It is Thursday. The partner employers want a spring-cohort summary by Monday, the board chair has asked what changed, and the delivery manager has to decide whether the practice session goes into the next course. From lesson 5 you have the finding: 15 of 25 respondents used the skill at work within 30 days, and 15 of the 40 completers are unknown. Now it becomes a report someone can check, and the course becomes a pilot for next cycle.

Why do reports stall on the usual paths?

In short: The report is where scattered data gets its last chance to be reconciled, and there is rarely time. A fluent paragraph with no path back to the records falls apart when someone asks “which learners?”

On the most common path, someone exports the follow-up survey to Excel, pastes it into ChatGPT and asks for a summary. The draft reads well, but nobody can see which rows produced “60%”, the same file pasted twice can give two answers, and learner names have travelled into a chat window. A CRM with AI bolted on counts registrations but never connected the survey comments and mentor notes. A warehouse shows the number, and “what stopped the other ten?” goes back to a spreadsheet. Either way the team spends the week reconciling instead of deciding.

What goes in a report brief?

In short: Six lines: audience, decision, period, evidence required, detail allowed, and coverage and unknowns. Write it before any narrative, and separate what the reader requires from what you guess they want.

“Provide a 30-day follow-up result” in a partner agreement is a requirement. “They probably want a success story” is a guess to check. Design changes how a report looks, never its denominator or who may see a quote.

How does every claim point to a record?

In short: Write the finding in four sentences (result, coverage and timing, limitation, action) and attach to each claim the record it came from, its coverage and what is unknown. If a reviewer can’t open the source in one step, the claim isn’t ready.

The talk sets the standard with one question: “Who did the staff checkbox miss?” The answer names three learners flagged at risk in week 12, and each ID links to its record: a mid-program survey, a mentor note, an exit survey. County data, loaded as a public survey, follows the same rules. A report should work the same way.

Behind it sits a claim-and-source table, the part of the brief a reviewer reads first.

The last row is Maria: confidence 2 out of 5 at intake and 4 at exit, 10 of 12 sessions, a mentor who saw her lead a mock interview, and skill use on the job at 30 days. Because every piece carries ID 0417, checking it took minutes, not an afternoon of matching names across three tools. When the report is a longer narrative for a funder, with quotes to choose and permissions to confirm, use the deep dive on writing a cited funder narrative and bring back its claim-and-source table.

How do you review a report before you share it?

In short: Let AI draft from evidence you’ve already checked, then have someone who didn’t write the draft open every source, recompute every number and confirm every quote may be shared. A second AI pass can spot problems; it isn’t sign-off.

Using only the records and tables I have shared, draft a one-paragraph finding for [audience] about [decision].
Include the result with its numerator and denominator, response coverage, the time window, one limitation and the next action.
Rules: cite the record or table for every number. Do not claim the course caused the result. Report non-response as unknown. List anything the report needs that the evidence does not contain.

Five checks before a report leaves the team. The change log is a team practice, kept wherever your team keeps decisions.

Be honest about what review can’t settle. These are self-reports from 25 of 40 people, and the 15 who didn’t reply may differ. A 30-day checkpoint shows use at day 30, not lasting change, and showing the course caused it would need a comparison group. A link proves where a sentence came from, not that its interpretation is right. People decide what the finding means; AI helps find the records and draft the words.

What does one governed record look like in practice?

In short: Open Play Foundation runs four sports facilities in Stellenbosch, South Africa, covering coaching, water infrastructure and food security. On one governed record, ten program reports became one funder submission.

The second result matters as much as the first. A water leak surfaced in real time because the data was connected. When collection is governed from the first form, reporting stops being a scramble at the end of the year and becomes something the team notices during it. The organization’s CEO put it this way: “I’m digitizing our entire business through Sopact.”

How do you choose a workflow and run a pilot?

In short: Start with one form you already run, decide which fields AI may see, and add the next workflow when that one is working. A pilot is one question, one cohort, one owner and a review date.

The training team doesn’t rebuild everything. It starts with the registration form it already runs, so each learner gets an ID at the first form. Names, emails and phone numbers stay out of what AI sees; confidence scores, barrier answers and mentor notes go in. Once registration works, the exit survey and 30-day follow-up join the same ID. Nothing needs merging later, because the record was connected when it was collected.

If the next cohort’s rate is higher, that is encouraging, not proof: the groups and response rates differ, and the report should say so.

How do you test a tool before the pilot?

In short: Run the six checks from lesson 2 again with your report question, on any tool, ours included. A good answer names the records behind it, shows coverage, and gives the same result when you ask twice.

In Sopact Sense, each person gets a persistent ID at the first form and later workflows join that record. Each team works in its own folder, the AI Assistant stays locked until you pick its surveys, you choose which fields are sent to AI, and every line of an answer links to a record you can open. Claude or ChatGPT can query the same data through MCP. A shared place for definitions and frameworks is coming soon. Run the six checks on it as you would on anything else.

Which workflow course should you take next?

In short: Pick the course whose records and decisions look most like yours, and carry this plan into it rather than starting new documents.

Training, partners, portfolios and more have their own courses. See all workflow courses.