Art of Procurement

Procurement talks about "the data" as if it's neutral.
It rarely is.
For years, we have talked about "the data" as if it were a single, uniform thing… a stack of invoices, a dashboard of KPIs, a quarterly business review deck handed over by a supplier.
Here's the problem: invoices are curated. Reports are crafted. And, most of the time, suppliers decide what you see… unless you know what to ask for.
In this episode of Buy: The Way…To Purposeful Procurement, Brian Gamble, COO at FineTune and a 30-year veteran of indirect services, joins podcast co-hosts Philip Ideson and Rich Ham to unpack BuyLaw #6: "develop expense-specific systems."
The directive is fairly simple on its surface, but it's also disruptive: no single data set or measurement system works across diverse categories. Uniforms are not utilities. Security is not pest control. Waste is not janitorial supplies. And trying to manage them all with the same playbook guarantees procurement will create blind spots.
Brian has seen those blind spots from both sides up close, first as a regional VP for a national uniform provider, now as an advisor helping clients defend their P&L against quiet leakage. He doesn't mince words: if your definition of "the data" is whatever appears on an invoice PDF, you are operating inside a commercial narrative written by your supplier.
The episode walks through examples that sound almost unbelievable until you realize how common they are. Security "dark hours" where posts go unfilled but still get billed. Pest control programs charging for weekly service where there's been no activity in months. Uniform inventory definitions that vary between suppliers, creating a scenario where 17 cents can be far more expensive than 21 cents, depending on what number you're multiplying.
None of that shows up cleanly on a summary invoice. Which brings us to AI…
As procurement leans more heavily on AI for benchmarking and research, the technology can generate polished, authoritative answers, even when the underlying data is thin or incomplete. But, the quality of the output rises or falls with the quality of the inputs. For example, Brian shares a live demonstration his team conducted internally: a generalist asking AI for "a good price" in a complex service category gets laughable, contradictory answers. Garbage in, garbage out, so to speak. A more informed user does slightly better. When a true category expert feeds AI high-quality, relevant, structured data does the output become meaningfully useful, and even then, it still requires human judgment to separate signal from noise. 
This episode also challenges another sacred cow in procurement: not all dollars are created equal. A $100 million utilities category might require minimal management. A $1 million uniform program might require 50 times the oversight. Yet procurement teams are often sized and measured purely by spend under management, not complexity, risk, or management intensity.
If procurement is going to be measured by what actually hits the P&L (as the earlier BuyLaws argue) then they must design contracts, data rights, and reporting structures that allow real validation. 
The future of procurement won't be won by those who have the most data. It will be won by those who know which data matters and, perhaps most importantly, why.
Links:
Rich Ham on LinkedIn
Learn more at FineTuneUs.com

"You don't want to over-engineer orchestration. The goal is progress, not complexity." - Philip Ideson, Founder and Managing Director, Art of Procurement
There has never been more tech available to procurement, but navigating the orchestration market is anything but simple. 
In this episode, Philip Ideson and Kelly Barner unpack the findings from AOP's upcoming "State of Orchestration" report, which is based on conversations with CPOs, digital leaders, and orchestration providers. They share the big trends, the evolving definition of orchestration, and candid advice on what to ask and look for before you buy.
Investment is surging, capabilities are converging, and the stakes for business impact keep rising. This episode is your fast-track to understanding where orchestration fits into your tech stack and operating model, and how to choose a solution that aligns with your priorities and risk appetite. 
In this episode, Kelly and Philip cover:
The five core categories for evaluating orchestration platforms
The questions to ask about native workflow depth versus integrations
How to avoid common pitfalls in change management and solution over-customization
Real customer adoption trends and what they signal 
 
Links:
Philip Ideson on LinkedIn
Kelly Barner on LinkedIn
Subscribe to the AOP Newsletter
Subscribe to Art of Procurement on YouTube

In this episode of the ProcureTech Insider Provider of the Week, host Jyothi Hartley speaks with Imran Shaikh, Head of Pre-Sales and Business Development at Samsung SDS America, about how AI-powered design-to-source-to-pay orchestration is transforming procurement's role in product development.
Samsung SDS Caidentia is an AI-powered platform designed to shift procurement upstream, connecting product design, sourcing, and supply decisions before spend occurs. Acting as an orchestration layer between PLM and ERP systems, the platform enables procurement teams to influence cost, risk, and supply resilience earlier in the product life cycle.
Imran shares how Samsung SDS Caidentia has evolved from a sourcing solution into a cross-functional platform centered around Bill of Materials (BOM) intelligence. In this conversation, they explore how procurement can move beyond transactional execution to become a strategic contributor to product decisions, leveraging AI to simulate cost impacts, assess supplier risk, and improve cross-functional alignment.
Links:
Samsung SDS Caidentia Provider Profile
Download the 2025-26 ProcureTech100 Yearbook
Subscribe to This Week in Procurement
Subscribe to Art of Procurement on YouTube

"The strategic rationale of selling is not really to make money. It's about preserving 200-plus jobs and making sure your colleagues have continuity in their lives." - Alessandro Comerci
Strategic divestitures and factory closures have become more common as organizations reshape their portfolios and seek agility. For procurement, these aren't just commercial events: they affect livelihoods, brand trust, and supplier ecosystems. Navigating them well demands a broader set of skills, perspective, and empathy than most of us learn in our core work.
In this episode, procurement veteran Alessandro Comerci draws on hard-earned experience negotiating large corporate divestments for Procter & Gamble. Alessandro reveals how job preservation, trust-rebuilding, and a nuanced understanding of local realities can drive better outcomes than straightforward cost calculations ever could. 
If you've ever faced tough transitions or wondered how procurement leaders adapt to 'the other side' of the table, Alessandro's practical, candid insights will strike a chord.
In this episode, Alessandro covers:
How job preservation and trust-shaping drive strategic divestments
How procurement skills translate to high-stakes selling
Why supplier relationships outlast the deal and why that matters
How divestments can spark unexpected supplier-led innovation
Links:
Alessandro Comerci on LinkedIn
Subscribe to This Week in Procurement
Subscribe to Art of Procurement on YouTube

Procurement doesn't have a data problem. It has a data delusion.
For 25 years, the function has told itself the same story: if we can just clean up our spend, we'll finally be in control. And yet here we are… swimming in the same dashboards, drowning in fields, and still struggling to answer a simple question: what do we spend?
In this episode of Buy: The Way…To Purposeful Procurement, Jason Busch, founder of Spend Matters and now a self-described builder of AI "co-workers," returns to the podcast to pressure-test BuyLaw #5: "prioritize comprehensive, high-quality data."
If procurement wants to operate in a world of AI employees, continuous validation, and P&L accountability, their data cannot remain partial, fragmented, or shaped by suppliers. 
Jason draws a sharp distinction between the roles or entities that manage procurement data: copilots, agents, and what he calls digital co-workers (multi-agent infrastructures capable of executing complex work autonomously). But all that capability comes with a catch. When the marginal cost of activity drops toward zero, the absolute risk of bad data increases exponentially.
Humans have the battle scars and the intuition to know when something isn't quite right with the data. AI doesn't, unless we explicitly teach it what 'right' looks like. That's where procurement's comfort with incomplete data becomes dangerous.
For decades, the function has relied on narrow slices of information: negotiated price, historical spend, maybe a market index or two, but in an AI-enabled world, that's insufficient. Jason explains why context means everything – supplier financial health, commodity forecasts, tariffs, inventory signals, competitive pricing, risk data, contract performance signals, governance structures, and the cultural guardrails that determine how decisions are made.
If procurement feeds incomplete, biased, or poorly governed data into increasingly autonomous systems, those systems won't just make mistakes faster; they'll actually end up institutionalizing them and making procurement's data problem unnecessarily worse.
Jason's advice for procurement is pragmatic and urgent: set up a data governance committee tomorrow. Not to tidy historical spend, but to define what data matters, which sources are trustworthy, what tolerances exist for error, and at what point autonomous systems are allowed to act on that data.
In a world of digital co-workers, incomplete data isn't a nuisance. It's a real, human liability.
Links:
Jason Busch on LinkedIn
Rich Ham on LinkedIn
Learn more at FineTuneUs.com