When the numbers don't agree, the problem is never the dashboard.
We rebuild the foundations, give the business one clean way to read itself, and pair it with AI chat that goes deeper on the same definitions. Reviews run on numbers everyone trusts, and the follow-up question gets answered in the same sitting instead of next sprint.
What we usually walk into.
One read of the business, and a chat that goes deeper.
The dashboard explains movement: if orders are down 123, every one of the 123 is accounted for. The chat answers the follow-up in the same sitting, from the same definitions, so the two never disagree.
Illustrative example.
Analysis that gets ahead of the big calls.
Reporting keeps the business honest week to week. The larger value is embedded analysis on the decisions that set the year, done with the rigor a decision that size deserves.
Foundations, then trust, then decisions.
Analytics and the engineering under it, as one system. You do not need all of it, and almost nobody starts with more than two. Everything lives in your repo and your warehouse, so it is yours whether or not we are around.
A number that moved is not a finding.
Every metric that moves gets the same treatment: what moved, the initial hypo, what is being done and who owns it. That discipline is what ends war rooms over noise. When everyone knows what normal variance looks like, a real change stands out on its own.
Initial hypo: ~$80k overspend on premium TV inventory, offset planned this week with lower spend. Conversion and mix are flat, so this is a cost story, not a demand story.
+30% topline and EBITDA in the first year on the rebuilt measurement, after two years flat.
A DTC brand stopped making budget calls off platform ROAS, rebuilt the measurement under one set of definitions, and moved spend it could finally defend.
Read the studySizing a loungewear whitespace before the budget committed, not after.
Category and audience data pointed at an opportunity the roadmap was about to walk past. The analysis put a defensible range on it first.
Read the studyFrom Google Sheets to thousands of orders a day, with cancellations down ~35%.
Complex fulfillment ran on semi-manual sheets that broke a little every day. We automated the backbone across NetSuite, Salesforce, and the 3PLs, and kept people on the steps where customers feel the difference.
Read the studyMore studies are being written up. If the situation you are in looks like one of these, the fastest way to see the detail is to ask.
Get in touch.
Tell us what you are trying to figure out. If we can help, we will say how. If we are not the right fit, we will say that too, and point you somewhere better.