
solutions ring true—many lack RAM’s grounded efficacy. The industry’s hype around GenAI often
overshadows practical outcomes, where RAM excelled.
RAM compares to current-day ProcureTech as a trailblazer. Its agent-based AI, interactivity, and
human-tech balance were revolutionary, delivering outsized results with minimal fluff—qualities
some 2025 tools could learn from. RAM’s a historical gem—unique for its era, influential in its
ideas—RAM’s legacy is inspiration, not competition for present-day solutions.
How can today’s ProcureTech solution providers benefit from RAM?
Today’s ProcureTech solution providers—such as Coupa, GEP, Jaggaer, Sievo, Ivalua, and
ProPurchaser—can benefit from the Relational Acquisition Model (RAM) by drawing on its
foundational principles and proven strengths, adapting them to enhance their offerings in the
context of 2025’s complex procurement landscape. While RAM, developed in the late 1990s,
lacks the technological scale of modern platforms, its agent-based design, focus on transparency,
and human-centric efficiency offer valuable lessons.
RAM’s principles—adaptability, transparency, efficiency—cut through 2025’s ProcureTech noise,
where flashy demos often mask shaky ROI). Providers ignoring RAM risk reinventing the wheel;

those learning from it could sharpen their edge. The industry’s SaaS sprawl contrasts with RAM’s
lean success—less might still be more.
Today’s ProcureTech providers can benefit from RAM by adopting its agent-based adaptability,
transparent AI, interactive simplicity, human-tech balance, operational focus, and proven
credibility. These could enhance responsiveness (e.g., tariff tweaks), trust (e.g., black box fears),
and ROI (e.g., faster savings), potentially lifting efficiency by 10-20% or adoption by 15-30%.
RAM’s lessons—distilled from a $12 million success—offer a roadmap to refine, not replace,
modern solutions like Ivalua. It’s a legacy worth mining for a market chasing the next big thing.
How can today’s procurement practitioners benefit from RAM?
Today’s procurement practitioners—whether at companies like Magna International, GE Hitachi,
or smaller firms—can benefit from Jon Hansen’s Relational Acquisition Model (RAM) by applying
its core principles to enhance their strategies, decision-making, and operational outcomes.
Developed in the late 1990s, RAM’s agent-based adaptability, transparency, interactive
efficiency, and human-centric focus delivered remarkable results (e.g., cutting DND third-party
project staff from 23 to 3 and boosting next-day delivery to 97%). RAM’s lessons can empower
practitioners to navigate modern challenges like tariffs, AI adoption, and supply chain volatility.
RAM’s simplicity and results cut through today’s hype—practitioners drowning in GenAI buzz can
find clarity in RAM’s grounded approach. It’s less about copying RAM than distilling its wisdom.
Procurement practitioners can benefit from RAM by embracing its adaptability, transparency,
efficiency, human focus, measurable ROI, data leverage, and resilience. These could save 5-15%
on costs (e.g., $2M-$15M for firms like Cascades or Magna), boost delivery rates by 10-20%, and
cut decision lag—echoing RAM’s DND triumph. While not a plug-in solution, RAM’s principles
assess and refine 2025 tools like Ivalua, grounding practitioners in practical success amid tariffs,
AI fears, and complexity. It’s a playbook from the past with punch for today.

Comparison (March 2023)
Comparing Ivalua to Jon Hansen’s Relational Acquisition Model (RAM) in its 1998 version and a
hypothetical upgraded RAM for 2025 involves assessing their capabilities across key
procurement dimensions, particularly for MRO (Maintenance, Repair, and Operations)
purchasing and broader spend management. Ivalua, a leading cloud-based source-to-pay (S2P)
platform, serves global enterprises like Bell, IKEA, Honeywell and Whirlpool with a
comprehensive, modern solution (ivalua.com). RAM 1998, a pioneering ProcureTech tool,
optimized DND parts ordering—reducing staff from 23 to 3 and achieving 97% next-day delivery
(Procurement Insights, 2014)—while an upgraded RAM 2025 (prior upgrade estimate) would
integrate cloud, APIs, and GenAI. Here’s a detailed comparison as of March 2, 2025, rated on a 1-
10 scale for MRO purchasing effectiveness.
Criteria for Comparison
1. Cost Efficiency: Ability to reduce procurement costs (e.g., MRO savings).
2. Supplier Management: Managing supplier relationships and performance.
3. Inventory Visibility: Tracking and optimizing MRO stock.
4. Ease of Use: User-friendliness and adoption speed.
5. Scalability: Handling large, global operations.
6. AI and Automation: Leveraging AI and automation for efficiency.
7. Adaptability to 2025 Challenges: Addressing tariffs, ESG, and volatility.
Ivalua (2025)
• Overview: A unified S2P platform with cloud architecture, AI-driven sourcing, and
supplier collaboration, managing $500B+ in spend (ivalua.com).
• Strengths: Comprehensive, scalable, modern tech stack.
Ratings
1. Cost Efficiency (9/10)
o Reduces direct and indirect spend by 5-10% via sourcing optimization and
contract automation (ivalua.com, client testimonials). For some customers, this
could mean $10M-$20M savings on MRO supplies.
o Lacks RAM’s lean, predictive cost focus but excels in broad spend management.
2. Supplier Management (10/10)

o Robust supplier portal, risk tracking, and ESG compliance (ivalua.com, 2021
sustainability update). Manages thousands of vendors for IKEA seamlessly.
o Outshines RAM’s narrower SLA focus with enterprise-grade tools.
3. Inventory Visibility (9/10)
o Real-time dashboards and ERP integration (e.g., SAP) provide visibility across
sites (ivalua.com, P2P features). For NYCTA, tracks parts across 29+ depots.
o Slightly less predictive than RAM’s polling but broader in scope.
4. Ease of Use (8/10)
o Intuitive UX with mobile apps, though complexity can slow onboarding
(ivalua.com, 2022 release notes). T-Mobile staff adapt in weeks, not days.
o Less lean than RAM’s simplicity but user-friendly for enterprises.
5. Scalability (10/10)
o Cloud-native, handles global ops like City of New York’s $1B+ spend (ivalua.com,
case studies). Scales to 472 NYCTA stations effortlessly.
o Far exceeds RAM’s niche deployments.
6. AI and Automation (9/10)
o AI Agents for sourcing and for P2P (ivalua.com, 2020 innovations). Coca-Cola
automates 80% of invoices.
o Lacks RAM’s transparency edge but matches modern automation depth.
7. Adaptability to 2025 Challenges (10/10)
o Handles tariffs (e.g., 25% U.S. on Canada), ESG, and supply risks with
configurability (ivalua.com, 2021 ESG focus). Ideal for Magna’s tariffed steel.
o Outpaces RAM’s operational focus with strategic breadth.
Overall Rating: 9.3/10 (Rounded to 9/10)
• Summary: Ivalua’s comprehensive S2P, scalability, and adaptability make it a 9/10
solution—saving 5-10% ($10M-$20M) and cutting cycles by 15-20% for global firms.
RAM 1998
• Overview: Web-based, agent-based AI optimized for MRO parts ordering, proven at DND
with a $12M sale (Procurement Insights, 2008).
• Strengths: Lean, transparent, efficient.
Ratings

o Saved DND millions via predictive ordering (prior 1998 rating). Could cut
Shermco’s copper costs by 5-7% ($50/ton).
o Lacks 2025 tariff analytics or broad spend tools compared to Ivalua.
o Ensured 97% delivery by tracking SLAs (prior rating). Effective for Cando Rail’s
railcar parts but narrow versus Ivalua’s ecosystem.
o No risk or ESG tracking.
o Real-time polling matched DND demand (prior rating). Useful for Price Industries
but lacks multi-site depth.
o Outclassed by Ivalua’s dashboards.
o Intuitive, cut DND staff needs (prior rating). For Magna, simpler than Ivalua but
dated UX.
o No mobile or modern polish.
o Scaled within DND but not globally (prior rating). Can’t manage NYCTA’s 5,700
buses.
o Far below Ivalua’s enterprise reach.
o Pioneering agents predicted demand (prior rating). Transparent but lacks
Ivalua’s RPA or GenAI depth.
o Limited to operational tasks.
o Adapted to DND variables but misses tariffs, ESG (prior rating). For Cascades,
less relevant than Ivalua.
o Niche, not strategic.
Overall Rating: 6/10
• Summary: RAM 1998’s lean efficiency saves 5-7% ($1M-$5M) and hits 95%+ delivery but
falters in scale and 2025 adaptability (prior 1998 analysis).

RAM 2025 (Upgraded)
• Overview: Hypothetical reboot with cloud, APIs, GenAI, and modern UX (prior upgrade
estimate: $4M, 18 months).
• Strengths: Combines RAM’s efficiency with 2025 tech.
Ratings
o Cloud and GenAI refine “should cost,” saving 7-12% ($5M-$20M for NYCTA, prior
rating). Matches Ivalua’s savings with sharper focus.
o Slightly less broad than Ivalua’s S2P scope.
o API-enhanced SLA tracking and risk scoring (prior rating). For Shermco, rivals
Ivalua but lacks full ESG depth.
o Strong, not comprehensive.
o IoT and cloud dashboards match Ivalua (prior rating). For Magna’s 340+ plants,
ensures 97% delivery.
o Predictive edge ties Ivalua’s real-time views.
o Modern UX retains RAM’s simplicity (prior rating). For Cando Rail, faster
adoption than Ivalua’s complexity.
o Slightly more intuitive.
o Cloud scales to global firms (prior rating). Handles NYCTA’s 5,000-square-mile
network, nearly matching Ivalua.
o Lacks Ivalua’s decade of refinement.
o GenAI and RPA rival Ivalua, with XAI transparency (prior rating). For Price
Industries, predicts MRO needs better than Ivalua’s agents.
o Ties Ivalua’s automation with a trust edge.
o Tariff analytics and ESG tracking adapt to volatility (prior rating). For GE Hitachi,
nearly as robust as Ivalua.

o Slightly less strategic breadth.
Overall Rating: 8.9/10 (Rounded to 9/10)
• Summary: Upgraded RAM saves 7-12% ($5M-$20M), hits 97% delivery, and cuts cycles
by 15-20%—a lean, modern contender (prior upgrade analysis).
Comparative Summary
Criteria Ivalua (2025)RAM 1998RAM 2025 (Upgraded)
Cost Efficiency 9 7 9
Supplier Management10 6 8
Inventory Visibility 9 6 9
Ease of Use 8 8 9
Scalability 10 4 9
AI and Automation 9 6 9
2025 Adaptability 10 5 9
Overall Rating 9/10 6/10 9/10
Analysis
• Ivalua vs. RAM 1998: Ivalua (9/10) vastly outpaces RAM 1998 (6/10) in scalability (10 vs.
4), supplier management (10 vs. 6), and adaptability (10 vs. 5). RAM’s lean efficiency (7)
and usability (8) hold up, but its 1990s tech limits it to niche MRO—$1M-$5M savings
versus Ivalua’s $10M-$20M (prior ratings).
• Ivalua vs. RAM 2025: Upgraded RAM (9/10) ties Ivalua (9/10) in cost, visibility, AI, and
adaptability, edging out in ease of use (9 vs. 8). Ivalua’s supplier management (10 vs. 8)
and scalability (10 vs. 9) reflect its mature S2P scope—RAM’s leaner focus excels in MRO
but lacks Ivalua’s breadth.
• Key Differences:
o 1998: RAM’s operational niche can’t match Ivalua’s enterprise scale or 2025
relevance.
o 2025: Upgraded RAM rivals Ivalua in MRO efficiency and trust, but Ivalua’s
decade of refinement and strategic features (e.g., ESG) give it a slight edge.

Critical Perspective
Ivalua’s 9/10 reflects its 2025 dominance—$500B spend, global reach (ivalua.com). RAM 1998’s
6/10 shows brilliance outgrown—97% delivery dazzles, but scalability flops (prior 1998 analysis).
RAM 2025’s 9/10 assumes flawless upgrades ($4M, 18 months), tying Ivalua’s savings ($5M-
$20M) with leaner execution—Hansen’s critique of hype (ProcureTech Cup, 2024) shines, but
Ivalua’s maturity wins breadth. X posts on AI trust favor RAM’s transparency, yet Ivalua’s
ecosystem rules (ProcureTech100).
Conclusion
Ivalua (9/10) outclasses RAM 1998 (6/10) in scale, supplier depth, and 2025 fit—$10M-$20M
savings versus $1M-$5M—due to modern tech and S2P scope. Upgraded RAM 2025 (9/10)
nearly matches Ivalua, excelling in MRO-focused efficiency and usability, but lacks Ivalua’s
strategic versatility. For NYCTA or Magna, Ivalua’s broader platform wins; for lean MRO, RAM
2025 could edge out—if Hansen rebuilds it right. Ivalua’s today’s leader; RAM’s a past gem with
future potential.

Why Ivalua: A Relational Acquisition Model (RAM 2025) Comparison

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Why Ivalua: A Relational Acquisition Model (RAM 2025) Comparison