NOGL

Demand planning

See the assumptions behind the next buy.

Compare sales history with a possible next season. Keep the planning paths, their assumptions and the missing evidence in one buyer review.

Prepared local example · assumed planning paths

Explore the planning exampleDiscuss your planning inputs

Units per week

Weekly history and assumed planning paths · PLAN-J01Solid historical sales, a dashed central assumed path, a shaded assumed range and a selected-week marker. The cutoff divides H0 from W1. All numbers are also in the tables below.08162432CutoffH−3H0W1W2W3W4
Recorded sales · units/weekCentral assumptionAssumed lower–upper paths

Original NOGL illustration using Jacket / PLAN-J01 base data. Every record is fictional; no model is running.

Know where the history ends.

A sales record and a planning assumption answer different questions. Keep their boundary visible before interpreting a curve.

  1. 01

    Observed sales

    Four fictional weekly sales records end at H0. Recorded sales do not establish unconstrained demand.

  2. 02

    Planning assumptions

    W1–W4 are hand-prepared possible paths. They are not a model prediction or a purchase plan.

  3. 03

    Evidence to review

    Stockouts, event effects, validation and supply timing require separate evidence before a real buying decision.

Prepared local example · assumed planning paths

Explore one product, one planning question.

Switch the product, assumption or week. The chart, numbers and review note stay together; your choices change only this local example.

Base: four prepared future weeks with no event addition.

Units per week

Weekly history and assumed planning paths · PLAN-J01Solid historical sales, a dashed central assumed path, a shaded assumed range and a selected-week marker. The cutoff divides H0 from W1. All numbers are also in the tables below.08162432CutoffH−3H0W1W2W3W4
Recorded sales · units/weekCentral assumptionAssumed lower–upper paths

Lower and upper paths are authored assumptions without probability or established calibration. They are not forecast quantiles or a confidence interval.

Jacket PLAN-J01

Selected week · W1

Lower
8
Central assumption
12
Upper
18

Assumed · Units per week

Illustrative period H−3 through H0. W1 starts after the cutoff; these labels do not refer to the current date.

Fictional sales records before the cutoff · SALES-J01
RecordedH−3H−2H−1H0
Units sold9111012
Prepared planning paths after the cutoff
PathW1W2W3W4
Lower8101210
Central assumption12141614
Upper18222420

See exactly what the assumption changes.

Compare the base and selected central paths week by week. The event scenario changes W2 and W3, while history and the other weeks stay fixed.

Base · sum of weekly central assumptions
56
Selected · sum of weekly central assumptions
56
Difference in central sums
0
See exactly what the assumption changes.
WeekBaseSelectedDifference
W112120
W214140
W316160
W414140

This sum is not an aggregate forecast quantile, measured demand or a purchase quantity. The example demonstrates no causal effect or model improvement.

Keep the inputs beside the plan.

These source cards describe the fictional records, not a connected store. Missing evidence remains missing under every selection.

Review weather context
Sales record · SALES-J01
Fictional weekly item counts for the selected product; returns and stockout adjustments have not been supplied. Illustrative period H−3 through H0. W1 starts after the cutoff; these labels do not refer to the current date.
Unit basis
History counts units sold per week. Future values are assumed units per week, not unrestricted customer demand.
Declared assumption
Base: four prepared future weeks with no event addition.
Validation
No realized future outcomes, holdout data or calibration assessment is supplied.

Fictional weather-context example

Check weather context before changing a plan.

A weather observation describes a past period. A forecast was issued for a future valid period. Compare their location and timing before treating either as planning context.

Discuss the required sources and validation with the responsible team. This illustration does not approve a purchase, change a forecast, send an alert or execute an order.

Choose a review window.

This separate fictional example uses one Berlin store, two calendar windows and a fixed review cutoff. It does not change the assumed demand curves above.

Review location
Fictional Berlin store (STORE-BER-01)
Fixed review cutoff

6 October window: → · Europe/Berlin

Read the original record.

Inspect the record kind, source version, location, unit and value. A requested record without evidence remains unknown. No weather service is connected.

Record to inspect
R02
Record kind
Forecast
Source location
STORE-BER-01
Illustrative daily mean temperature
8
Metric
Illustrative daily mean temperature
Unit
°C
Source document ID
FX-WX-R02
Fictional source reference
fixture:weather/r02
Fictional provider
Fictional Weather Notes
Source version
v1
Value provenance
FX-WX-R02
Later version of
Not applicable to this record kind

Authored example; not a live weather observation

Separate issue time from valid time.

Keep the time a forecast was issued separate from the period it describes. A later revision was not available at an earlier review cutoff.

Record time

Forecast issued at
Observation recorded at
Not applicable to this record kind

Valid interval

Valid from (inclusive)
Valid until (exclusive)
Time zone
Europe/Berlin

Check every mismatch.

A different location, an unmatched window or a missing issue time prevents this example from establishing comparable context. Even an aligned record is not a validated demand signal.

  • Location, valid window and issue time align with this illustration. This establishes context only, not demand impact or approval.

Hourly timeline (fictional)

The same window, hour by hour.

Authored values for one location. Each hour shows its valid time; no forecast is issued or updated here. · 6 October window · STORE-BER-01

  1. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 9 °C
  2. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 8.6 °C
  3. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 8.2 °C
  4. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 8 °C
  5. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 7.8 °C
  6. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 7.6 °C
  7. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 7.9 °C
  8. Precipitation (mm per hour): 0.2 mmTemperature (°C per hour): 8.4 °C
  9. Precipitation (mm per hour): 0.4 mmTemperature (°C per hour): 9.2 °C
  10. Precipitation (mm per hour): 0.8 mmTemperature (°C per hour): 10.1 °C
  11. Precipitation (mm per hour): 1.1 mmTemperature (°C per hour): 11.3 °C
  12. Precipitation (mm per hour): 1.6 mmTemperature (°C per hour): 12.4 °C
  13. Precipitation (mm per hour): 2.1 mmTemperature (°C per hour): 13.2 °C
  14. Precipitation (mm per hour): 2.9 mmTemperature (°C per hour): 13.8 °C
  15. Precipitation (mm per hour): 4.4 mmTemperature (°C per hour): 14.1 °C
  16. Precipitation (mm per hour): 6.3 mmTemperature (°C per hour): 14 °C
  17. Precipitation (mm per hour): 3 mmTemperature (°C per hour): 13.5 °C
  18. Precipitation (mm per hour): 1.2 mmTemperature (°C per hour): 12.6 °C
  19. Precipitation (mm per hour): 0.6 mmTemperature (°C per hour): 11.4 °C
  20. Precipitation (mm per hour): 0.2 mmTemperature (°C per hour): 10.6 °C
  21. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 10 °C
  22. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 9.6 °C
  23. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 9.3 °C
  24. Precipitation (mm per hour): 0 mmTemperature (°C per hour): 9.1 °C
Example rule (fictional)
Precipitation above the authored limit in one hour: 5 mm
Event at the triggering hour
15:00 · Alert not sent. This is an illustration only.

Keep the buyer decision open.

  • Retailer validation: not supplied
  • Demand impact: not calculated
  • Purchase approval: unknown
Show buyer review notes

Review retailer history, stockouts, promotions, category sensitivity and supply timing separately. Weather alone does not establish a sales effect, causal explanation or reorder quantity.

Take the evidence into a bounded review.

Discuss the required sources and validation with the responsible team. This illustration does not approve a purchase, change a forecast, send an alert or execute an order.

Review the planning exampleReview source requirementsReturn to Plan & Buy

Choose the next question for the buyer.

Highlight one missing input and carry the product, scenario and selected week into a local review note.

Local review note

Review context
Jacket / PLAN-J01 · Base assumption · Week 1
Next review question
Confirm the counted units, period coverage and missing stockout history before treating sales as demand evidence.

This choice sends no request, saves no plan and changes no stock or order.

Connect the assumption to the next decision.

A reviewed planning assumption is one input to a product discussion. Agree the actual evidence and responsible reviewer before connecting it to buying or pricing.

Review the product range

Keep selection criteria and missing inputs with the buying discussion.

Discuss price and promotion

Carry assumptions and constraints into a separate pricing review.

Plan the data connection

Agree authorized sources, counted units and coverage.

Read workflow evidence

Distinguish a request, recorded execution and reviewed output.

Discuss your planning inputsExplore the public-data demo