#eficientassortment #efficientdistribution

Optimisation of assortment and distribution

We analyze assortment distribution in-store to ensure maximum presence, while also identifying and suggesting efficient ranges or cluster optimisations to evaluate their growth potential.

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At POS Potential we like to be specific. Below, we have outlined examples of some assortment efficiency problems that we’re sure you’ll have encountered. Thanks to the perfect integration and evaluation of sell-out data, we can help you solve them, while always having the right tools to sell a higher quantity of stock, more effectively.

Distribution case: Effective in-store assortment presence

With a combination of hundreds of stores and thousands of SKUs, there are often – especially in supermarket channels – accidental stock losses during distribution.

  • Aim: Ensure stock presence in stores, especially in the supermarket channel
  • What is analysed?: Numerical Distribution by channel/store cluster
  • Key metrics (KPIs): Numerical Distribution
  • Action: Visit stores without stock to solve problems; logistical action at the distribution centre
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Results
Optimisation of billing and shopper satisfaction/reduction of linear check-in times/up-to daily, real-time information

Methodology:

The availability of sell-out data by store means we know the sales, and can thereby determine the presence of each SKU

  • Monthly identification of SKUs/stores that have not had sales, despite being in the defined assortment
  • Automatic alarm system to improve process efficiency
  • Replenishment of missing SKUs, either centrally or at the store level

Assortment case #1:
define an assortment adapted to a channel

Defining an assortment adapted to a channel is the basic and fundamental element of commercial strategy

  • Aim: respond to the needs of the shopper in a given category, in a specific shopping trip, and in a sustainable and profitable way for the chain and manufacturer
  • What is analyzed?: simulating changes in the product mix using real sales information
  • Key metrics (KPIs): rotations/product P&L
  • Action: define an optimal assortment in terms of profitability

Results
improve the assortment’s profitability

Methodology

The availability of sell-out data and a brand/chain’s profit and loss account allows us to find the optimal combination of brands/SKU/channel/chain.

Starting with the definition of the characteristics of those stores that make up the same channel (large/medium/small supermarkets, discounters, etc.)

  • Compare rotations by chain, brand and SKU
  • Compare contributions to product P&L
  • Detection of opportunities and proposal of the assortment
  • Rotation/profitability simulations with the defined assortment

Assortment case #2: Optimisation of the product mix

The defined assortment is composed of SKUs featuring different levels of profitability. Good definition of the mix or changes to it can have important consequences for the category’s global attractiveness and profitability.

  • Aim: Improved profitability for distributor and/or manufacturer, covering the needs of the shopper.
  • What is analysed?: Simulating changes in the product mix using real sales information.
  • Key metrics (KPIs): Numerical Distribution/Weighted Distribution/rotations/product P&L.
  • Action: Define an adapted assortment in rotations and profitability for each cluster/geographic area.
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Results
Improved response to the shopper’s needs.

Methodology:

The availability of sell-out data helps define an optimal assortment based on a comparison of the efficiency of the current assortment (store rotations; Numerical Distribution/Weighted Distribution).

  • Start with the definition of the customer need units (strategic choice of chain positioning).
  • Comparison of various stores of the same size/positioning.
  • Comparison with average panel data for a channel.
  • Profitability simulations from assortment/mix hypotheses

Assortment case #3:
Tactical change of assortment in a channel

Apart from a complete assortment review, it is important to establish a routine to monitor the cluster assortment’s or the channel’s effectiveness of the cluster assortment or channel, and to be able to react quickly to seasonal changes or new trends.

  • Aim:Ensure that the assortment SKUs follow the best of the available range for the considered channel.
  • What is analyzed?: Comparison of presence and rotations of the assortment in the different store clusters of the distributor.
  • Key metrics (KPIs): Numerical Distribution/Weighted Distribution/rotations.
  • Action: Informed decision about an assortment change in a channel.

Results
Optimization of the available linear potential

Methodology

  • Monitor daily assortment rotation and distribution in the defined channel
  • Proceed to change the cluster level by SKU, depending on the rotations and billing/profitability potential of each one.

Assortment case #4: Testing the potential of an assortment change in a channel

Before proceeding with a big assortment change, it’s good practice to perform an assortment test in a limited number of stores, as an example of distributor/manufacturer collaboration.

  • Aim: Evaluate the potential risks of an assortment change.
  • What is analysed?: The shopper’s response to the new assortment offer.
  • Key metrics (KPIs): Daily rotations/profitability via facing.
  • Action: Informed decision about an assortment change in a channel.
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Results
Save time and improve efficiency before a general assortment change.

Methodology:

  • Definition of the rotation’s targets and profitability of the category following the change.
  • Choice of a representative sample of cluster stores.
  • Daily monitoring of sell-out data over a representative period in these stores.
  • Profitability differential calculation.
  • Conclusions.
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