Celonis Product Documentation

The SAP Ariba Extractor can now extract custom tables and fields out of the box. The Extractor uses dynamic metadata resolution to automatically translate all fields that are accessible to the asynchronous APIs. You don't need to make any changes to your existing connections - new tables and columns are just shown in the Extractor interface. For delta loads, set the option to include metadata changes.

We've also increased the Extractor's extraction speed and reduced its API usage, by retrieving the record count with the Count API and using it to optimize the Ariba job configuration and running order. The counts and limits are recorded in the Extractor logs.

You can now include perspectives in Studio Packages for object-centric process mining. Perspectives are views on the object-centric data model including a subset of the object types and event types that is relevant to a process, or to another grouping that you want to analyze. See Perspectives for more information about them.

You include perspectives in a Package using Data Model variables. A package can't contain a mix of case-centric Data Models and object-centric perspectives. They all need to be the same type as the one you use in the first Data Model variable that you add to the Package - so either all perspectives, or all case-centric Data Models. To swap a package between case-centric and object-centric models, you'll need to take all the variables of the previous model type out before adding the new type.

When you @ tag a colleague in a comment component in a View, they'll now get an email notification with a link to your comment and a description of its context.

See Configuring tables in legacy views for the instructions.

Triggers allow you to define business objects which, when detected in your records, will trigger a predefined automation.

To set this up, in Knowledge Model, use Triggers to define relevant business objects you want to detect and run automations for. You can use filter conditions to refine your definitions. In Action Flows, use a Watch Trigger module that allows you to connect a Trigger with a selected Action Flow.

Triggers created this way will continuously monitor all available data and detect whenever there is a new item that fulfills your criteria.

For more information on how to start using Triggers, see Triggers. Make sure to check out the Celonis Academy MicroCourse on Triggers as well.

With the Microsoft Power BI May 2023 release, the Celonis Platform Connector is officially certified by Microsoft and included when you download or update the Power BI Desktop installation. You won’t need to download the connector from the Celonis Platform marketplace or install it separately. It’s therefore being removed from the Marketplace. For the Celonis Platform Connector documentation, see Experiences.

Business Miner is now generally available for all customers, and you can use it to explore your processes using a guided series of questions and answers. Business Miner lets you leverage Celonis Platform functionality quickly and easily and collaborate with colleagues using Insights.

We’ve added extra questions for our standard Explorations and introduced (subject to licensing) process-specific Explorations for our core processes:

You can also discover how automated your processes are with our new Automation Explorations and uncover the underlying causes of issues with our KPI driver analysis for standard Explorations.

Business Miner supports object-centric process mining. You can set up Business Miner and create a Process Workspace based on the object-centric data model and the prebuilt perspectives for our core processes.

To find out more about Business Miner, see Business Miner.

Object-centric process mining is a technology that enables the analysis of interrelated objects and events involved in business processes. Events are related to objects instead of a single case, making it possible to fully view complex and interacting processes from any angle.

Now you can experience the power of object-centric process mining in Celonis Platform:

To access objects and events and the object-centric data model, you'll need a Celonis Platform contract that includes object-centric process mining. The license is process-specific - you can only use these capabilities to model the processes you've licensed. If you can't see the Data > Objects and Events option in your Celonis environment, your team doesn't have this feature yet. Talk to your Celonis Account Executive to find out more.

To get started with object-centric process mining, see Object-centric process mining overview.

The new End-To-End Lead Times app is the first Celonis app built to use the capabilities of object-centric process mining. The End-To-End Lead Times app:

You can use the app’s findings to help you to:

You can download the End-To-End Lead Times app from the Celonis Marketplace. The app works with objects and events, and requires the Inventory Management perspective that’s supplied with our object-centric data model. You’ll need to load the object-centric data model with your data and validate the Inventory Management perspective, then set up the End-To-End Lead Times app (which doesn’t need its own data connector).

The Inventory Management Control Center app (from version 2.0.1), Inventory Management Master Data Improvement app (from version 2.0.1), and Inventory Management Material Shortages app (from version 2.1.1) no longer depend on the Inventory Management Starter Kit. The apps now have their own fully self-contained Knowledge Models, so you don't need to install the Inventory Management Starter Kit and connect it to the apps before you can use them.

We've streamlined the KPIs for Inventory Management as part of this change. KPIs, filters, and variables that were not used in the Starter Kit or in any of the Inventory Management apps have been removed to reduce complexity. For the Inventory Management Starter Kit, these changes are in version 1.3.1. We've also unified some intermediate KPIs in version 2.0.1 of the Inventory Management Control Center to optimize the computation of Target Stock and Excess Inventory Rate.

If you still want to keep the previous setup, where the Inventory Management Starter Kit's Master Knowledge Model acts as a single point of truth for all Inventory Management KPIs, you can. That Knowledge Model contains all of the Inventory Management KPIs that are used by the apps. Follow the guide at Inventory Management Control Center (IMCC) App installation if you want to set up any of the apps to use the Master Knowledge Model instead of their self-contained Knowledge Model.

The Payment Term Checker App for Accounts Payable is now fully validated and has achieved GA status. The app compares payment terms on posted invoices, purchase orders, and vendor master data to identify unfavorable mismatches. The app is supported for SAP ECC, and it works best when you process both purchase orders and invoices in SAP.

Celonis is updating the IP addresses used by Celonis Platform. The previous Celonis IP addresses might be filtered in your company's firewall or connected Software-as-a-Service applications. To avoid Celonis Platform service disruption, please confirm with your IT infrastructure team if they maintain a list of allowed IP addresses for the Celonis Platform and ask them to add the new IP addresses. The new IP addresses can be found here: Allowlisting domain names and IP addresses

The connector now supports XML input with an XML converter.

For the Kafka to Celonis Platform Connector upgrade documentation, see Upgrade from the previous version.

Celonis Platform can now calculate the optimal order for the tables within an extraction task, and for the extractions and transformations within a Data Job. We work this out by looking at historical extraction data and the dependencies between extractions and transformations. With this optimization, transformations can start while unrelated tables are still loading.

The Smart ETL extension for extractions is automatically included for all of your Data Jobs as soon as it rolls out in your Celonis Platform instance. If you want to switch it off again, click the context menu (three dots) for a Data Job, select Execution Settings, and use the slider Include Extractions into the optimization of Data Jobs.

To help you find and contact our ecosystem partners more quickly and easily, we've created the new Meet our partners area in the Marketplace to showcase the resources our partners offer. Select Meet our partners in the left navigation menu to get there.

If you're a Celonis partner and you have at least three apps available in the Marketplace, talk to your Celonis representative to find out how to participate in the Partner Landings program.

Selected customers of Workforce Productivity (powered by Task Mining) can now create projects with up to 2500 concurrent users, and analyze on average 6 months of historical data. If you want to expand your projects beyond the current generally available limits (100 users and on average 60 days of data) to an enterprise scale, get in touch with your Celonis point of contact.

That average time for historical data analysis is based on the maximum permitted number of users sending a typical amount of Task Mining events daily. The actual limit is 1.6 billion events, so if you have fewer users in your project or they send fewer events than expected, you can analyze the data for a proportionally longer timeframe. We might also be able to help you in certain scenarios to roll out beyond the upper limit of 2500 concurrent users. Realm-specific limits on the number of concurrent users might affect your maximum scalability.

The Limited Availability package uses Views to match (and simplify) all the analysis features available in the GA package, and adds a Team Insights view. To learn more about Workforce Productivity (powered by Task Mining), see Task Mining.Task Mining

The audit log entries now include specific entries for Action Flow changes with relevant details about the event. The logged events are creation, activation, or deletion of an Action Flow, a change to its draft configuration, or a change to its schedule. See Audit logs for the full listing of audit log entries.

The Duplicate Invoice Checker now uses machine learning to calculate a confidence score that predicts the probability of the group containing a true duplicate. This confidence is now the default sorting column in the Action View where the groups are ranked, so users can identify true duplicates more quickly and accurately.

As a Limited Availability feature, you can customize the duplicate checking algorithm in the app's Knowledge Model to define custom patterns that determine a match. You can specify the columns that are checked for each pattern, perform multiple exact and fuzzy matches in the same pattern, and adjust the sensitivity parameters for fuzzy matches. Ask your Celonis Platform contact if you want to try this out.

For the app documentation, see Duplicate Invoice Checker