Customers paying for Tier 2 have access to the Historical Analytics.  This file is updated once a day to allow for long-term analytics.  The most recent data is not available in the Historical Analytics, but will be available within 1 day of the actual transaction.

General overviews and a few specific highlights of each page are provided below.  Review the General Use document for tips on how to use Power BI to its fullest.

The Historical Analytics file is not intended for display across the warehouse.  Instead, it's meant for a more personal dive into analytics.  The visuals are smaller and more compact.  Most filters are provided directly on the page instead of needing to use the Filter Panel.  

Hierarchies are setup for metrics like Dates (Year -> Quarter -> Month -> Day), Item Categories (Category -> Sub Category -> Master Item), and Location Zones (Area -> Zone).  Hierarchies allow for drill down on data to view large data sets over years or smaller data sets over weeks.

Home Page

  • A Home Page groups and provides links to separate pages within the report.
  • At the bottom of the report, the latest dates of each key metric is shown.  This can help ensure that the data is being updated on a regular basis.
  • A link in the top right will take you to the documentation pages

Summary and User Comparison

  • The Summary and User Comparison reports are similar to reports available in the Live Dashboard.  They provide a general overview of all metrics or a comparison by user.
  • Change the metric at the top of the page to show Pick/Pack in Lines, Quantity, or Orders
  • Change the User's Group to see comparisons within a WOS Group to get better comparisons between the Picking team, Inbound team, etc.
  • Right click on a user to drill-through to a Summary page specific to that user

Item & Location and Item Contribution

  • The Item & Location page shows a general overview of items and locations within the warehouse.
  • See a variety of different measures over time.
  • View the trend over time or year-over-year comparisons of Unique Items, Unique Locations, and totals of the selected measure.

Item Contribution

Item Contribution is providing details on the "80/20 rule".  It shows how much each individual item contributes to the total measure selected, like Pick Qty.  

If an individual item's Contribution % is 4.2%, this means the item contributes 4.2% of all Picked Qty across the selected time frame.  The Pareto of Item Contribution shows that cumulative contribution as each items' individual contribution is summed towards the total of 100%.

Note: Item Contribution does not follow the same date range filtering as the rest of the Historical Analytics.  The calculations to provide the Pareto chart were fairly intensive and to provide a better user experience (faster visuals), this data is pre-calculated on a nightly basis.  
Date ranges for the Contribution Category data is provided in static values from 3 months to 24 months.

Items are grouped into categories of incrementing 10% values.  This allows for individual selections to see which items make up the top 10%, or the middle 31-40%.  

The Item Total Contribution by Category visual shows how many items fall within each 10% category

In the example below, 4 items make up 10% of all picked qty.  Farther along the x-axis, there are 138 items in the 50% category.  Combined, those 138 items contribute an additional 9.97% to the total.  Their assigned category is 50% because their contribution falls between 40% and 50% of cumulative contribution. 

The Actual Contribution % shows the variance of how much the items actually contribute outside of the standard-width categories.  So while the first 4 items are in the 10% category, their actual contribution amount is 9.86%.  The 5th item has a contribution amount of 1.33% which takes the cumulative above 10% and slots the 5th item into the 11-20% category.

A table at the bottom of the page shows specific item numbers and their individual contribution.  This table can be filtered by selecting a specific category from the Item Total Contribution by Category or using the slider to show all items below a certain %.  Once filtered, the More Options => Export Data feature on the item list allows for the top items to be exported and reviewed.

Heat Matrix

The Heat Matrix shows a grid-pattern visual of the rows and bays within the warehouse.  If your warehouse is a fairly standard grid, it will come close to representing the actual layout.  Each cell (which represents a Bay within a specific Row) will be highlighted based on how many picks were performed in that bay.

Filters allow for changing the Measure, filtering to specific Zones or Areas, filtering out Location Types to get a better view of the Pick face vs Backstock locations.

Details from the item's contribution to Total Pick Qty over the last 6 months are also available as a filter on this visual.  This allows for a view of the top 10% of items to see where they are picked or stored.

Note: Because the Contribution numbers are a static calculation of 6 months, it could present a disparity between the date range selected for the Matrix and the selection of highest picked items.  This filter can still be helpful to see where those items were stored in a longer period, but will only provide details on highest picked items over the most recent 6 months.

A list of items and locations will show specific locations and how much of that item was transacted at that location.

Other Reports Coming Soon

The Historical Analytics file is in active development.  Other reports regarding Orders, Inventory, and other operations will be provided as they become available.