Every decision,
with its story.
Made, under review, rejected, revised. Each with who made it and when, the tags, and a mark on those already implemented. You search, filter, open.
The why,
not just the what.
“Develop our own digital made-to-measure”: what was decided, why — the new habits of younger customers —, the context, the evidence taken from the project’s research with its source, the risks, and the alternatives: those considered and those rejected, which stay on record as the “why not”.
Write the decision.
MAPS finds the evidence.
Title, what, why. Then “Find evidence”: MAPS searches the project’s research for what supports the decision — with the source. And “Suggest risks & alternatives”: it infers them from that evidence, without inventing facts. You keep, discard, add.
Here, for a loyalty program for made-to-measure customers, MAPS flags the privacy risk on measurement data and proposes an alternative: an annual subscription for styling and tailoring check-ups.
Already have the minutes?
MAPS extracts the decisions.
You upload the meeting minutes — PDF, Word — or paste them. MAPS pulls out the decisions, each with its status: made, postponed, rejected. You deselect the ones you don’t want, and the others become editable, searchable decisions.
From four-point minutes: the Christmas social budget (made), the pop-up in Milan (postponed), the loyalty program (made, assigned to the CRM team), TikTok (ruled out for the year).
From a decision,
a plan with dates and names.
Every decision can become an operating plan: the decision is the objective, and “Generate with AI” proposes the Key Results — measurable, tied to the project’s evidence. Each one gets an owner, a deadline and a progress status. The plan copilot edits it in plain words: “move KR 2 to the end of August and assign it to the digital team”.
All the plans,
over time.
The Matrix puts plans in the rows and months in the columns; the Gantt shows each Key Result as a point on its line. You see at a glance what’s due when, and where plans overlap.
Ask your plans.
Even to change them.
“What’s due by the end of the year, and who owns the most Key Results?” The copilot reads all the plans and answers. And if you ask it to push one back by a month, it proposes the changes: you apply them only after you’ve seen them.
An alternative
can become a plan.
On an alternative that was considered, MAPS analyzes consequences and implications starting from the evidence. If it’s worth it, it becomes a linked plan — “start a partnership with a 3D configurator provider” instead of building one — and when you choose the path you mark it as implemented. The Plan map shows what derives from what.
Six months from now,
ask the chat.
Every decision and every plan goes into the project’s AI chat. “Why did we rule out TikTok?”, “where are we with the digital made-to-measure plan?”: the answer comes with the reasoning, the evidence and the alternatives considered — and when a choice is revisited, you start from there instead of from scratch.