A CFO for a mid-market manufacturer stared at a dashboard that was supposed to tell whether the quarter would close in the black or the red. The numbers flickered, refreshed, and then contradicted yesterday’s report. The team blamed “the system.” The system, as it turned out, was a cloud ERP platform into which the company had invested seven figures and a year of implementation effort. What they actually had was not a single source of truth, but a single point of failure that everyone was quietly working around.
Scenes like this have become a defining paradox of modern finance operations. The global ERP software market, estimated at around $60–$65 billion in annual revenues in 2024 and projected to double by 2030, continues to grow at a double-digit compound annual rate as organisations chase real-time visibility and control. Yet the lived reality in many finance departments is one of spreadsheet detours, manual reconciliations, and month-end “war rooms,” even as vendors herald an era of autonomous close and AI-driven decision-making. It is in this gap between promise and practice that Etter+Ramli, a specialist in post‑go‑live NetSuite governance, has chosen to stake its claim, and where its founder, Todd Kimpton, is emerging as a persistent voice for CFOs.
The Quiet Failure of Go‑Live
Analysts now project the ERP market to grow to roughly $90–$120 billion by the end of this decade, driven by the industry’s need for data-driven decision-making and automation. Yet surveys consistently show that a large share of ERP value is never realized: projects finish broadly on time, but organizations revert to manual workarounds, shadow spreadsheets, and bespoke reports that no one fully trusts. When finance leaders do talk publicly, they describe systems that are technically live but functionally brittle—difficult to change, opaque in their logic, and heavily dependent on a handful of administrators.
Kimpton’s diagnosis is straightforward: “Most ERP systems don’t fail with a bang, they fail with a shrug,” he says. “Users do often tell vendors and partners that things aren’t working, but support desks can only advise so much, and commercial teams tend to focus hardest around renewal. In the meantime, people quietly stop believing the numbers and go back to Excel, because reverting to Excel is fast, familiar, and feels safe.” Kimpton is careful to separate execution from accountability. In his view, automation does not diminish the role of finance leaders—it sharpens it. As AI absorbs routine work, human value concentrates around judgment, risk ownership, and the definition of acceptable failure, responsibilities that no system can assume on its own. Once users are back in spreadsheets, they feel productive and justified in their roles, even as the system is steadily sidelined. In Etter+Ramli’s client base, many engagements start months or years after go‑live, once the organisation has accumulated what he calls “quiet entropy,” a build-up of unreported issues and workarounds that never make it into ticket queues.
From Implementation Project To Operating System
The pivot from project to platform is where Etter+Ramli has carved out a distinctive niche. Unlike traditional providers, the firm is not structurally geared toward implementation fees; it engages primarily once the system is in production, positioning itself as a long‑term operator rather than a project‑based builder. Its core offering is a retainer‑based NetSuite Managed Services model that bundles optimisation, governance, and automation into a single, predictable monthly engagement. When clients explicitly request it, the team will lead or rescue implementations, drawing on Kimpton’s experience deploying NetSuite into around 100 businesses.
On the surface, this appears to be another variation on managed services, a segment that has expanded alongside cloud ERP. But that label understates the firm’s intent. Etter+Ramli positions itself less as a provider of support capacity and more as an operational steward—responsible for keeping the system coherent, governable, and trustworthy as it evolves. Across its client base, Etter+Ramli observes that organizations with tighter governance tend to reduce their total cost of NetSuite ownership by 8.7%, while growing transaction volumes by 7.4% and decreasing active user counts by 4.1%. This outcome suggests both the consolidation of workflows and a tighter definition of roles. In a market where license utilisation and user sprawl can quietly erode margins, those numbers stand out.
CFOs Confront the AI Readiness Gap
A Gartner survey found that 58% of finance functions were already using some form of AI, up 21 percentage points from the previous year, with primary use cases in intelligent process automation, anomaly detection, and analytics. At the same time, respondents cited inadequate data quality and a shortage of technical skills as their biggest obstacles to scaling AI in finance, a tension that is evident in ERP environments, where transaction data, workflows, and approvals are deeply intertwined.
Vendors have been keen to capitalise on that interest. NetSuite, like its peers, has rolled out embedded AI capabilities across its suite, positioning them as tools to boost productivity and accelerate insights. Advisory firms have gone further, outlining 90-day AI readiness frameworks and cautioning that companies that delay data standardization, workflow mapping, and governance will be 12 to 18 months behind their peers. The message to CFOs is clear: move now, or risk competing with one hand tied behind your back.
Kimpton sees a different kind of risk. “The uncomfortable truth,” he says, “is that a lot of ERPs are not just unready for AI—they are unstructured for it. Poorly governed systems produce poor-quality data, and most ERP clients don’t have the level of process control and data oversight that AI agents need to operate with confidence. If you have five versions of the truth in your invoice data, an AI agent will simply amplify that confusion at machine speed.” For Kimpton, the goal is not artificial intelligence as an autonomous decision-maker, but as a governed operator. He describes future ERP environments as systems in which AI agents execute within clearly defined permissions, escalation paths, and audit boundaries—acting at machine speed but always within human-defined authority. In parallel, Etter+Ramli incorporates renewal renegotiation into its Managed Success model, managing vendor contractual relationships on behalf of clients. Their independence from the partner ecosystem allows them to represent customers without conflicts of interest and to recognize renewal patterns that many clients never see. That independence, Kimpton argues, is essential; once an advisor is commercially aligned with license volume or implementation scope, it becomes difficult to challenge whether the system is actually serving the business.
From Firefighting To Autonomous Operations
What Etter+Ramli is selling is not a technology stack but a change in operating rhythm. Many NetSuite customers arrive with familiar symptoms: unreliable reports, proliferating custom scripts, brittle integrations, and a month‑end close that depends on a handful of spreadsheets no one wants to admit exist. The firm’s practitioners first discuss data quality and workflow discipline before they address AI agents or autonomous close.
This sequencing aligns with broader advice from ERP specialists, who caution against treating AI as a shortcut. Blogs aimed at NetSuite customers now emphasize that chasing automation without addressing upstream processes merely accelerates exceptions and audit risk. In that light, Etter+Ramli’s insistence on structured governance sounds less like conservatism and more like a prerequisite for the kind of AI‑assisted operations vendors envision.
A Measured Voice in an Overheated Debate
In a technology landscape prone to grand narratives, Etter+Ramli’s positioning is deliberately narrow. The firm works only with NetSuite and only with live customers; it does not chase implementation fees as its primary engine of growth, and it does not describe itself as a reseller or traditional solution integrator. Growth has come instead through referrals, long‑term client relationships, and incremental scope expansion within existing accounts.
What distinguishes the firm is not any single innovation, but its insistence on framing ERP as serious infrastructure rather than a fashionable technology layer. Kimpton’s writing and speaking, much of it aimed squarely at CFOs, COOs, and CIOs, returns to the same theme: systems must be governed, not merely used. In an era when more than half of finance functions are experimenting with AI but still struggle with data quality and talent, that message carries a sobering quality. It also hints at a deeper anxiety: that the next wave of automation will not merely fix governance gaps, but rather expose them.
If ERP continues to be treated as a one‑time project, dispatched to integrators and revisited only at renewal, specialists like Etter+Ramli will remain niche players, summoned to clean up messes after the fact. If, however, CFOs come to see their core systems as living operating platforms, then the kind of methodical, post‑go‑live governance the firm practices may look less like an optional extra and more like a baseline requirement. In Kimpton’s experience, users rarely announce they are giving up on the system; they quietly step out of it and do the work offline instead. He estimates that as much as 80% of day‑to‑day pain never gets reported, because logging an issue feels “more expensive” in time and effort than just doing it themselves. That leaves management focused on the loud 20% of problems that justify formal projects, while the silent 80% erodes trust and efficiency in the background.
By leaning into that unreported 80%, Etter+Ramli aims to build the structural base on which automation can safely rest. “The big automation projects, the AI use cases—those are the visible 20%,” Kimpton suggests. “They only endure if the everyday experience for users is clean, fast, and dependable.” In Kimpton’s framing, the future of finance systems will not be decided by how much work automation can absorb, but by how clearly responsibility is defined when it fails.”
In a market hurtling toward autonomous, AI‑assisted operations, that unassuming promise, that the system will be quietly, dependably right, may prove to be the most consequential one of all.
