Store Grouping: Specifies the list of attributes which should be considered for each category while creating the Attribute Groups

Column	Description
reorder_store_group	Grouping of stores for which we would like to order bestsellers separately. Eg., All the stores within a store group will have the same set of styles for reordering
discount_store_group	Grouping of stores for which we would like to offer discounts. Eg., All the stores within a store group will have the same discount recommendation for any style
reorder_flag	Indicates if the Store’s data needs to be included in Reordering analysis. Value should be either 1 or 0 if a Store needs to be enabled/disabled respectively
discount_flag	Indicates if the Store’s data needs to be included in Discounting analysis. Value should be either 1 or 0 if a Store needs to be enabled/disabled respectively

Style Grouping: Defines group of Styles(at any attribute level) for reordering/ discounting, plannned trading days,season type(OSM/NSM) and discount override

Column
style_group	Grouping of styles at any attribute level, for example, a grouping of style can be at category level or within T-shirts you want to compare polos separately and round neck separately
season_type	The season type of the style for example it could be OSM(Old Season Merchandize), NSM(New Season Merchandize) ,Fashion or Flexi
lifecycle	The plannned trading days (e.g.,60,90,etc) of the style.
discount_override	If there is a new season(NSM) and old season merchandise(OSM), brands may not want to change(increment) Discounting for certain styles of NSM. So we can add these NSM styles to the override. We will consider these override styles for comparison but still not change anything on it. Value could be 1 or 0 to consider or not consider style as override respectively.

Reordering Engine Logic: Reorder decision matrix with ROS and Discount as factors

Column	Description
ROS	Classification of unique ROS values as HIGH/MEDIUM/LOW in the product as according to the benchmarks provided at store group style group level
discount	Classification of Discount value HIGH/MEDIUM/LOW in the product as according to the benchmarks provided at store group style group level
action	Decision as Reorder/Kill/Continue according for the 3×3 matrix of ROS and Discount

Discounting and Reordering Guardrails: Guardrails at Brand/Category/ Season level to limit the maximum discount or to avoid offering a discount on good performers

Column	Description
season_type	The season type of the style for example it could be OSM(Old Season Merchandize), NSM(New Season Merchandize), Fashion, or Flexi
start_discount	Min discount put when a style is discounted for the first time
max_discount	Maximum discount to cap discount increments
incremental_discount	Percentage value by which the discount needs to be increased or reduced basis recommendation of Increase/Decrease in each cycle
reorder_max_discount	Discount cutoff for bestsellers to cancel reorder if achieved
reorder_trump_ros	ROS Threshold benchmark to qualify certain styles for reorder regardless of the high-medium-low ranking.

Discounting Engine Logic: Discounting decision matrix with ROS, Lifecycle(DOH+Age), and Health as factors

Column	Description
ros	Classification of unique ROS values as HIGH/MEDIUM/LOW in the product as according to the benchmarks provided at store group style group level
doh_ageing	Classification of unique Lifecycle(DOH+Ageing) values as HIGH/MEDIUM/LOW in the product by comparing it with the planned trading days of the style provided by the brand
health	Classification of styles as HEALTHY/UNHEALTHY in the product as according to the pivotal size benchmarks provided
action	Decision as Increase/Decrease/Continue according for the 3x3x2 matrix of ROS and Discount
perc_of_max_discount	Flexible capping based on a combination of high-medium-low

GRN: Day+Warehouse+SKU level GRN quantity. GRN resets ageing – can be cases where its in WH but not at stores