# Ray Hill

Ray Hill shares practical perspectives on modernizing finance operations, using process intelligence to find recurring work and improve outcomes across areas such as order-to-cash, accounts payable, and financial planning.

- Profile: https://b2binfluencer.marketing/creators/ray-hill/
- LinkedIn: https://www.linkedin.com/in/debrerhill
- LinkedIn followers: 853
- Topics: artificial-intelligence, ai-in-finance
- Based on 15 dated posts, latest 2026-10-08

## Summary

Ray Hill is useful for finance operations talks that connect process data to practical decisions in order-to-cash, accounts payable, record-to-report, and FP&A.

- Best for: A finance transformation consultancy or CFO roundtable needing practitioner-led speaking and co-produced LinkedIn content.
- Not for: A software vendor wanting guaranteed reach, lead volume, or a product-led webinar as the central proof point.
- Check first: Confirm whether Ray Hill offers sponsorship formats, rates, audience data, and approval terms in writing.

### Takeaways

- Finance modernization starts with the work and its constraints, not with AI.
- Automating order-to-cash is not the same as making it perform.
- Process mining exposes variation hidden inside a process and what a single measure misses.

## Main ideas

- **Finance modernization starts with the work and its constraints, not with AI**: Ray Hill argues that most discussion of AI in finance is commentary about the topic rather than the work itself, and that finance modernization is a discipline rather than a technology project. The starting point is how a finance function's data is structured, layered, moved through the business, and shaped by the variation in how work actually gets done. Applied technology comes later, once the function and its constraints are understood.
- **Automating order-to-cash is not the same as making it perform**: Ray Hill argues that AI can automate much of order-to-cash execution without improving process performance; the real question is where the work goes wrong. The alternative is to ask where cash is delayed, where customer commitments break, where people repeatedly intervene, and where exceptions are created upstream and managed downstream. Each exception signals how the operating model is performing, rather than presenting an isolated automation opportunity. The objective is a business result — faster cash flow, fewer exceptions, stronger customer commitments, less unnecessary manual intervention — not more AI.
- **Process mining exposes how much variation hides inside a process — and what a single measure misses**: Ray Hill describes drilling into a process and finding that what first looks orderly becomes dozens, hundreds, or thousands of ways the work actually gets done. Data can reveal a pattern, but the people closest to the work often explain it; the hard part is deciding what the business is prepared to change once the full story is visible. A single KPI and a frontline account can both be true without being the same conversation.
- **Give every finance stream a result it owes, then build a business case you can prove**: Ray Hill assigns each part of finance a next result rather than a generic improvement: source-to-pay should protect critical supply and put cash to work, order-to-cash should convert profitable commitments into predictable cash, record-to-report should surface material shifts while leaders can still act, and FP&A should move capital and capacity as conditions change. The described method — a finance modernization workbench — follows the handoffs, finds what constrains the result, scopes the change, and builds a business case with a clear way to prove it. Once a result is proven, it becomes the starting point for the next business case.
- **Constraints and measurable contribution decide which AI ideas deserve investment**: Ray Hill's answer to the abundance of AI possibilities is constraints-based value engineering: rather than inventorying technology, determine which possibilities deserve investment and what must change around them to produce value. They describe studying the work, watching decisions and handoffs, and measuring business contribution; those observations shape the goal, the solution, and the next move. The practice draws on the Theory of Constraints and process reengineering.
- **The thinking is deliberately unfinished and open to challenge**: Ray Hill frames the writing as working in the open — sometimes thinking out loud — and invites readers to bring their operational reality, challenge the assumptions, and sharpen the next move. The post ends with a question rather than a conclusion. The material also holds a tension: it treats AI skeptically when discussed without the underlying work, yet presents AI as a reason to revisit what finance could anticipate, decide, and deliver, and as something that expands what is possible. Its value depends on whether the work underneath has been understood first.

## Work to read

- [Empty AI talk versus the work underneath](https://www.linkedin.com/posts/debrerhill_financemodernization-financetransformation-activity-7513751813515542528-STk-)
- [AI can automate order-to-cash without making it perform](https://www.linkedin.com/posts/debrerhill_nexactsolutions-ordertocash-o2c-activity-7508539431742607360-942T)
- [What process mining reveals, and the conversation it exposes](https://www.linkedin.com/posts/debrerhill_processmining-processintelligence-ordertocash-activity-7503066470554263552-8ABD)
- [Following recurring finance work back to its source](https://www.linkedin.com/posts/debrerhill_finance-modernization-po-series-activity-7510537682566049792-Qrzu)
- [A repeatable business-case loop for finance modernization](https://www.linkedin.com/posts/debrerhill_finance-modernization-continuous-transformation-activity-7511428037020872704-MI3a)
- [Modernization and transformation are not the same thing](https://www.linkedin.com/posts/debrerhill_finance-modernization-study-part-3-activity-7512028277574713345-gzeF)

## Brand relationships

- **Nexact Solutions LLC** (disclosed_partnership)

## Partnerships

Ray Hill publishes finance-transformation thinking on behalf of Nexact Solutions LLC, with a consultative engagement style rather than a packaged creator sponsorship. Posts invite readers to bring a recurring problem to the team, discuss where AI and process intelligence fit in a finance operating model, or explore the firm's finance-modernization material. These are openings for working conversations about finance operations, not published sponsor offers. The posts don't specify sponsorship formats, rates, deliverables, exclusivity terms, audience guarantees, or approval timelines, and no official partnership inquiry page or media kit appears alongside them. Before committing to a content collaboration or speaking engagement, ask directly about scope, compensation, review process, and disclosure expectations. The subject matter includes order-to-cash, source-to-pay, record-to-report, FP&A, process mining, and constraints-based value engineering, with an emphasis on evidence-led, plain-language discussion over surface-level AI commentary. A co-authored perspective, recorded working session, or finance-operations speaking slot may fit better than a standard product-placement sponsorship; confirm available formats directly.

## Alternatives

- Victoria Shcherbakova: Choose Victoria Shcherbakova when the roundtable's real subject is change fatigue rather than process detail. The two posts reviewed argue that finance is no longer transforming occasionally but operating in permanent change, that transformation fatigue is not only a wellbeing issue but a business risk affecting trust, productivity, adoption and value creation, and that the future finance function will be defined by how much change it can absorb. For a consultancy whose follow-up offer is helping a finance organisation sustain a transformation, that framing gives the room a shared problem to name and a reason to keep talking after the session. It also suits a conference or client event where the audience's complaint is change overload rather than missing process intelligence.
- Pranil C. Pawar: Choose Pranil C. Pawar when the need is finance controls and anomaly detection rather than process intelligence across the whole function. Their posts argue that as AI becomes better at producing answers, leadership shifts from finding information to applying judgment. They use the line that fraud rarely starts with a large transaction but with one exception nobody notices to ask whether accounts payable and receivable merely process transactions or actively protect the business. That is a sharper angle for a CFO audience worried about duplicated invoices, unauthorised vendor changes, delayed collections and unusual transactions, and it pairs with a controls, audit or risk follow-up offer rather than a process-redesign offer.
- Tino Lancellotti: Choose Tino Lancellotti when the audience is enterprise architecture and transformation leadership rather than finance operations. Their ERP post argues that AI is not replacing ERP systems but replacing the workflow layer built on top of them, and lists five changes to how a consolidation programme should be designed: keep consolidating the system of record, stop building workflows inside the ERP, add an AI orchestration layer, invest in master data and semantic modelling, and architect for AI-native operations. Their second post extends that to agentic AI joining contract, service, finance and customer data to reach long-tail accounts, including data federation and a single customer identifier. A consultancy selling an AI-native architecture story can build a session on that split between the system of record and the system of work, and the co-produced piece can take a position CIOs and transformation leads will argue with.

---
AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/