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Workforce Productivity (powered by Task Mining) (2023-10-30)

 

Everyone can scale projects up to 2500 concurrent users and 6 months of data (General Availability)

 

After our successful Limited Availability phase, we’re giving all customers of Workforce Productivity (powered by Task Mining) the capability to create projects with up to 2500 concurrent users, and analyze on average 6 months of historical data. Selected regions will see the new capability immediately, and everyone will get it on 30 October.

 

Subject to licensing, you’ll benefit from the new user limit whenever you create a new project. You’ll also see that the package’s new delta architecture processes incoming data ready for analysis typically within 1 to 3 hours. Our new views simplify all the analysis features available in the previous version of the package. You’ll also get the Team Insights view which lets you calculate metrics for a subset of defined users, such as teams, regions, or roles.

 

Because your existing projects are built on the older data model, we can’t migrate them automatically. You won’t see the new user limit, views, and processing speed for existing projects. If you want to upgrade and scale up an existing project, you’ll need to set it up again as a new project and manually adapt the views and analysis to work with the new schema. If you’d like to do this, get in touch with your Celonis point of contact.

 

The 6-month 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.

 

To learn more about Workforce Productivity (powered by Task Mining), see Task Mining.

 

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