About ten years ago, I was having lunch with a B-school classmate, talking about Power BI and Tableau and how they were remaking so much of the work we were both doing at the time. He was farther along on his data analytics journey than I was, and at some point in the conversation he used the term “small data.” It stuck in my head.
When I later went looking for a definition, I found one from analyst Allen Bonde that has stayed with me ever since:
“Small data connects people with timely, meaningful insights (derived from big data and/or ‘local’ sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.”
The work I do with small and mid-sized businesses deals almost exclusively with small data, and that’s by design:
- Actionable and understandable come at a premium. For an SMB, an insight the owner can’t act on — or can’t explain to their team — is worthless, no matter how sophisticated the analysis behind it.
- Big data favors big infrastructure. The term itself implies large-scale data systems, storage, and tooling that my clients don’t generally have — and which I have no interest in selling them.
- Decision cadence matches the data. SMB decisions get made monthly or quarterly: pricing, staffing, inventory, cash. Real-time pipelines add cost and complexity without changing a single decision.
- My clients keep ownership. Small data lives in tools they already have and understand. When my work is done, they can open the file, trace any number back to its source, and maintain it themselves — no data team, no vendor dependency.
In practice, I follow a few ground rules for what small data means for my clients:
- Scaled to desktop tools. Everything fits naturally into MS Access, Excel, and Power BI — software my clients already own and use every day.
- Point-in-time snapshots, not live feeds. Data is refreshed on a deliberate cadence, which keeps things simple, auditable, and inexpensive.
- Monthly granularity by default. Most SMB decisions are made on a monthly rhythm; where it makes sense, we go daily — but never more granular than the decision requires.
Ten years on from that lunch, the tools have changed — but the idea has only gotten more relevant. Most SMBs don't have a data problem; they have a usable data problem. The numbers they need are already sitting in their invoices, their payroll, their point of sale, their accounting system. My job is to shape them into something an owner can open on a Tuesday morning, understand in five minutes, and act on by Friday.