SAP S/4HANA Cloud Professional Services Time Entry serves multiple purposes - as both a record of attendance, and more importantly the key driver for Service revenue. This blog will give you some ideas for managing this data through KPI visualizations. User time entries enter the system with the Manage My Timesheet application, or via the Workforce Timesheet API. Time Administrators and Project Managers can benefit using a KPI approach to find and evaluate exceptions in these entries with easy-to-use KPI’s to see the discrepancies and act.
Before you begin it is important to have a working knowledge of both the Custom CDS View App and the Custom Analytical Query App.
The following steps are guidelines, and field lists and Join conditions given are recommendations as well, and may vary based on use case.
Step 1
Create Custom CDS View of scenario 'Analytical Cube' (YY1_timesheetrecords) This view is comprised of the data from thees CDS Views:
- I_TimeSheetRecord for the raw time record
- I_WBSElementBasicData for the customer or internal project assignment
Use the following join condition between the sets:
Below you will see the elements/fields chosen for the CDS view:
The result of this step creates a CDS View combining the Project data with Time Entry data, and as the basis for our KPI.
Step 2
Create a Custom Analytical Query (YY1_Timesheet) based upon the CDS view YY1_timesheetrecords. This assures that the data can be filtered and aggregated.
Here is a
great blog to get you started on this App
Here is a screenshot example of this query:
Step 3
Creating the KPI
Follow the guidelines in this excellent blog for step by step instructions.
Analytics Extensibility Part III : Manage KPI and Reports | SAP Blogs
Create or use an existing KPI Group. In this example the the KPI Group is created and named ‘Timekeeping’. KPI Groups are used to organize similar KPI’s.
Step 4
Now create the actual KPI report and assign it to this Timekeeping KPI Group.
Begin by creating the description and data source details. (YY1_Timesheet). I do not introduce Semantics for measure or scaling in this example simply because the only value metric is the time entry value calculated in unit of measure H (hours).
Nest create a report “Timekeeping’ that will be used for drilldown from the KPI. Select the Configuration tab in the Edit Report function. Input Parameters and Filters describe which data elements can be selected for filter analysis. In this example it is
- Company Code
- Activity Type
- Project
- Time entry Status
Next you will add a mini-tile for the report and select the Group KPIs. There are five standard tile choices available.
The next step is to build chart visualizations. Select Add in the Charts and Tables and enter the title and view type ‘Chart’. I have created 4 chart views for each of the filters - Activity Type, Company Code, project, and time entry Status:
Select Add to create each of the four. Add the view title ‘Activity Type View’ and the chart will render in first iteration. Select Edit button to make sure of the column properties contains Activity Type.
After Activation select Show Preview to see your KPI chart(s).
Next Steps:
After activation follow the Analytics Extensibility Part III blog post for saving and publishing the new application to the role catalog.
There are many places you can go from here as you refine your analytical queries with parameters and filters.
Time Management is an important process and crosses many boundaries in the enterprise including accounting, payroll, billing, and cost management. I hope with this post that you will see additional possibilities for improvement in all these areas, as well build a better management of the abundant exceptions that accompany this process.
You are encouraged to provide your feedback on what works and what can be improved in your analysis of the topic, so please check back regularly.
The SAP S/4HANA Cloud Community provides a wealth of product knowledge and advice and direction, and to ask a specific question see the forums at
https://community.sap.com/topics/s4hana-cloud.