Same recipe, same run: production group planning at Flora Food Group

Flora Food Group

Client case study · SAP IBPDelivered by Straveo

How grouping products that share a recipe in SAP IBP removed line crossovers and capacity overloads, and cut setup, labour and wastage costs.

€3.0bnnet sales value, 2025

1.0%net sales CAGR, 2019 to 2025

100+countries served

14manufacturing sites

Client and context

Headquartered in Amsterdam with 150+ years of heritage, Flora Food Group delivers culinary essentials across butters and spreads, creams, sauces and liquids, and cheeses, through brands such as Flora, Becel+ProActiv, Blue Band, Country Crock, Rama and Violife.

Many products share the same flavours and ingredients. On the factory floor, several finished goods can run from one recipe, if the plan brings them together.

Source: Flora Food Group Annual Report 2025

Flora Food Group products including Rama, Violife, Blue Band, Flora and ProActiv

The problem

Three Flora Plant Butter finished goods share one recipe. Each had its own demand, but with no grouping, that demand never came together at the shared semi-finished good (SFG) and raw materials (RM). Dependent demand was scattered across different weeks.

Demand stays apartEach FG passed its demand to the recipe on its own, in its own week.

Same recipe, many runsOne recipe ran several times on different lines and weeks.

Costs and waste upMore setups meant higher setup and labour costs, more wastage and strained resources.

Planner burdenPlanners had to stitch together both quantity and sequence by hand.

One mixer, three packaging lines, demand in three different weeksRaw materials become one SFG in the mixer, which is packed into three tubs on three lines, yet each tub’s demand lands in a different week.

RAW MATERIALS (RM)Plant oil blend
Water
Salt
Emulsifier

MixerSFG · Plant butter base

LINE 1

Plant Butter Tub

W1demand

LINE 2

Plant Butter Tub

W3demand

LINE 3

Plant Butter Tub

W5demand

Same SFG and RM called three times, not once

Dependent demand scattered over W1, W3 and W5

Three mixer batches and setups for one recipe

How it works in IBP: before and after

GRP_PlantButter brings the three FGs that share one recipe into a single group product, which is the input to the IBP optimizer. The optimizer plans the group with its setup cost and capacity counted once per period. Based on the maintained attribute values, orders then flow to each FG and, through the BOM, to the SFG and RM.

GROUP PRODUCTGRP_PlantButter

100 g

200 g

500 g

input

IBP OPTIMIZERPlans the groupSetup and cost once per period

attribute values

Plant Butter Tub 100 g

Plant Butter Tub 200 g

Plant Butter Tub 500 g

BOM

SFGPlant butter base

BOM

RMPlant oils, water, salt, emulsifier

Optimizer levers for the group:Fixed setup capacityFixed group costMinimum output

Before: planned FG by FGProduction and dependent demand by week

W1W2W3W4W5W6

No group

Plant Butter Tub
100 g

Plant Butter Tub
200 g

Plant Butter Tub
500 g

SFG and RM
dependent demand

3 setups3 runsSFG and RM called in 3 weeks

After: planned as GRP_PlantButterGroup planned in W1, orders flow to FGs, SFG and RM

W1W2W3W4W5W6

GRP_
PlantButter

1
setup

Plant Butter Tub
100 g

Plant Butter Tub
200 g

Plant Butter Tub
500 g

SFG and RM
dependent demand

1 setup1 runSFG and RM called once

SetupOriginal demand weekThe optimizer pulls demand forward when the setup saved outweighs the cost of holding stock. Weeks are illustrative.

Executed with the SAP IBP Optimizer.

Solution and implementation

PROPOSED SOLUTION

Straveo recommended group planning within Flora’s SAP IBP tenant, using grouping attributes that match business needs, so the three FGs are planned together as GRP_PlantButter, orders flow down correctly to FGs, SFG and RM, and lines become clearer and more direct.

IMPLEMENTATION

Built on Flora’s existing master and transactional data, with an automated group products master data type and maintenance rules, so the process runs with very little manual effort.

1Maintain attributesPlanners set the grouping attribute values on the FG master data.

2Rules propagateMaster data maintenance rules push the values down automatically.

3Group product createdAn automated master data type builds GRP_PlantButter from the three FGs.

4Optimizer plans the groupGRP_PlantButter is the optimizer input, so setups, costs and minimum batches are planned once.

5Orders flow downBased on attribute values, orders flow to each FG, then through the BOM to SFG and RM.

Impact on the business

Before vs after group planning

BeforeAfter

Capacity overloadLower

Setup and labour costLower

WastageLower

Working capital tied upLower

Plan reliabilityHigher

Bars show the direction of change and are not to scale.

WORK WITH STRAVEOShared recipes deserve a shared plan.

If similar products are planned apart in your network, there may be capacity, cost and material efficiency waiting to be unlocked. Our SAP IBP team can help you find it.

1Planning efficiency reviewWhere grouping could ease capacity and cut setups

2Group planning implementationDesign, build and roll-out in your IBP tenant

3IBP Optimizer enablementSet-up, tuning and planner adoption

Start a conversation

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