An efficient sales process is the lifeblood of any company. Every team on a deal can be working well while the deal still waits, because the handoffs between them are just a little off. Secant Advisors brings senior leadership insight that pulls the strategy together, helps teams get creative deal by deal, and finds where the process can be streamlined. The interfaces between teams are defined so the process scales as the company scales.
Splunk, Okta and Klaviyo. Three consecutive companies that each crossed a billion dollars in revenue during his time inside them. A founding member of US deal strategy through a run from $668M to $2.23B in revenue, territory automation across 400-plus reps, a go-to-market systems team of seven, and a CPQ implementation at each. Before that, fifteen years selling and delivering technology at Quest Software.
Deal strategy, commercial guardrails and deal reviews. Senior support on the deals that need extra guidance, while the business keeps running.
The artifacts and process changes the business needs, from a simple approval matrix to a detailed deal structure and bookings guide, a streamlined process or an AI workflow.
Usage-based or outcome-based pricing starts showing up in large enterprise contracts, with commitments and true-ups the old process was never built for.
Bookings, approvals and revenue recognition need to hold up to a new CFO, an audit or public-company scrutiny.
Acquisitions bring more than one price book, contract paper and approval path into a single deal.
A deal desk, revenue operations or GTM systems leader moves on, and deals cannot wait for the backfill.
And just as often, a growing team that simply wants its deals to move a little faster.
Deal velocity, in about a minute. Captions are on by default.
Large deals that close faster, and sellers who know how the rest of the deal works.
One shared plan for the path a deal takes across teams that report to different leaders.
Less discount leakage, and deals that book and recognize cleanly.
Deal velocity measured the same way across the portfolio, read again a quarter later.
Standard terms and structures, so fewer contracts are redlined from scratch.
Sales, finance, legal, deal desk and systems each belong to a different leader. Support teams join the deal too, like forward deployed engineers, business value and enablement. Each works well on its own, and the time is lost in the handoffs between them.
| Team | Usually reports to | Where the handoff is a little off |
|---|---|---|
| Sales | Sales leadership | How the company engages buyers is not connected to when other teams get involved |
| Deal desk and pricing | Finance or RevOps | Exceptions decided one deal at a time |
| Finance and Revenue Recognition | The CFO | Commitments and revenue treatment settled after the terms are agreed |
| Legal | General Counsel | Non-standard terms redlined from scratch |
| Quote-to-cash and billing systems | RevOps or the CIO | Deal terms the systems cannot quote, book, bill or recognize cleanly, so they get handled by hand |
| Team | Usually reports to | Where the handoff is a little off |
|---|---|---|
| Deployment and forward deployed engineers | Product or Engineering | Scoped after signature instead of before |
| Business value | Sales or Solutions | Value story disconnected from price and delivery |
| Sales enablement | Sales or RevOps | A strong cadence for sellers, but without the deal context to connect pricing, contracts, systems and value |
| Field programs | Marketing | Programs not tied to live deals |
Each team keeps running its own way. Secant defines what passes between them: the trigger, what is handed over, who owns it next and how fast. Together the interfaces add up to one shared plan for every deal, and as the company grows, teams can change how they work inside without breaking it.
Eighteen handoffs, not a straight line. Sellers sit at the center and meet every team except finance.
| Example handoff | Trigger | What is handed over |
|---|---|---|
| Sales stages to every team | A deal reaches an agreed stage | Which teams engage next, using whatever methodology the team already runs |
| Sellers to deal desk | Non-standard pricing or terms appear | Deal context, the customer's commercial ask and the business case |
| Deal desk to Finance and Legal | Structure agreed | Terms that need review, with the revenue recognition treatment flagged |
| Sellers to deployment | Before signature, not after | Scope, success criteria and the timeline the customer agreed to |
| Signature to quote-to-cash | Contract signed | A booking package the systems can book, bill and recognize without rework |
| Deals to enablement | A pattern repeats | What sellers need to know so the next deal does not need the same help |
The current engagement model, methodology, tools and org, formal or not. Formalize only what keeps breaking.
A simple approval matrix for an early team, a detailed guide for a more mature one. More structure arrives as the company does.
Standards come from the deals that needed help, not from a framework rolled out up front.
A baseline first, and the same number read again after.
Two layers, worked at the same time. The running support shows where the business needs to change, and each change makes the next deal easier to run.
Deal strategy, commercial guardrails and deal reviews. Senior support on the deals that need extra guidance, helping teams get creative deal by deal while the business keeps running.
The artifacts and process changes the business actually needs. Along a continuum, sized to where the company is:
A simple, one-page matrix, often all an early team needs.
A detailed guide and bookings policy for a more mature business.
Changes to an existing process where the handoffs are a little off.
Added where it makes the deal faster, and governed like any other change.
The work is breaking down barriers and improving efficiencies between teams. Sometimes that takes AI, and often it takes simply a better process. AI workflows already inside the deal path, such as quote generation, approval routing, clause risk flags, value cases and deal clinics, are assessed where the work happens rather than as a separate program.
Every change gets one test: did the deal get faster? AI workflows also have to show they work on real deals and are governed, because agents acting on quotes, contracts and bookings touch the records that most need controls.
The signals a leadership team will recognize:
Usage-based or outcome-based pricing moving into large enterprise contracts, with commitments, true-ups and credits the old process was never built for.
Deal desk, pricing, GTM operations, business value, deployment and enablement each staffed, with no one leading across them.
Exceptions, redlines and approvals that add weeks, decided one deal at a time.
New tools and AI spread across sales, legal and operations, with nobody able to say whether deals move any faster.
The first three stages are familiar consulting work. The fourth is the one most programs skip, and it is the reason for the other three. A roadmap that is never checked against the number it was built to move is only a document.
The numbers. Deal velocity measured two ways. Leading signals that move within weeks: exception rate, approval turnaround, quote revisions after a proposal, and booking rework. And cycle time, from proposal to signature and from signature to production. Built from the CRM and the client's own records, scoped to one segment, region or set of strategic deals.
Where each deal actually waited. Every component of the deal path, how the work runs today, the systems behind it and any AI workflows touching it. Captured from real deals rather than reconstructed in a workshop.
The few interfaces that cost the most. Each candidate change is scored on the velocity it should move and sized to the company's stage. If a change cannot name the number it is meant to move, it does not go on the roadmap.
The signals moved, or they did not. The leading signals, read again on the same basis a quarter later. Cycle time is reported too, as a direction rather than a verdict, because a single quarter rarely closes enough large deals to prove it on its own. Changes get kept, fixed or dropped on the reading rather than on enthusiasm. This is agreed and priced at the start, because a reading left until later does not happen.
Most engagements start small on purpose: one segment, one reading, and then a decision about whether to go further.
Velocity measured, every team and handoff mapped, and the costliest interfaces named. Fixed fee, scoped to a segment.
Baseline, interfaces defined, a cross-functional deal review, and the re-read. Only the artifacts the business needs, built into the enablement cadence and applied to live deals.
A standing Deal Velocity lead, or interim cover for a GTM systems, deal desk or revenue operations seat. Fractional at one to three days a week, or interim full time, typically starting inside a month. What the seat owns gets a number on the way in and the same number on the way out.
A regular deal review, with access on the largest deals. For teams that already run well and want senior insight on what does not fit the standard.
Stages one and four, for a program someone else is running. Large integrators and internal transformation offices are measured on delivery milestones. Neither is accountable for whether deals got faster, and the sponsor who approved the spend will be asked exactly that. Secant answers that question independently, each quarter, in a short written reading.
Secant does the baseline, the discovery, the roadmap and the quarterly reading, and works the deals that need help. Where an engagement calls for larger build work, such as systems implementation, data engineering or enablement content, trusted specialists can be brought in.
Their work is tied to specific items on the roadmap, so it gets measured the same way as the rest of the program, and who does what is agreed up front.
Independence where it matters. When Secant is hired to give an independent reading on a program, it does not also sell delivery work into that program or take a seat on it.
Fifteen years selling technology before building any of it. Application development and consulting sales first, then business value consulting and seven years running a services organization, sales and delivery both. Scoping and structuring services contracts is where the finance and legal fluency comes from.
Then deal strategy, close to how large deals actually get structured and approved, and from there into building the systems that carry them: CPQ, contract lifecycle, integration, territory, and the enterprise booking policy governing non-standard transactions. Bookings policies, deal structure guidebooks and field training built and rolled out with enablement teams. The most recent team spanned sales systems, seller experience and deal strategy, pre-sales and post-sales both.
Business process and automation have always meant process first, designed from the stakeholder's view. Fifteen years as the person demanding things from a systems org came before a single day inside one.
The work has always had the same shape: build the process out to consistency, instrument it, and report whether it moved. Most recently that meant repositioning a go-to-market systems function around AI, as the go-to-market representative on a company-wide AI Council. Today that means building agents, skills and connector architectures day to day, and writing publicly about what holds up in the LinkedIn newsletter AI in GTM Operations.
Where an engagement needs depth outside these capabilities, senior operators from a trusted network can be brought in.
The first conversation is one question, and the client does most of the talking: how long did the last ten large deals take, and where did each one wait?
If there is a number leadership would stand behind, the work starts from it and nothing new is built. If nobody can answer, that is the first finding, and it is far cheaper to know now than after the next quarter is judged on it. If the problem is an empty seat, the first conversation is different: the date it needs filling and what the seat owns.
LinkedIn profile · AI in GTM Operations, the newsletter