Good afternoon,
I’m working with a customer who relies heavily on flyer promotions and is facing challenges in keeping promotional uplifts out of the Adjusted Demand, which then affects the statistical forecast.
I’d really appreciate insights or best practices from others who have solved similar scenarios in IFS Cloud Demand Planning.
Customer Background
This customer’s sales are strongly influenced by flyer campaigns — short-term promotional periods with significantly increased volumes and reduced pricing. These uplifts do not represent baseline demand, and the customer wants to ensure they don’t contaminate the historical demand used for forecasting.
What they tried so far
1. Campaigns (previous solution)
They previously used Campaigns (adjusted solution, internal case).
However, the issue is that campaign quantities scale dynamically when the statistical forecast changes.
This violates the requirement that promotional volumes must remain fixed, not proportional.
2. Events
They also considered Events.
Events are fixed and could work for positive/negative adjustments.
However, once the Event falls into the past, it no longer impacts Adjusted Demand, meaning the historical uplift still pushes the baseline forecast upward — which is exactly what they want to avoid.
3. “Smart” model / deviation detection
They asked whether IFS has a built‑in mechanism that automatically identifies sales spikes (deviations) and prevents them from influencing future baseline calculations.
A key concern is whether such a model can reliably handle recurring or multi‑week promotional uplifts, not just isolated spikes.
What we need from the community
I’m looking for best practices or configuration recommendations for this type of scenario in IFS Cloud Demand Planning:
- How can we ensure that flyer promotion uplift is excluded from Adjusted Demand and the future statistical forecast?
- Are there standard ways in IFS to clean historical demand from promos while still planning the uplift operationally?
- For recurring or long-lasting flyers, what is the recommended approach?
- Should we use Campaigns, Events, multiple Flows, manual history adjustments, or something else?
If anyone has dealt with similar requirements, I’d love to hear how you structured:
- Promo flow vs. baseline flow
- Handling uplift volumes
- Ensuring forecast integrity
- Maintaining fixed (non-scaling) promo quantities
The customer is still in early design discussions, and your experience could help us guide them toward the correct solution.
Thanks a lot in advance for any recommendations or successful patterns you can share.
Pavel K.
