Within Spend Intelligence, users can review tables of data on their Cost and Forecast information cast across a variety of informative metrics. Each of these tabs - one for Cost Detail and one for Forecast Detail - permits users to filter the core interface of any table by an elected data element. These tables can also be exported to your local machine for analysis in either Excel or to be imported into a secondary data system that your organization maintains.
With Cost Detail, you can access part level cost detail to ensure accuracy and data integrity of spend data. Each of the primary Cost Tables can be (1) toggled with the dropdown list and the CPN Savings % has similar options on the left.
When selecting a given sub-item like (2) Commodity: Mechanicals, then the Cost Table will be filtered to that value but also scrolling further down to the Master Cost Table will also be filtered to Mechanicals Parts:
The Master Cost Table allows you to see all your part costs and savings in one place along any selected time period. Aggregate or view at detailed level what cost drivers you need to take action on.
With Forecast Detail, you can access part level demand detail to ensure accuracy and data integrity of your demand data across any time period. Examine how your forecast compares to actuals to discern the difference between projections and results. Know what insights bring the most value to your core business drivers. Forecasts can be viewed at the commodity, part, or vendor level.
Users can (1) pick their View for the doughnut chart and see total forecasted units in the center figure with the items that add up to it arrayed in the circle around.
(2) Selecting an element in this case Commodity: Passives filters the rest of the information so the user can (3) hover over to view detail or select a quarter, or (4) compare forecast information across quarters with this filter selected at the top of the interface (in this example, we've selected 2023[Q1,Q2,Q3] and those are all visible). If the user picks just one quarter in the timeline view, the forecast table will be restricted to just that quarter.
A commodity manager may want to review the forecast vs. actual demand for the parts they manage in the LevaData Platform. In this example, Matt the commodity manager would view by commodity manager and select his own name to filter the subsequent data.
Matt can now see the Forecast vs. Actual Demand for parts under his management. This table shows the forecasted and actual values for every selected quarter aggregated to each dimension selected for view.
Spend and Savings Impact based on Forecast vs Actual Demand:
Demand Breakup is available by each quarter for the selected time period. This table will help users understand the CPN level demand in different groupings.
and Component Forecast Details:
Allowing him to review his Forecast information from a variety of dimensions.