Reporting Assessment v2.0.0
reporting · 8 sections
Metadata
Scales, categories & audiences
Scales: none · Categories: none · Audiences: business technical
Edit these in the raw JSON editor below — they change rarely and carry structure (levels, signals, deep-dive wiring) that a form would mangle.
1 · Your Business & What It Needs business
Commercial context before systems — what data needs to DO here.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| business_1_in_your_own_words | In your own words — what does this team do, and what makes it genuinely different from a competitor? | verbatim | — | — | |
| business_2_the_three_most_important | The three most important decisions in your area each week/month — who makes them, on what information? | verbatim | — | — | |
| business_3_who_are_your_most | Who are your most important 'clients' (internal or external) and what do they expect from your data & reporting? | verbatim | — | — | |
| business_4_what_would_have_to | What would have to be true about your data for your team to feel genuinely confident in the numbers? | verbatim | — | — | |
| business_5_is_there_a_business | Is there a business question you're asked that you can't answer — or that takes too long? | verbatim | — | — | |
| business_6_questions_referencing | [BU-specific] 1–2 questions referencing this business's market / commercial model / known challenges | verbatim | — | — |
＋ Add question to “1 · Your Business & What It Needs”
2 · Your Reports, Day to Day reports
Map the current reporting environment — what exists, who uses it, what it costs, what fails.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| reports_1_the_report_you | The report you couldn't do your job without — what does it tell you, who else depends on it? | verbatim | — | — | |
| reports_2_which_report_takes_the | Which report takes the most manual effort each week/month? Walk me through the steps — what can't be automated? | verbatim | — | — | |
| reports_3_is_anyone_the_only | Is anyone the only person who knows how to run a particular report? What happens when they're away? | verbatim | — | — | |
| reports_4_how_do_reports_reach | How do reports reach the people who use them — email, shared drive, dashboard? Is that working? | verbatim | — | — | |
| reports_5_any_reports_you_run | Any reports you run out of habit that probably nobody looks at anymore? | verbatim | — | — | |
| reports_6_how_long_from_data | How long from 'data exists' to 'report in the right hands'? Where does the time go? | verbatim | — | — |
＋ Add question to “2 · Your Reports, Day to Day”
3 · Data You Can't See shadow
Surface shadow reporting without putting anyone on the defensive — it's normal, we just need the scale.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| shadow_1_reports_or_extracts_produced | Reports or extracts produced in Excel / outside the main systems that IT may not see? (very common) | verbatim | — | — | |
| shadow_2_decisions_made_on_data | Decisions made on data that isn't from the official reporting system — where's that data from? | verbatim | — | — | |
| shadow_3_when_someone_needs_a | When someone needs a number quickly and the standard report isn't fast enough, what do they do? | verbatim | — | — |
＋ Add question to “3 · Data You Can't See”
4 · Definitions & Consistency definitions
Get people to name the inconsistencies rather than discover them mid-engagement.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| definitions_1_when_you_say | When you say [key metric], what does it actually mean here? How is it calculated? | verbatim | — | — | |
| definitions_2_if_another_reported | If another team/brand reported the same metric, would it be calculated the same way? Do you know if it is? | verbatim | — | — | |
| definitions_3_that_mean_something | Terms/metrics that mean something specific to your team but differ for finance or another part of the business? | verbatim | — | — | |
| definitions_4_when_a_report_shows | When a report shows a surprising number, how is it resolved? Who decides which number is 'right'? | verbatim | — | — | |
| definitions_5_how_do_you_handle | How do you handle two reports showing different numbers for the same thing? | verbatim | — | — |
＋ Add question to “4 · Definitions & Consistency”
5 · Data Governance govern
Probe whether governance actually happens or just exists on paper — directly, without judgement.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| govern_1_who_owns_the_key | Who owns the key metrics in your area — a named person/team for definitions, quality, accuracy? | verbatim | — | — | |
| govern_2_when_data_quality_goes | When data quality goes wrong (wrong figures, broken feed), how is it caught? By whom? How long? | verbatim | — | — | |
| govern_3_how_are_access_controls | How are access controls managed for your reports — who sees what, is it maintained? | verbatim | — | — | |
| govern_4_for | For client-facing data: what's the process if a client disputes a figure? | verbatim | — | — | |
| govern_5_any_regulatory_contractual_or | Any regulatory, contractual or privacy obligations affecting storage/access/reporting? (APRA, Privacy Act, client contracts) | verbatim | — | — |
＋ Add question to “5 · Data Governance”
6 · Looking Forward forward
Future-state aspirations — and a non-salesy way into the AI/Copilot conversation.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| forward_1_if_you_could_type | If you could type a question in plain English and get an immediate answer from your data — what's the first question? | verbatim | — | — | |
| forward_2_if_you_could_redesign | If you could redesign how report output reaches people from scratch, what would it look like? | verbatim | — | — | |
| forward_3_a_scenario_where_the | A scenario where the system could flag something automatically before a human looks — what would it flag? | verbatim | — | — | |
| forward_4_what_would_reporting | What would 'self-service reporting' need to look like for your team to actually use it? | verbatim | — | — | |
| forward_5_with_trusted_current | With trusted, current, easy-to-get data — what's the first thing you'd do differently? | verbatim | — | — | |
| forward_6_any_ai_tools_your | Any AI tools your team already experiments with (Copilot, ChatGPT)? Reaction to AI for data questions? | verbatim | — | — |
＋ Add question to “6 · Looking Forward”
7 · The Group Picture group
Multi-entity only — ask at a cross-brand session or add per BU and compare.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| group_1_compared_to_another | Compared to another brand's numbers (headcount, placements, revenue) — do the definitions match? What conversations would need to happen first? | verbatim | — | — | |
| group_2_what_does_the | What does the parent/group ask you to report up — format, frequency, detail? | verbatim | — | — | |
| group_3_if_the_group_could | If the group could see one consistent metric meaning the same thing everywhere, what should it be? | verbatim | — | — | |
| group_4_cases_where_brand_figures | Cases where brand figures don't quite make sense together — what's usually the explanation? | verbatim | — | — | |
| group_5_a_consolidated_view_across | A consolidated view across all brands on one screen — what's the first thing you'd want to know? | verbatim | — | — |
＋ Add question to “7 · The Group Picture”
Technical / Architecture session tech · audience: technical
IT/data team audience (Pedro-led). Maps current state: systems, integrations, infrastructure, pain points, future state.
| Id | Question | Type | Category | Scale | |
|---|---|---|---|---|---|
| tech_1_full_list_of_source | Full list of source systems feeding the warehouse — and how the data actually gets there? | verbatim | — | — | |
| tech_2_per_integration_method | Per source: integration method (API/DMS/SSIS/flat file), who controls it, refresh frequency? | verbatim | — | — | |
| tech_3_source_systems_you_lack | Source systems you lack good visibility of — fragile or poorly documented? | verbatim | — | — | |
| tech_4_walk_me_through_the | Walk me through the warehouse architecture — layers and what happens at each? | verbatim | — | — | |
| tech_5_how_many_etl_jobs | How many ETL jobs, roughly? How monitored & maintained? Where does ETL fail most, and recovery time? | verbatim | — | — | |
| tech_6_reporting_stack_tools | Reporting stack — tools, who uses each, how connected to data? Report inventory & subscriptions management? | verbatim | — | — | |
| tech_7_hosting_cloud | Hosting — cloud / on-prem / hybrid? Separate dev environment? Source control & change management? | verbatim | — | — | |
| tech_8_access_control_compliance_obliga | Access control, compliance obligations, and any data quality / lineage gaps you're not confident about? | verbatim | — | — | |
| tech_9_if_you_could_redesign | If you could redesign the platform from scratch — keep / throw out / add? Discussions about Fabric or self-service? | verbatim | — | — |
＋ Add question to “Technical / Architecture session”
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Advanced — raw JSON
Full pack document, validated on save (schema yarn-pack/2). This is where scales, audiences, structured conditions and adaptive config live.