The Trust Gap

You've invested six figures or more in NetSuite. You have real-time data, automated reports, customizable dashboards, and analytics capabilities that should make any finance leader happy. So why does your CEO still ask Finance to "put together a quick spreadsheet" before every board meeting?

Because somewhere along the way, the numbers didn't match reality. Maybe it was once. Maybe it was a few times. But the memory of that discrepancy persists. Once trust is broken, executives route around the system—no matter how much you've invested in it.

The frustrating part is that the mistrust often isn't the system's fault. It's configuration problems, data quality issues, or communication gaps that could be fixed. But until they are fixed, you have an ERP that people don't trust, which means you have an ERP that isn't delivering its full value.

How Trust Gets Broken

The Numbers Changed

An executive pulled a report Monday and again Wednesday, and the numbers were different. Maybe there's a good reason—late entries, corrections, timing differences. But if nobody explained it, all they remember is that the system showed different numbers on different days.

From their perspective: if the system can show $4.2M revenue on Monday and $4.1M on Wednesday without explanation, how do they know today's number is right? The seed of doubt is planted.

The Report Was Wrong

It only takes one material error—revenue double-counted, expenses in the wrong period, a formula that broke—to create lasting skepticism. That one wrong number gets remembered longer than months of accurate reporting.

Executives remember: "Finance told us we hit target, then came back a week later and said we missed by 5%. What else is wrong that we don't know about?"

It Doesn't Match Their Mental Model

Executives develop intuition about the business through experience. They have a sense for what revenue should be, what margins should look like, what the pattern should be. When reports don't align with that intuition—and nobody can explain why—they assume the report is wrong.

Sometimes they're right, and there is a data problem. Sometimes they're wrong, and the business has genuinely changed in ways they haven't internalized. Either way, the unexplained gap erodes confidence.

Nobody Can Explain It

When an executive asks "why did margin drop 3 points?" and gets "let me look into it and get back to you," confidence erodes. If Finance doesn't understand the data instantly, how can executives trust it's right?

Every "I'll get back to you" signals that Finance doesn't have real-time mastery of the numbers. That's often unfair—complex questions legitimately require research—but perception matters.

Reports Don't Reconcile

The revenue dashboard shows one number. The P&L shows another. The sales commission report implies a third. They should all tie, but they don't quite.

Each report might be correct for its purpose, but the differences create confusion. Executives don't want to understand the nuances—they want one number they can trust.

The Real Root Causes

Data Quality Problems

The most common source of reporting mistrust is data quality issues at the source. Transactions entered incorrectly. Missing dimensions. Inconsistent classifications. Bad data flows through to reports and produces unreliable output.

Data quality is often treated as a downstream cleanup problem rather than an upstream prevention problem. That's backwards. Every incorrect report starts with incorrect data entry.

Period Management Issues

If data can change after reports are published, executives will never trust any number. Late entries, corrections after period close, adjustments without clear communication—these create the "numbers changed" problem.

Disciplined period management—closing periods promptly and limiting post-close changes—is essential for trustworthy reporting.

Calculation Inconsistencies

Different reports calculate metrics differently. What counts as revenue? How is cost of goods sold determined? What's included in margin?

When definitions vary across reports, numbers don't reconcile, and users lose confidence.

Report Design Problems

Sometimes reports are technically accurate but misleading. Confusing layouts. Metrics without context. Data that requires interpretation but provides none.

A report that's technically correct but misunderstood might as well be wrong.

Communication Gaps

Finance knows why the numbers changed. Finance knows what adjustments were made. But if that knowledge doesn't reach the people using the reports, the changes seem random or suspicious.

Rebuilding Trust

Fix Data Quality at the Source

Every incorrect report starts with incorrect data entry. Build validations, automations, and upstream controls that prevent problems before they reach reports.

Custom scripts can enforce data quality rules that native features can't: validating combinations of fields, checking against reference data, requiring approvals for unusual values, preventing common errors.

Data quality is not a one-time cleanup—it's ongoing governance. Build it into daily operations.

Lock Periods Promptly

Once a period is reported, lock it. Minimize post-close adjustments. When adjustments are necessary, make them in subsequent periods with clear documentation.

Users should trust that the numbers they saw last month are still the numbers for last month. That stability enables planning and analysis.

Version and Timestamp Everything

When reports change, have a clear audit trail of what changed and why. Unexplained changes are what kill trust. Explained changes build confidence in the process.

Custom reporting solutions can capture version history: the report showed X at this time, then Y at this time, with documented reason for the change.

Reconcile to External Truth

Bank statements, customer confirmations, third-party data—when internal reports tie to external sources, credibility increases.

Build reconciliation into regular processes. Don't just verify that the bank reconciles; show users that it reconciles. External validation supports internal confidence.

Standardize Definitions

Create a data dictionary defining how key metrics are calculated. Revenue, cost of goods, margin, EBITDA—define each once and apply consistently across all reports.

When reports disagree, you can point to definitions rather than appearing to make up explanations.

Build Self-Explaining Reports

Custom dashboards can show not just what happened, but why. Variance explanations built into reports. Drill-down capability that lets users verify the underlying data. Context that helps users interpret results.

When executives can verify for themselves, trust grows.

Train Executives

A 10-minute walkthrough of how a dashboard works creates more trust than a 50-page data dictionary nobody reads. Show executives how data flows, where it comes from, how to verify it.

Understanding breeds trust. Mystery breeds suspicion.

The Hard Truth

Trust is earned slowly and lost quickly. One wrong number undoes months of accurate reporting. The solution isn't better dashboards—it's better data, better processes, and better communication.

When executives trust the data, they stop asking for spreadsheets. They use the system. They make faster decisions based on real-time information. That's the ROI of trustworthy reporting.

Until then, every report is guilty until proven innocent.