How to automate ERP, Excel, and Google Sheets reporting

Every Friday, someone at your company spends three to six hours downloading ERP CSV, pasting into Excel, merging CRM sales, fixing broken formulas, and emailing a report that is stale within thirty minutes. It is not lack of discipline—it is a manual process that does not scale when you add a branch, product, or channel. Automating reports does not require an enterprise data warehouse; it requires clear sources, rules, and recipients.

At Devson Labs we see the same pattern: CONTPAQi, Aspel, SAP Business One, Odoo, or vertical SaaS run operations, but the "official truth" lives in shared sheets maintained by one person. When they are out, leadership flies blind. The goal is not to kill Excel—it is to kill manual paste and conflicting versions.

Report inventory before automating

List every recurring report: who requests it, cadence, sources, critical fields, and decisions it enables. Prioritize by hours spent × error risk. A wrong overdue collections report hurts more than a delayed web traffic dashboard. Remove duplicates: many SMBs have three different sheets for the same sales pipeline.

• Report name and business owner (not only IT).
• Source systems and current extraction method.
• Definitions: billed vs accrued revenue? gross vs net pipeline?
• SLA: delivery deadline and acceptable delay.

Technical patterns that work for SMBs

Scheduled extraction: native connectors, APIs, nightly SFTP exports, or light RPA when no API exists (with audit). Transform: Power Query, Python scripts in Cloud Functions, or n8n normalizing dates, tax IDs, and cost centers. Load: Google Sheets or Excel Online as read layer; Looker Studio, Metabase, or Power BI for visuals. Distribution: automated email, Slack, or internal portal—always with visible last-updated timestamp.

An automated report nobody trusts is worse than a manual one everyone understands.

ERP + CRM + payroll integration without chaos

Most requested merge: sales vs billing vs collections. Define master keys (customer tax ID, order, invoice UUID). Map Mexican fiscal calendar differences (VAT, withholdings, payment complements). Do not mix currencies without documented exchange rates. Automate exception reconciliation: non-matching rows go to a review sheet with owner, not hidden.

1. Minimum data model: dimensions (customer, product, date) and facts (amount, quantity).
2. Quality rules: null fields, duplicates, outliers.
3. Frozen history: do not overwrite closed months.
4. Role-based access: finance sees margin; sales sees pipeline without sensitive costs.

Where AI helps (without hallucinating numbers)

AI should not compute tax totals without validation. It does help: draft executive commentary on weekly variances, flag anomalies ("collections dropped 30% in North region"), suggest leadership meeting questions, and classify "wrong report" tickets. Numbers come from SQL or APIs; AI only narrates verified data.

Security and compliance

Financial and payroll reports are personal and confidential under LFPDPPP. Use service accounts with least privilege, encryption in transit, logs of who exported what. Avoid ERP credentials in shared sheets. If using external AI, anonymize or aggregate before sending text to public models.

Realistic 8-week roadmap

Weeks 1–2: inventory and prioritization. Weeks 3–4: automate painful report #1 end-to-end. Weeks 5–6: dashboard and exception alerts. Weeks 7–8: documentation and business owner training. Only then tackle report #2. SMBs attempting ten reports at once end with none reliable.

Alerts leadership actually reads

A dashboard nobody opens is useless. Configure exception alerts: overdue collections above X pesos, gross margin below threshold, inventory below minimum, stuck pipeline. Send executive summary Mondays and immediate alert only when something breaches band. Less noise, more action.

Include in each alert: what happened, since when, source system, resolution owner. Without owner, the alert is just fancier noise.

Concrete tools by SMB size

Teams of 5–15 often start with Google Sheets + Looker Studio + n8n cloud: low cost, moderate curve. From 15–80 employees, Power BI or Metabase with ERP and CRM connector centralizes reports without duplicating sheets. Above 80, evaluate a light data warehouse (BigQuery, Snowflake) only if fiscal volume and complexity demand it—many Mexican SMBs overbuy infrastructure before mastering one automated report.

Train the business owner to read the dashboard, not SQL. Success is finance no longer being the Monday bottleneck.

If your team lives in Excel but data lives in silos, we connect them with automation and responsible AI. Start with an automation radiography to quantify recoverable hours. Fewer paste Fridays, more decisions with numbers that tie out.