process-mining
2021.10
true
Process Mining
Automation CloudAutomation Cloud Public SectorAutomation SuiteStandalone
Last updated Sep 2, 2024

Analysis - Deviations

Introduction

Analysis - Deviations is the main dashboard where you can analyze the deviations that occur in the Order-to-Cash process. The blue colored activities are the main activities in the process, the happy path. Deviations are recognized as block (red) or change events (yellow). These are events that you would ideally not want to happen. See the illustration below.



The information displayed in the dashboard is based on the creation date of the sales order items. The Period filter in the Filters panel enables you to select a period to display the sales order items that were created in the selected period.

Note: Since the process graph displays all sales order items which are created within the selected time period, the graph can also contain changes to these sales order items that might be outside of the selected period.

KPIs

Below is a description of the KPIs that are displayed at the top Analysis - Deviations dashboard.

KPI

Description

Blocks set

The total number of block (set) events on sales order items during the selected period.

Note: If you click on the Blocks set KPI, a filter is automatically created and added in the Filters panel.

Changes

The total number of change events on sales order items during the selected period.

Note: If you click on the Changes KPI, a filter is automatically created and added in the Filters panel.

Main events

The total number of main events on sales order items during the selected period.

Note: If you click on the Main events KPI, a filter is automatically created and added in the Filters panel.

SO items

The total number of unique sales order items during the selected period.

Total value

The total value of the sales order items created during the selected period.

Avg. event throughput time

The average event throughput time for sales order items events during the selected period.

Note: If you click on the Avg. event throughput time KPI, the Avg. event throughput time metric is selected in the SO item events dashboard item.

Timestamps

Throughput time is the duration between the event end timestamps of two events that follow each other. In this case, waiting time and idle time are also calculated. Processing time is the time actually spent on the event. In this case, waiting time and idle time are not taken into account.

SO item events

With the SO item events dashboard item you can analyze the Sales order items in more detail.

You can create various different contexts by selecting different attributes from the drop-down list. For example, when you select the Activity trigger you can analyze the reason that triggered the sales order item event.

The metric selector enables you to select different metrics. Below is a description of the metrics that can be used to analyze the sales order item events regarding the selected attribute.

Metric

Description

Number of events

The number of unique sales order item events, within the selected period.

Avg. number of events

The average number of events that were performed on sales order items, within the selected period.

Percentage of SO items

The percentage of sales order items per category, compared to unique sales order items of all categories, within the selected period.

Avg. event throughput time

The average throughput time of all sales order items events, within the selected period.

Avg. event processing time

The average processing time of sales order items events, within the selected period.

Note: The selected metric applies to all the different dashboard items of the Analysis - Deviations dashboard. If you select a different metric in the SO item events dashboard item, the other charts will also change accordingly.

Activity category legend

The colors of the activities in the process correspond to the different event categories. See illustration below.



  • Introduction
  • KPIs
  • Timestamps
  • SO item events
  • Activity category legend

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