Examples of retail channels. Logos identify their respective brands; this display does not imply a Fundle partnership, endorsement or certified integration.
“Which outlets are below target after adjusting for reporting coverage?”
Fundle Brain
01
Receive the partner file
Identify the partner, reporting period and layout. Keep the original file reference so an imported record can always be traced to its source.
02
Apply deterministic checks
Validate required fields, numeric values, dates, duplicates and master mappings. Route uncertain records to the exception queue.
03
Build comparable reporting
Align store sets and periods before calculating year-on-year or like-for-like changes. Separate sales, returns and stock measures.
04
Turn the finding into a partner action
Use target gaps, article performance and stock-cover questions to prepare a focused discussion with the partner or regional owner.
BUILT AROUND THE WORK
Make partner data usable before asking it questions.
A multi-brand outlet or shop-in-shop network rarely sends one clean reporting format. Fundle’s MBO workflow uses defined recognition and validation rules to standardise partner files, preserve their origin and build a consistent secondary-sales view.
01
Partner-file ingestion
Recognise known layouts and map sales and stock columns to a common structure. Retain partner-specific identifiers alongside standard article and store masters.
02
A visible exception process
Flag unknown mappings, invalid rows and uncertain records for review. Keep accepted and unresolved data distinct so a reporting total does not conceal ingestion problems.
03
The commercial hierarchy
Analyse partner, region, store, category and article performance. Bring targets, stock cover and margin context into the comparison where those inputs are available.
04
Read-only business questions
The documented conversational reporting approach works over validated records. Source rows, versions and correction history remain the basis for checking answers and authorised adjustments.
THE OPERATING FLOW
From the first question to the next useful action.
Different partners call the same field different things. Before comparing outlet performance, the workflow standardises formats, flags uncertain rows and preserves the link back to each source file.
01
Receive the partner file
Identify the partner, reporting period and layout. Keep the original file reference so an imported record can always be traced to its source.
02
Apply deterministic checks
Validate required fields, numeric values, dates, duplicates and master mappings. Route uncertain records to the exception queue.
03
Build comparable reporting
Align store sets and periods before calculating year-on-year or like-for-like changes. Separate sales, returns and stock measures.
04
Turn the finding into a partner action
Use target gaps, article performance and stock-cover questions to prepare a focused discussion with the partner or regional owner.
BRING YOUR BUSINESS QUESTION
Give Fundle Brain something useful to work on.
Start with the question. Define the data and workflow needed to answer it.
↗Which outlets are below target after adjusting for reporting coverage?
↗Where is stock cover high while article sales are slowing?
↗Which partner files contain unresolved article or store mappings?
CONNECT
Start with the right data.
Partner sales and stock files, store hierarchy, SKU masters, targets, commercial schemes and reporting periods.
PUT IT TO WORK
Leave with a useful output.
Validated secondary-sales views, exception queues, stock-cover analysis and conversational answers.
Read file acceptance, record completeness and unresolved exceptions alongside target attainment, sell-through and stock cover. Distinguish an operational data gap from a commercial performance gap.
GOOD QUESTIONS
Before we get started.
Does AI automatically correct partner financial data?
Corrections follow deterministic validation and a review process. Conversational analysis works over reporting data; financial changes require explicit authorised action.
What happens when a partner changes its spreadsheet?
The layout needs to be recognised and mapped before its records enter the standard reporting view. Unknown or ambiguous fields should be reviewed rather than silently guessed.
Can the team check an AI explanation?
The reporting approach preserves source-row and version context. Validate material answers against the selected period, store set and underlying records; the assistant is not a financial correction engine.
