productmix_storelevel: productmix_storelevel

In inventorize: Inventory Analytics, Pricing and Markdowns

productmix_storelevel

Description

Identyfing ABC category based on the pareto rule for both demand and selling price,a mix of nine categories are produced. Identyfing ABC category based on the pareto rule.A category is up to 80 in this fuction the data is splitted by store and a product mix is made on each store individually.

Usage

productmix_storelevel(
  SKUs,
  sales,
  revenue,
  storeofsku,
  na.rm = TRUE,
  plot = FALSE
)

Arguments

SKUs,	charachter, a vector of SKU names.
sales,	vector, a vector of items sold per sku, should be the same number of rows as SKUs.
revenue,	vector, a vector of total revenue per sku, should be the same number of rows as SKUs.
storeofsku,	vector, which store the SKU is sold at.should be the same number of rows as SKUs.
na.rm,	logical and by default is TRUE
plot,	default is FALSE,if true a plot is generated

Value

a dataframe that contains ABC categories by store with a bar plot of the count of items in each category.

Note

this is the first version of the inventorize package, all the functions are common knowledge for supply chain without any academic contribution from my side, the aim is to facilitate and ease much of the bookkeeping that is endured during stock analysis.

Author(s)

"haytham omar email: <[e-mail]>"

Examples

productmix_storelevel(c(1:1000),sales = runif(1000,4,10000),
revenue  = rnorm(1000,100,20),storeofsku = rep(seq(1:10),100))

inventorize documentation built on June 1, 2022, 1:07 a.m.