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5 Location Clustering Task
Location Clustering groups stores into clusters based on similar performance, attributes, or space characteristics. These clusters allow planners to create localized assortments at scale by applying a single assortment to groups of similar locations. All locations within a cluster receive an identical assortment unless modified through store-level exceptions. Clustering may also be referred to as store groups or store tiers.
Clusters are defined using a combination of location attributes and performance metrics. Planners can select up to three attributes to drive clustering, although fewer may be used depending on the business need. Selecting more attributes increases the number of clusters, improving localization but also increasing planning complexity.
Cluster versions can be created and reused across assortment periods, also referred to as buying periods or seasons. This allows planners to apply different clustering strategies by season while maintaining consistency where needed. When creating an assortment period, the planner selects the cluster version to be used for that season, which impacts the assortments planned.
Create the Location Clustering Segment
To create the Location Clustering segment:
1. Click Assortment Services in the Task menu.
2. Select the Planning Maintenance activity.
3. Select the Location Clustering task. The Create New Plan dialog opens.
4. Click Create New Plan .
5. Enter a plan label and click OK .
6. In Select Product , choose one or more categories and click Next .
7. In Select Sales Source , choose the data source and click Next .
- Actuals uses historical performance data.
Selecting Actuals for future periods will result in no data.
-
Forecast uses forecast data from external integrated systems.
-
Plan uses MFP Location Plan values (if available).
For elapsed periods, MFP data may include both actuals and plan.
8. In Select Calendar , choose the time periods (recommended: at least six months of data) and click Finish.
Step: Setup
The Setup step defines the inputs and parameters used to generate location clusters. These inputs determine how locations are grouped and directly impact assortment localization.
Tab and Views in this Step:
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Setup Tab:
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Attribute Analysis View
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Clustering Setup View
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Sales Perf Group Setup View
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Space Group Setup View
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Review Location Space View
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Application Actions
Seed Strategy Weights
Populates performance metric weights using the strategy weights defined in Planning Administration.
Optimize Clusters
Runs the BaNG algorithm to generate optimized clusters using a science-based methodology. This is an optional application action.
Create Cluster
Generates clusters based on selected attributes, weights, performance groups, and algorithm. This action must be rerun whenever inputs are updated.
Setup Tab
This tab supports attribute analysis and configuration of clustering inputs.
Attribute Analysis View
The Attribute Analysis view displays location attributes alongside performance metrics based on the selected sales source (Actual, Forecast, or Plan) and calendar periods. This view enables planners to evaluate how attributes differentiate store performance and supports selecting the most meaningful attributes for clustering.
| ~ Attribute Analysis | ||||
|---|---|---|---|---|
| Measure(Default) = $$ | ||||
| [0 | LocationAttributes Fh 2 | |||
| Measure ‘Sales | Reg+PromaUl | SalesU% | RateofSalesU | LocationCount |
| Location Arributes | ||||
| = Climate | 5,776,522 | 194 | 170 | |
| Cold | 1,021,054 | 17.7% | 189 | 32 |
| Hat Dry | 946074 | 16.4% | 193 | 28 |
| HotHumid | 706,116 | 122% | 192 | ral |
| Marine | 420,465 | 73% | 201 | 12 |
| MixedDry | 271567 | 47% | 194 | a |
| MissedHumic | 1,111,190 | 19.27% | L949 | 32 |
| NA | 439,525 | 76% | 549 | 7 |
| VeryCold | 860.735 | 149% | 159 | 31 |
| = CustomerType | §.557,199 | 187 | 163 | |
| Conservative | 1,973,624 | 37.0% | 188 | 60 |
| FashionForward | 2,095,754 | 30.3% | 203 | 59 |
| Mainstream | 1,267,821 | 23.8% | 145 | ae |
location attribute defined in the Clustering Setup View. In this view, planners complete the process by defining the number of space groups and choosing between Breakpoint or Optimized clustering. Then they create clusters here.
If using the Breakpoint algorithm, the steps to complete this process:
1. Enter the number of performance groups (maximum of five).
2. Define the Space Source from integrate files (such as, Fixture capacity, Square Feet, Square Meter).
3. Review and adjust upper breakpoint boundaries if needed.
4. If you adjust the upper boundary, it will only be valid for the current session and will not be committed to the segment. When you create a new segment, the system will revert to the recommended values.
5. Review location count and average sales.
6. Execute Create Cluster application action to generate cluster assignments.
Note
If you make changes to any settings, you must rerun the Create Cluster Application Action in order to see updated results.
If using the Optimized algorithm, the steps to complete this process:
1. Enter the number of performance groups (maximum of five).
2. Define the Space Source from integrate files (such as, Fixture capacity, Square Feet, Square Meter).
3. Enable the Use Optimized Perf Group Boolean flag.
4. Review the Location Count and Avg Sales U for each performance group.
5. Execute Optimize Clusters application action to generate optimized clusters using a science-based methodology.
6. Execute Create Cluster application action to generate cluster assignments.
Note
If you make changes to settings, you must rerun the Optimize Clusters and Create Cluster Application Actions in order to see updated results.
|>5.ReviewLocation
Space
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|
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|
|«
Locatio
|nSpace@
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||
|---|---|---|---|---|
|
|
LocationSpace Avg # ofFioctures|
FisineCaneclig|
‘SquareFeet|Square Meter|
|Location|||||
|1101 US -CreekSquare|2.0|oo|0.0|0.0|
|1102 US - Easton TownCenter|oo|a0|oo|a0|
|1103 US -Southpark Mall|0.0|0.0|0.0|0.0|
|1106 US -Beachwood Place|a0|2.0|0.0|0.0|
|1107US - LombardStreet|20|0.0|o.0|0.0|
|1108 US -WaterTowerPlace|La]|a0|0.0|0.0|
|1110US-SohoStore|Lia]|0.0|0.0|0.0|
On selecting the alternate dynamic hierarchy defined in the Define Location Rollup View, you can see the subtotals at each nested level. You can edit these subtotals with editable measures to spread the values to all the associated positions.
Step: Approval
The Approval step finalizes the clustering process by creating approved cluster versions for use in assortment planning. In this step, planners review the final cluster results, assign version labels, and approve clusters for use in Assortment Maintenance. Approved cluster versions can be reused across assortment periods, enabling consistent and repeatable clustering strategies.
The output of this step is an approved cluster version that can be assigned to an assortment period.
Tab and Views in this Step:
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Approve Tab :
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Final Cluster Review View
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Approve View
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Approved Cluster View
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Select Cluster Version View
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Application Actions
Approve
Creates an approved cluster version that can be assigned to an assortment period. Multiple versions can be created and reused across different planning cycles. Approving to an existing version will overwrite its contents.
Refresh Cluster Version
The Refresh Cluster Version application action updates the workspace to display the cluster assignments for the selected cluster version. This action allows planners to switch between approved cluster versions and compare how locations are grouped across different versions.
Approve Tab
This tab is used to review clustering results, define version details, and approve cluster versions.
Final Cluster Review View
The steps to complete this process:
1. Review location count by cluster.
2. Update Override Cluster Label if needed.
3. Execute Approve application action to apply label changes.
| > Approved Clusters | ||||
|---|---|---|---|---|
| ClusterVersion | Version01 | Version 02 | Version03 | ‘Version 04 |
| Measure | Approved Cluster | Approved Cluster | Approved Cluster | Approved Cluster ‘i |
| Location | ||||
| + North America | US Brick & Mortar US/ | US Brick & Mortar_US / | ‘USBrick & Mortar_US/ | US Brick &Mortar_US/ |
| » United States Brick and Mortar | US Brick & Mortar_US / | US Brick & Mortar_US / | ‘US Brick & Mortar_US / | US Brick&Mortar_Us/ |
| 1101 US - CreekSquare | US Brick & Mortar_US / | USBrick &Mortar_US/ | US Brick & Mortar_US // | US Brick &Mortar_US/ |
| 1102US - EastonTown Center | USBrick & MortarUS / | US Brick & Mortar_US / | US Brick & Mortar US / | US Brick &Mortar_US / HatDry |
| 103 US - Southpark Mall | US Brick & Mortar_US / | US Brick & Mortar_US / | US Brick & Mortar_US / | US Brick &Mortar US / |
| 1106US - Beachwood Place | US Brick & MortarUS/ | US Brick & Mortar_US / | US Brick & Mortar_US / | US Brick &Mortar_US/ |
| 1107 US - Lombard Street | US Brick&Mortar_US/ | US Brick & Mortar_US / | US Brick & Mortar US // | US Brick &Mortar_US / Hot Dry |
| 1108.US - Water Tower Place | US Brick & Mortar_US / | US Brick & Mortar_US / | US Brick&Mortar_US / | US Brick &Mortar_US / Very |
| 1110 US - Soho Store | US Brick & Mortar_US / | US Brick & Mortar_US / | ‘US Brick & Mortar_US J | US Brick&Mortar_US/ |
| 1111 US -Westboro | US Brick & Mortar_US/ | US Brick & Mortar_US / | ‘USBrick & Mortar_US/ | US Brick &Mortar US/ |
| 1113 US - Fox Valley Mall | US Brick & Mortar_US / | US Brick & Mortar_US / | ‘US Brick & Mortar_US | US Brick&Mortar_US / Very |
| 1114 US - Westwood Plaza | US Brick & Mortar_US / | US Brick & Mortar_US / | US Brick& Mortar_US / | US Brick &Mortar_US/ |
| 1115US - Lincoln Road Mall | US Brick&Mortar US/ | US Brick & Mortar_US / | US Brick & Mortar US // | US Brick &Mortar_US/ |
| 1117US-TheGrove | USBrick&Mortar_US/ | USBrick&Mortar_US/ | USBrick&Mortar_US/ | USBrick&Mortar_US /HotDry |