Stopping $100K Forecast Errors and Reclaiming Team Time with HeronAI

With HeronAI, Enrich turned a fragile, Excel-heavy forecasting process into a simple shared workspace the whole team can use. Monthly forecast prep dropped from around 40 hours to roughly 4–10, and spreadsheet maintenance went from about 20 hours a week to closer to 2–4. Instead of one person compiling everything, five to seven team members now enter data directly. That shift has pushed reconciliation issues close to zero, reduced what used to be about a $100,000 quarterly forecast error, and cut reporting from days down to hours so leaders can move faster and use meetings for real decisions.

Rich Chiano leads Enrich, a full-service lead-generation agency that mixes traditional media, digital campaigns, SEO, and website work. Over eight years the business grew steadily, and so did the complexity of its forecasting needs. Enrich could see past performance well enough, but predicting the future remained brittle, expensive, and organizationally risky.

That tolerance for a six-figure forecasting error was the company’s breaking point. If revenue can’t be predicted within $100k for a quarter, how do you plan hires, marketing spend, and vendor commitments? The human cost was also obvious. One team member, Mark, was spending enormous time cobbling spreadsheets and preparing the monthly forecast:

Rich framed it bluntly, the company was effectively paying a near-salary for manual data labor that a modern system should automate.

The brittle workflow: Excel, QuickBooks, and a patchwork of dashboards

Before Heron, Enrich’s analytics were a patchwork. QuickBooks handled accounting and historical numbers, client dashboards tracked campaign metrics, but forward-looking forecasts lived mostly in Excel. QuickBooks could tell Rich where they’d been, but projecting forward was a manual, error-prone ritual.

The consequences were clear, duplicated effort, fragile formulas, dependence on a single person’s tribal knowledge, and long preparation cycles that ate weeks of productive time each month. The business had visibility into past performance but not the kind of reliable, auditable forecasting it needed to make confident strategic choices.

Version two, a shared hub that scaled the work

Heron delivered a fundamentally different architecture for forecasting, a shared hub where multiple contributors enter projections and those inputs are linked into a single dashboard. Rich describes the deployment as “version two”, already useful for high-level projections and actively being expanded with drill-downs and historical capabilities. Critically, this was both a technical and a cultural shift, forecasting moved from being an individual’s heavy lift in Excel to a team-driven, auditable process.

By decentralizing data entry and centralizing the result, Heron eliminated the single-point bottleneck and made the monthly forecast a collaborative activity rather than a month-long spreadsheet ritual.

The economic and organizational payoff

The savings were immediate and measurable: five to seven people now input their own client projections rather than one person collecting and rekeying everything. That reduced transcription errors, sped up reporting, and removed the dependency on Mark’s manual work. But the payoff reaches beyond raw hours saved.

Preparing for the monthly forecast shifted from a multi-day grind to a streamlined meeting. Instead of any one person spending 40 hours pulling and reconciling data, the team now works from a central hub that aggregates inputs without a linear increase in manual effort.

Leadership stopped asking whether they could trust the numbers and started asking why the numbers moved, shifting conversations from basic verification to richer strategic debate and faster decisions.

The forecasting rhythm now scales with the company. As more accounts and more people contribute, the hub continues to aggregate inputs without adding friction or headcount.
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For a twenty-something-person company, Heron delivers near-enterprise functionality without the cost and complexity of building proprietary systems, making it a pragmatic alternative to an internal BI platform.

Heron reduced that hidden salary drain and redirected human time toward analysis and client work.

More than automation, a shift in meeting quality

Time savings alone would be valuable, the deeper win was a qualitative change in how leadership used data. With a trusted source of projections and better drill-downs, meetings became strategic sessions. Executives were able to test hypotheses, identify revenue drivers, and make choices about expenses with more clarity. Rich highlights the difference, the team now focuses on insights and strategy, not data plumbing.

That roadmap, moving from high-level projections to rich historical and drill-down analysis, was a major reason Rich felt confident about the partnership.

Why Heron stood out, a custom fit for a small company

What differentiates Heron, according to Rich, is customization. Generic off-the-shelf tools are built for broad use cases; Heron took time to learn Enrich’s business and build capabilities that matched their workflow.

That bespoke approach lets small companies access enterprise-grade capabilities without the capital or engineering lift required to build a custom solution. Rich’s practical advice: give Heron three to six months to build something tailored—the odds, he argues, are high that a small company will be pleased with the result.

Community ripple effects, analytics that strengthen the local economy

Rich draws a line from better analytics to broader community benefits. When local businesses can analyze data and make intelligent decisions, they grow, hiring people, spawning leaders, and strengthening the local economy. 

In Rich’s view, smarter analytics is not just a company-level advantage, it’s a civic win that helps the whole ecosystem.

Closing endorsement

He reiterated that the current implementation was only the beginning and expressed excitement about product evolution and future capabilities.