Zanovoy

Zanovoy partners with the Office of the CFO to modernize finance operations across ERP, procurement & FP&A. Integrated systems. Engaged beyond go-live.

PE, Life Sciences, Manufacturing & more.

08/05/2026

The most expensive disagreement in a leadership meeting is not about strategy. It is about whose number is right.

Sales says revenue is one figure. Finance says another.

Both are technically correct, because they are measuring slightly different things and calling them the same word. The meeting that was supposed to be about a decision becomes a debate about definitions, and the actual question gets deferred to next time.

This is not a tooling problem first. It is a definitions problem.

When there is no single agreed meaning for revenue, churn, ARR, or gross margin, every system that reports them will reflect a different assumption, and every dashboard becomes arguable.

The fix nobody wants to own: a governed set of metric definitions, agreed once, enforced everywhere, so the number is the number regardless of which screen it appears on.

The technology can only enforce a definition that the organization actually decided on.

Until that exists, better dashboards just produce faster disagreements.

How many versions of your most important metric exist across your tools right now?

08/04/2026

Most forecasts are built as line items.

Rows of accounts, each grown by a percentage, rolled into a total. It looks rigorous. It usually is not, because it models the outputs of the business instead of what actually moves them.

A business does not run on ledger lines.

It runs on drivers. Headcount, pipeline conversion, price, usage, churn. When those move, everything downstream moves with them.

A line-item forecast hides that relationship. Change one assumption and you are manually updating forty rows, hoping you caught them all, unable to answer the question a board actually asks: what happens to the plan if this one thing changes.

Driver-based planning inverts it.

You model the handful of things that genuinely move the business, and the line items follow from them. Now a scenario is one input away. What if conversion drops two points. What if we hire a quarter late.

The model answers, because it is built on the logic of the business, not just its chart of accounts.

The accuracy problem in forecasting is often really a structure problem.

What are the six drivers your business actually runs on?

07/30/2026

The boldest claim in AI-native finance is autonomous accounting.

Books that close themselves, entries that post without review, a finance function that runs on its own. It is a compelling pitch. It is also not the version that works yet, and the honest platforms know it.

Here is the distinction that matters. Automation handles the volume. The recurring entries, the standard reconciliations, the pattern-matching that fills a controller's week. Removing a human from that is a gain.

Autonomy means removing the human from the judgment too, the contract modification, the unusual accrual, the anomaly that is either an error or the first sign of something real. Removing the human there is not a gain. It is a risk with a confident interface.

The platforms worth trusting are precise about the line. They automate aggressively and stay explicit about which decisions still route to a person.

That is not a limitation they are apologizing for. It is the design that makes them safe to run a ledger on.

AI-native platforms like Rillet and Campfire earn trust exactly by being clear about where the human stays.

Autonomous sounds better in a demo. Human-in-the-loop is what survives an audit.

Where would you want a human to stay in your close?

07/29/2026

The three-way match is the quiet tax on every accounts payable team.

Purchase order, goods receipt, invoice. When all three agree, the payment flows.

When one does not, the invoice drops into an exception queue and a person has to work out which of the three is wrong, chase the answer across departments, and hold the payment until it resolves.

The frustrating part is that most mismatches are not fraud or error. They are timing. The receipt posted late. The invoice used a different unit price than the PO.

A partial delivery split one PO across two invoices. Each is small. Together they consume more AP time than the matches that pass.

The fix is not more reviewers.

It is enforcing the match at the point of entry, so the exception is caught and routed the moment it appears instead of discovered at payment run.

Policy tolerances handle the small variances automatically. People only touch the ones that actually need judgment.

What share of your AP team's week goes to exceptions instead of payments?

07/28/2026

Every finance team has an official system and a real one.

The official system is the ERP. The real one is the collection of spreadsheets and side databases where the actual work quietly happens.

The shadow spreadsheet appears for an honest reason.

The system does not do the one thing the team needs, so someone builds a workaround. It works. It spreads. Soon a critical number, a reconciliation, a whole reporting pack lives outside the system of record, in a file with no version control, no audit trail, and one person who understands it.

This is not laziness. It is the finance team routing around a gap the system left. But it carries real risk. The shadow file is where errors hide, where knowledge concentrates in one head, and where the audit trail simply stops.

The presence of shadow spreadsheets is diagnostic. It tells you exactly where your system is failing the people who use it.

The fix is not banning the spreadsheet. It is asking why it had to exist, and closing that gap in the system itself.

What is the one spreadsheet your close could not survive without

07/23/2026

Somewhere between wanting control and having it, approval workflows quietly become the thing that slows the business without actually protecting it.

The pattern is familiar. A purchase needs sign-off from a manager, then finance, then a second finance approver over a threshold, then procurement, then legal if a contract is involved.

Each step was added for a reason. Together they form a chain where a routine purchase waits days for approvals that are, in practice, rubber stamps, while the one purchase that actually needed scrutiny sailed through because everyone assumed someone else was looking.

More approvals do not equal more control. Past a point, they produce the opposite: approvers who stop reading because everything routes to them, and requesters who learn to route around the process entirely.

Good approval design is about thresholds, not layers.

Small, low-risk spend clears automatically. Scrutiny concentrates where the risk actually is. The people who approve are the people whose judgment the decision genuinely needs.

An approval that protects nothing is just latency with a signature.

How many steps does a routine purchase take in your workflow?

07/22/2026

Rogue spend is rarely dramatic. It is not fraud in most cases.

It is a manager expensing a tool the company already pays for, a team buying from an unapproved vendor because it was faster, a subscription that renews on a personal card and reimburses through the back door.

Each instance is small and defensible on its own.

The pattern is what costs money. Spend that happens outside approved workflows is spend your controls never checked, your negotiated rates never applied to, and your budget owners never saw coming. It surfaces after the fact, in a variance nobody can fully explain.

The instinct is to police it harder after it happens.

The better design prevents it at the point of purchase. When buying flows through an intake where policy is checked before the money moves, off-policy spend gets caught as a request, not discovered as a line item. Control designed into the workflow beats control enforced by audit.

Rogue spend is not an ethics problem. It is a workflow problem wearing an ethics costume.

How much of your spend happens where your controls cannot see it?

07/16/2026

About 80% of "ERP implementations" are actually customization projects the standard configuration could have avoided.

Here's how it happens:

A discovery call surfaces 14 "must-have" requirements. Eight are habits, not requirements. Three are workarounds for a broken process. Three are actually unique.

The implementation partner who builds against 14 customizations earns more. The implementation partner who pressure-tests each one against two questions earns less, but builds something that survives:

1. Can the standard configuration handle this?
2. Will this survive the next platform update?

Customizations built to be maintained beat customizations built to be impressive. The documentation discipline matters more than the build discipline.

If your last implementation has 50+ undocumented custom workflows, the bill you're paying isn't to maintain them. It's to keep paying because nobody else can figure out what they do.

07/14/2026

Six weeks from go-live. Your functional owner just quit.
The deck is still green. But the person who could answer "why do we do it that way" is walking out the door.
Here's what actually happens next, and what to do instead. ⬇

07/09/2026

The "continuous close" is the most-cited capability of AI-native finance platforms. It's also the most misunderstood.

Most 10-day closes don't need a new platform. They need four things fixed on the one they already have.

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