Reporting, retention, automation and AI. Written from building it, not selling it.
Practical guides on making your own data useful. No gated PDFs, no email wall.
Most business reporting fails not because the data is wrong, but because nobody decided what the report is for. Here is how to pick the handful of numbers that actually change what you do this week.
Almost nobody fires you. They just order less, then later, then not at all. The signal is sitting in your order history, and it is boringly easy to detect once you decide to look.
Most disappointing AI projects in small businesses fail for an unglamorous reason: the model was asked a question the data could never answer. Here is the order of operations that works.
A straight capability map, with the failure modes named. Useful if you are trying to work out which of the things you have been promised are real.
Late payment is mostly an admin failure, not a relationship problem. A dull, consistent, automated chase sequence collects more than an awkward phone call three months late.
Before you plan any automation or reporting project, it is worth knowing what your systems will and will not give you. Here is how to check in an afternoon, without being technical.
A ranking method that takes an afternoon and stops you automating the wrong thing. Most businesses pick by irritation, which is a poor guide to value.
You don't need to know how it gets built. You do need to be precise about six things — and being vague about them is what makes projects overrun.
You do not need a data scientist to stop running out of your bestseller. You need cover, cadence and a small amount of honesty about seasonality.
Double entry between systems is the most common hidden cost in a small business, and the easiest to remove. It's also where the errors come from.
Tell us the job that keeps not getting done. We'll tell you if software can take it off you, and what it costs.
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