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As it is rightly said, “Small things makes things perfect, though perfection is not a small thing”. In today’s world of technology disruption, where it’s extremely important to adapt the changing business needs offered by technology, it is equally important to keep check on how efficiently the implemented technology is getting continuously utilized for improving business needs, cutting the business bottle necks and planning better. Indeed, Analytics is playing a crucial role and has become a tool of intelligence to figure this out in the form of reporting. So, these small steps are adding continuous value for improving operational efficiency of business.

This blog mainly spotlights/list downs the standard analytics reports offered by C/4 HANA for customers extensively using ERMS (Email response management system).

In this blog focus would be to explain the importance of all prominent standard analytics report related to ERMS (Email response management system), and how it could be utilized in order to generate analytics results on real time basis. These results would in turn be used extensively to streamline the business needs and would contribute in better planning of resources as per respective business needs.

In business, there could be instances when senior management would like to have a look on time spent on each status(by user) within a service ticket in cloud for service.

For Eg: Service ticket is created through ERMS, as incoming email from customer and is assigned to Internal Sales rep 1. The typical time for Internal Sales rep 1 to complete their process and move to Internal Sales rep 2 for processing should be 5 hours, then 3 hours for Internal Sales rep 3 and so on… Management would need a report in order to access and enhance the efficiency of allocated resources, while giving transparency to customer (on demand) where the ticket is within its processes or not.

In case there is requirement to take into account work schedules, for instance if customer submits a service ticket at 5:00 PM, and closing of business hours is 6:00 PM, then the service level agreement of 5 hours would continue the next day business hours with 4 hours remaining.

Also, this information would be presented as average time spent per ticket, with a benchmark of how the average time relates to the SLA. In order to address this, there are several standard analytics report in C4C, which could be used for service ticket/time management analytics.

Furthermore, this blog would also be used in understanding of standard report extension needs by customers/partners as per respective business requirements.

  1. CODACTU_Q0001 – This report enables user to do activity analysis.
  2. CRMSRQHB_Q0014 – Agent Workload.
  3. SEODSRQDTS01_Q0001 – All tickets with Account, Processor, Service org., Service Category, Service level info etc.
  4. SEODSRQINTU01_Q001 – Shows all tickets and all associated interactions(email, phone and internal notes).
  5. COD_RESP_TIME_ANA_Q0002 – Average Response times by day.
  6. /ITSAM/SAPSRB_Q0002 – Shows a comparison of created versus solved incidents against duration.
  7. CRMSRQHHB_Q0002 – Daily Average Ticket Backlog (YTD and MTD).
  8. CRMSRQHHB_Q0004 – Daily Average Ticket Backlog by Service org.
  9. CRMSRQHB_Q0002 – Daily Average Tickets Created vs. Completed(YTD and MTD).
  10. /ITSAM/SAPSRB_Q0003 – Shows the processing times required by requestors and providers for closed incidents.
  11. SEODSRQDTS01_Q0003 – List of Tickets by ID (also used for navigation to agent workspace).
  12. /ITSAM/SAPSRB_Q0001 – Shows open incidents and whether IRT and MPT have been exceeded.
  13. SEODSRQDTS01_Q0002 – Ticket Backlog: all Open and In Process tickets.
  14. CRMSRQHHB_Q0001 – Ticket Backlog (Last 7 days).
  15. CRMSRQHB_Q0013 – Ticket creation trend.
  16. CRMCASEREPB_Q0001 – Contains Main Ticket and its Sub-Tickets.
  17. CRMSRQHB_Q0016 – Top 10 Agents by Tickets Completed.
  18. CRMSRQHB_Q0015 – Unassigned Tickets by Age.
  19. COD_RESP_TIME_ANA_Q0004 – User Interactions by Day.
  20. COD_RESP_TIME_ANA_Q0005 – User Interactions by Hour.

(1) CODACTU_Q0001 – This report enables user to do activity analysis.

Below report details activity analysis against employee responsible and provides the activity counts
considered by user for various duration. This report can also be utilized in ERMS for several other
parameters already available in available fields like Account, Contact, Region, ABC Classification etc.

(2) CRMSRQHB_Q0014 – Agent Workload.

Below report provides ticket analysis against selected Sales organization. Column “Number of Open and In Process” displays output of assigned tickets to each available user. This report can also be utilized in ERMS for several other parameters already available in standard reporting like BP id, ABC Classification etc.

(3) SEODSRQDTS01_Q0001 – All tickets with Account, Processor, Service org., Service Category, Service level info etc.

Below report provides details on various teams that handles tickets and its further details like each
tickets Processor, Status, Priority, Average Handle Time, Average Review time etc. Report fields can be adjusted as per various fields available in available fields.

(4) SEODSRQINTU01_Q001 – Shows all tickets and all associated interactions(email, phone and internal notes).

Below report provides details on user sentiments against selected duration.

(5) COD_RESP_TIME_ANA_Q0002 – Average Response times by day.

This report elaborates on network time and server time details. In ERMS, email delays could be kept in check with this report.

(6) /ITSAM/SAPSRB_Q0002 – Shows a comparison of created versus solved incidents against duration.

This report would be extremely helpful in ERMS where incidents completion counts needs to be kept in check/track on frequent basis.

(7) CRMSRQHHB_Q0002 – Daily Average Ticket Backlog (YTD and MTD).

In ERMS, this report would be providing service request backlog in the form of dashboard view.

(8) CRMSRQHHB_Q0004 – Daily Average Ticket Backlog by Service org.

This report would be providing service request backlog against service org. in ERMS.

(9) CRMSRQHB_Q0002 – Daily Average Tickets Created vs. Completed(YTD and MTD).

This report details on number of incoming tickets created through ERMS and its completion status.
Results can be detailed against various fields like Service org etc.

(10) /ITSAM/SAPSRB_Q0003 – Shows the processing times required by requestors and providers for closed incidents.

This report details on number of incidents solved. In ERMS, it could be utilized to perform analysis
based on Average IRT (Initial response time), Average processing time etc.

(11) SEODSRQDTS01_Q0003 – List of Tickets by ID (also used for navigation to agent workspace).

This report list down tickets and its details like account, processor, closing date, employee id. It could be utilized in ERMS for analyzing ticket details in totality.

(12) /ITSAM/SAPSRB_Q0001 – Shows open incidents and whether IRT and MPT have been exceeded.

Below report details the open incidents counts and performs analysis by providing IRT exceeded, MPT exceeded etc.

(13) SEODSRQDTS01_Q0002 – Ticket Backlog: all Open and In Process tickets.

Below report provides analysis in ERMS as per Ticket Backlogs and its details like No. of open tickets, No of In-Process tickets etc.

(14) CRMSRQHHB_Q0001 – Ticket Backlog (Last 7 days).

Below report provides analysis in ERMS as per Ticket Backlogs and its details like No. of open SRs,
No of In-Process SRs etc.

(15) CRMSRQHB_Q0013 – Ticket creation trend.

This Report provides details on ticket creation trend and its comparison with other durations.

(16) CRMCASEREPB_Q0001 – Contains Main Ticket and its Sub-Tickets.

This Report provides analysis on Main tickets and its Sub-tickets. ERMS facilitate merging of several
tickets under main ticket.

(17) CRMSRQHB_Q0016 – Top 10 Agents by Tickets Completed.

Report provides details on top ten agents as per ticket completed.

(18) CRMSRQHB_Q0015 – Unassigned Tickets by Age.

Report elaborates on unassigned tickets by age.

(19) COD_RESP_TIME_ANA_Q0004 – User Interactions by Day.

Report displays analysis of number of interactions against dates. It also displays response time details etc.

(20) COD_RESP_TIME_ANA_Q0005 – User Interactions by Hour.

Report displays analysis of number of interactions against hours. It also displays response time details etc.

Thanks,
Chitrakant

 

 

 

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