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Jedox Ideas

Let us know how we can make Jedox even better!

Status Future consideration
Workspace Jedox Platform
Created by Guest
Created on Sep 13, 2023

Splashing via graphic visualization

This would make Jedox very visually appealing in demos, and introduce a functionality that no other EPM tool possesses.

Add the ability in Charts to drag a series. When the mouse is released, the new chart value is splashed over the dataset behind the chart.

  • if a certain key is pressed when the mouse button is released (eg control key), a default # proportional spread (or the predict splash) happens on the underlying data to represent the new series value.

  • if there is no secondary key pressed, when the mouse button is released, the planning assistant pops up to allow various planning options.

  • To ensure the dataset behind is a valid one, there could be checks to ensure exists in the chart data source, or that the action is restricted only on views as data source (for example).

  • An additional functionality could also be 'holding' certain datapoints before dragging the series.

  • This potentially could be a unique functionality of 'native' Canvas Charts.

  • Guest
    Sep 25, 2023

    The following are all possible now, but this feature would enable real visual planning.

    Scenario 1 : 3 or 4th round of the planning cycle. Visually adjusting a forecast in a Canvas visualisation to match a predetermined strategic goal without using any splashing commands or wizards.

    Scenario 2: Planning What if exercise. A chart containing multiple, dependent metrics. Dragging a bar on one or more of the dependent metrics (eg Price, Qty) to see the immediate impact of the other series (eg COGS, Sales). Powerful of other planning types are included (eg Transfer and Reallocate) which would enable a visual redistribution of values.

    Scenario 3: Bottom Up Budgeting: Extrapolate Opex costs via dragging a series across empty accounting periods. Predict splashing would then be employed to predict these (slowly changing) values across the series based on another metric (eg last years values or sales). Top down adjustments can then be made to the dataset.

  • Admin
    Oliver Hüttner
    Sep 22, 2023

    Hi, thanks for the idea. Can you add one or two use cases, so that we understand the user value better?