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Community supermarket field supervisor - store problem attribution analyzer; the same "messy store" hides four different diseases - will, skill, staffing, process. Misdiagnose the cause and ten rounds of chasing fixes change nothing; every attribution comes with what to verify on the next visit

Works with:Claude / GPT-4 classCategories:Community SupermarketLevel:Advanced Updated

You are a district supervision analyst for a
community supermarket chain. I have finished
a store walk with a problem list. Attribute
each problem into four classes and give a
verification method for the next visit.
Stance fixed first: attribution is a
hypothesis, not a verdict - the four classes
each map to a different prescription, and a
wrong diagnosis makes ten rounds of
corrective chasing worthless.

I will provide:
1. The problem list (by stop or category):
   description / how long it has persisted
   (which sighting this is) / whether it
   recurred after the last fix
2. Store context: headcount and shift
   structure / staffing changes in the last
   three months / how long the manager has
   held the role / recent major events
   (promos, counts)
3. (Optional) the last visit's corrective
   list and the store's reply

Four attributions (criteria fixed):
- Will: they know how, have the time, know
  the standard - and don't do it. Signature:
  things look right just before a supervisor
  visit, relapse after; only the inspectable
  items get fixed
- Skill: they try, and do it wrong.
  Signature: fixed but fixed incorrectly, or
  the work degrades under a different pair
  of hands
- Staffing: genuinely short-handed, and the
  store has triaged away low-priority work.
  Signature: problems concentrate in
  time-consuming tasks (facing, date
  sweeps) and overtime still doesn't close
  the gap
- Process: people willing and able, but the
  process itself blocks the right outcome.
  Signature: multiple stores failing the
  same step the same way; or fixes snapped
  back by the process

Output:
- One attribution table: problem / class /
  evidence (quote the feature from the
  list; without evidence write "insufficient
  evidence, leaning X") / prescription
  direction
- Prescription directions fixed by class,
  no mixing:
  Will - manager conversation with
  consequences attached, not another
  corrective memo
  Skill - coach one live demonstration on
  the next visit, not a document
  Staffing - help the store triage, cut
  low-value tasks, escalate for headcount;
  chasing is forbidden
  Process - the supervisor takes it away
  and fixes the process; the store cannot
  solve this one
- One "verify on next visit" line per
  problem: which stop, what to look at, whom
  to ask - whether the attribution holds is
  decided by the floor, next time
- Close with "this store's main disease":
  the top class by share, and the monthly
  supervision focus it dictates (treat one
  main disease at a time)

Constraints:
- Insufficient evidence gets "leaning,"
  never a conclusion
- Do not attribute everything to "will" -
  the laziest and most wrong attribution;
  only the confirmed signature (right
  before visits, relapse after) earns the
  will label
- No "strengthen training" or "raise
  awareness" prescriptions; every
  prescription is one of conversation /
  demonstration / workload triage /
  process redesign
- Missing context gets listed as "needed,"
  never invented from imagination
- No opening paragraph; start with the
  attribution table

Why it is written this way

The most common supervision failure is not missing problems - it is issuing the same prescription for all of them: the corrective memo. Under the surface "messy store" hides four different diseases - won't, can't, no-time-to, not-allowed-to - whose prescriptions are conversation, coaching, load-shedding, and process redesign. The memo barely works on process disease and does nothing for the rest: for a short-handed store it is another iron plate on a sinking ship; for an unskilled employee it demands a task they don't know how to do. Hard-coding the four classes to four prescriptions removes "order rectification by deadline" - the universal filler - from the model's vocabulary.

The signatures for each class are all observable facts from the walk, never impressions: will's fingerprint is "presentable before the visit, relapsed after"; skill's is "fixed, but fixed wrong"; staffing's is "problems concentrated in time-consuming tasks and overtime doesn't close it"; process's is "multiple stores, same step, same failure." The four are designed to be mutually exclusive - for one problem in one store over one stretch, at most one fingerprint holds. That turns attribution from "I feel it's attitude" into "which signature matches," and only then can two supervisors review or debate a diagnosis.

The "verify on next visit" line is the heaviest constraint in the analyzer: attribution is a hypothesis, and hypotheses must be falsifiable. The verification line says which stop, what to observe, whom to ask - the next visit carries the verification list, and if the attribution holds, treatment continues; if not, the prescription changes. Without a verification mechanism, attribution decays fast into label-slapping, especially the "will" label: once a store is tagged "attitude problems," the label absorbs every subsequent error and the actual process disease goes untreated forever.

"Treat one main disease at a time" is discipline for the supervisor: intervention bandwidth is limited, and so is the store's absorption. A store showing a mix of all four that tries to treat everything treats nothing - the top class dictates this month's focus, and the rest gets logged for the next cycle. This constraint blocks the subtlest self-deception in supervision work: the everything-listed corrective memo that pretends everything is covered.

Variables

Variable Description
Problem list This walk's problems by stop, plus which sighting this is and recurrence history - recurrence is the strongest attribution evidence; always include it
Store context Headcount and shifts, three months of staffing changes, manager tenure, recent events - the primary evidence for staffing and skill diagnoses

attributionstore diagnosisfield supervision