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Results review

Accessing the screens

To review the overall results of a past scenario:

  1. Go to First Allocation → View Past Scenarios
  2. Click on the scenario ID number you want to analyze.
  3. Navigate through the multiple aggregated and disaggregated layers of data and results

Layers of Visibility

To enhance the understanding of system decisions and improve inventory management, Nextail provides multiple layers of visibility into initial allocation scenarios. Each layer allows users to analyze data and parameters at varying levels of granularity, offering a complete picture of the replenishment process. Let’s review them!

  • Scenario level
  • Product level
  • Product-Store level
  • Store level

Now, let’s dive into the different layers of visibility and explore the insights they offer!

  • Scenario Level:
    At this level, users can get a scenario summary of the total number of products, stores, SKU, and units to allocate, as well as the main key parameters set for the calculation.
    Additionally, on this level, there is a data table which provides an aggregated summary by product and store, for all those included in the allocation perímeter. These are selected through the tabs.

  • Products tab: Aggregated data at the product level, for all the stores included in the perimeter. Each product has an aggregated summary split by SKU, which is opened in a side panel just by clicking on any of the KPI metrics displayed. Otherwise, to go into deeper layers, if you click on a specific product, you can review the details of a single product at two different levels:

    • Product-level disaggregated results

  • Store/SKU: analyze data for a single product across all stores, broken down by SKU and grouped by store.

 

  • Forecast Visualization: see the estimated demand forecast evolution over the days and weeks for a single product, aggregated by the stores included in the perimeter. Additionally, compare the estimated ROS (Rate of Sales) of this product vs the real ROS performance of up to 5 similar items of your choice, in the same period from last year, and extract your own findings.

 

  • Product-Store level disaggregated results

  • Store Optimization: review store-level parameters used in optimization calculations, such as Visual Rules, Sales Threshold, SKU-blocks and Transit times amongst others. 

  • Forecast Visualization: see the estimated demand forecast evolution over the days and weeks for a single product in any particular store from the ones included in the perimeter. Additionally, compare the estimated ROS (Rate of Sales) of this product in this store vs the real ROS performance of, up to 5 similar items of your choice, in the same period from last year and extract your own findings.

  • Stores tab: Aggregated data at the store level, for all the stores included in the perimeter. Each store has an aggregated summary of Total Products and Total Units proposed to be allocated, split by Family, as well as the existing ones already allocated.

Advanced Analysis

Key Data Points

Below you can find a list of key data points provided in each different visualization lever.

  • Scenario summary
      • Number of products, stores, and SKUs involved in the allocation.
      • Total number of units proposed to be allocated.
      • Key parameters used for the calculation: Allocation Date, Calendar Plan, Warehouse, and Planning Horizon.

  • Product summary
      • Product level
        • Sales threshold, to know the service level defined.
        • Ratio and units of stock allocated from the total stock available to allocate, to know how much stock has been allocated from the available one and how much has not.
        • Ratio and units of estimated demand from the total stock allocated, to know how much of the stock allocated is demand-driven and how much it is not.
        • Ratio and number of stores allocated from the total perimeter target, to know how many stores have been allocated and how many have not.
      • Product-Size level
        • Ratio and units of stock allocated from the total stock available to allocate, to know how much stock has been allocated from the available one and how much has not.
        • Ratio and units of estimated demand from the total stock allocated, to know how much of the stock allocated is demand-driven and how much it is not.

  • Allocation summary
      • Dual-outcome eligibility
        • Baseline proposal summary
          • Number of units to allocate
          • Number of stores to allocate
          • % of Wh stock to allocate
        • Adjusted proposal summary
          • Number of units to allocate
          • Number of stores to allocate
          • % of Wh stock to allocate
      • Selected outcome details
        • Ratio and number of stores allocated from the total perimeter target, to know how many stores have been allocated and how many have not.
        • Ratio and units of stock allocated from the total stock available to allocate, to know how much stock has been allocated from the available one and how much has not.
          • Ratio and units of stock allocated by different types of logistic sets (if so), to know how much of the stock has been allocated in singles, in packs, or in prepacks.
        • Ratio and number of prepacks allocated from the total prepacks stock available to allocate, to know how many prepacks have been allocated from the available ones, and how many not.

  • Store/SKU details
      • By store
        • Total Demand Forecast
        • Total final stock
        • Planning Horizon
      • By Store/SKU
        • Demand Forecast
        • Min Display
        • Stock Projection
        • Units to allocate
          • In packs/singles
          • In prepacks
        • SKU Blocks
      • Sorting capabilities by (ascending/descending)
        • Total store Demand Forecast
        • Final store stock
        • Store code or store name
      • Filtering capabilities by
        • Min & Max final stock
        • Not allocated stores
        • Store Categories

  • Forecast Visualization
      • Allocation timeline: Allocation Date, lead time, and Planning Horizon
      • Daily and weekly demand forecast baseline value, within the whole Planning Horizon, limited up to 30 days.
      • Daily and weekly ROS, within the whole Planning Horizon, limited up to 30 days.
      • Promotion tag and demand forecast uplift.
      • Last year sales of similar items (manual selection), limited up to 30 days.

  • Store Optimization
  • Visual Rules requirements (Min Units)
    • Visual Rules requirements (Min size weight %)
    • Sales threshold
    • Active Promotions
    • End date
    • Demand Forecast
    • Min Display
    • Stock Projection
    • Units to allocate
      • In packs/singles
      • In prepacks
    • SKU Blocks

Making Data-Driven Decisions

These detailed insights enable users to understand how optimization parameters interact to influence on initial allocation outcomes. By analyzing these data points, users can refine their strategies, ensuring stock distribution aligns with business objectives while addressing store-specific needs.