Program · Small businesses
Lightweight Data & Reporting with AI Tools
A hands-on program for small businesses that want clear, simple reporting – built on the tools you already use – with AI helping summarize and analyze, not replacing your judgment.
We'll connect your existing tools, exports, and spreadsheets into a small reporting setup, then layer AI on top to explain what's happening, highlight trends, and surface questions worth asking.
Program overview · Audio
A short overview of the program: who it's for, what we cover, and how to get the most value out of it as a busy professional.
What your business will be able to do after this program
Less “we have data everywhere,” more simple, repeatable reports and clear explanations of what they mean.
- • Know where your key numbers live and how to pull them without a fire drill each time.
- • Maintain a few simple reports that owners and teams actually read and understand.
- • Use AI to summarize, compare, and sanity-check reports in clear language.
- • Spot basic trends and questions without hiring a full data team or buying heavy BI tools.
- • Run a light reporting cadence that fits your size and stage.
Who this is for
- • Owners and ops/finance leads who want more visibility without a huge project
- • Small teams piecing together exports from accounting, CRM, and ops tools
- • Businesses that feel “data-rich but insight-poor” and want a realistic start
What you'll work on
- • Your actual numbers: revenue, pipeline, ops, delivery
- • Reports your team wants to see regularly
- • AI workflows that help interpret the data you already have
Curriculum at a glance
Four modules to go from scattered exports to simple reporting with AI as a helper.
Module 1
Finding and cleaning the data you already have
- • Inventory where your key numbers live today (tools, exports, spreadsheets)
- • Decide which data is “good enough” vs. what needs fixing
- • Create a simple, repeatable way to pull data for reporting
Module 2
Designing simple reports that people actually read
- • Choose a small set of views: owner, ops, and team-level
- • Lay out reports so the main story is obvious in minutes
- • Avoid chart overload: where visuals help and where they don’t
Module 3
Using AI for summaries, insight-finding & QA
- • Use AI to turn exports into plain-language summaries
- • Ask AI to highlight trends, anomalies, and questions to ask
- • Use AI as a second set of eyes to sanity-check numbers
Module 4
Rhythms, ownership & continuous improvement
- • Define who owns which report and when it’s updated
- • Set a realistic reporting cadence (weekly/monthly/quarterly)
- • Keep a small backlog of report tweaks and new questions
1. Finding and cleaning the data you already have
Before buying anything new, we make the most of the data and tools you already pay for.
We start by mapping where key numbers currently live: accounting, CRM, payment processors, spreadsheets, and internal tools. Then we decide what's “good enough” to use and where we need basic cleanup.
- • Inventory data sources and exports you already have
- • Identify a few key tables/views to reuse
- • Decide on a simple file naming and storage pattern
- • Clarify who can pull what, and how often
Data map & pull checklist
You’ll leave this module with a short, practical map:
- • List of key sources (tools, exports, sheets)
- • What each one is used for in reporting
- • Who pulls it and where it’s stored
2. Designing simple reports that people actually read
If a report doesn’t change decisions, it’s decoration. We focus on views that owners and teams will look at regularly.
Next, we design 2–4 simple reports. Each has a clear owner, a specific audience, and a small set of metrics or views. Think “owner snapshot,” “ops weekly,” or “marketing basics.”
- • Decide on audiences and questions each report serves
- • Choose the metrics and dimensions that belong
- • Lay out tables and charts for quick scanning
- • Avoid dashboard sprawl and vanity metrics
Report blueprints
We’ll sketch report blueprints for your key views, including:
- • Purpose, audience, and cadence
- • Core metrics and comparisons (e.g., vs. last month)
- • Where the data comes from and how it’s updated
3. Using AI for summaries, insight-finding & QA
Let AI help explain what’s happening, not just generate charts you don’t need.
Here we connect AI to your reports: using exports or structured snippets, we ask AI to summarize, compare, and highlight potential issues — and we treat its output as a starting point for human judgment.
- • Format data so AI can interpret it sensibly
- • Use prompts that ask for summary, risks, and questions
- • Sanity-check AI’s take against your own intuition
- • Use AI to check for obvious inconsistencies or missing data
Reporting prompt pack
You’ll create a small prompt pack you can reuse every reporting cycle, such as:
- • “Summarize this report in 5–7 bullet points.”
- • “What changed the most vs. last period?”
- • “List 3 questions I should ask my team about this data.”
- • “Highlight anything that looks inconsistent or surprising.”
4. Rhythms, ownership & continuous improvement
Simple reporting only works if someone owns it and it fits into the week or month.
Finally, we make the whole thing sustainable: who owns each report, when it’s updated, how AI fits into the process, and how you’ll tweak reports as your questions evolve.
- • Assign owners to each report and data pull
- • Define realistic cadences (weekly, monthly, quarterly)
- • Plan a short review ritual for key reports
- • Keep a backlog of “future improvements” and new views
Reporting playbook
You’ll leave with a lightweight reporting playbook that includes:
- • Who updates what, when, and how
- • How AI fits into your reporting workflow
- • A simple checklist you can follow each cycle
Format & logistics
Built for teams that want better reporting without turning it into a full-time job.
Schedule
- • 3–4 weeks total
- • Weekly live working sessions (60–90 minutes)
- • Light data and report work between sessions
Team
- • 2–6 participants
- • Typically: owner/GM + ops/finance + a “numbers-friendly” IC
- • Private cohorts per business
What you leave with
- • 2–4 simple reports your team actually uses
- • A reporting prompt pack for AI summaries & insights
- • A clear cadence and ownership model for reporting
FAQ: Lightweight Data & Reporting with AI Tools
Questions small teams usually ask before investing time in better reporting.
Do we need a data warehouse or BI tool before this?
No. This program is explicitly designed for teams using a mix of core tools (accounting, CRM, ops platforms) and spreadsheets. If heavier tooling becomes obviously worth it, we'll note that — but it's not the starting point.
How much does AI actually do vs. humans?
AI helps with summaries, comparisons, and spotting patterns or questions. Humans still own the interpretation and decisions. We avoid prompts that ask AI to “decide for you” and instead use it as a thinking and writing partner around the numbers.
What if our data is messy or inconsistent?
That’s normal. Part of the work is deciding what level of “good enough” you can live with for each report. We’d rather ship a slightly imperfect but honest report than chase perfection and never get to a usable rhythm.
Will this replace our accountant or bookkeeper?
No. This program sits on top of the financial and operational work you're already doing. It helps you turn that work into clearer, more actionable reporting — and use AI to understand and communicate what's going on.
Ready to turn scattered data into clear, simple reporting?
This program helps you build a lightweight reporting setup and plug AI in where it's strongest — summarizing, explaining, and helping you see what matters — without overbuilding a data stack.
If you’d like to pair this with Owner Dashboard or AI Assistant Stack, mention that in your note and we'll suggest a track that fits your stage.