iDoc Error Management: A Revolution

SAP standard tools for IDoc error resolution do not provide enterprises with sufficient meaningful information, for optimized issue remediation across the business & technical teams. This inefficiency leads to the following problems common across most SAP implementations:

  •  Difficultly for business teams to navigate the iDoc Error Cockpit and decipher the root cause issues efficiently
  •  Among a large number of iDoc failures, it's not possible to delineate which iDocs need to be fixed in a priority sequence, eg which iDocs have the biggest financial impact vs which ones do not?
  •  Where dependencies exist across iDoc failures, it's not possible to identify where 1 fix could resolve 500 iDocs.
  • Searching iDocs within the SAP system can be extremely slow with poor response times leading to incomplete analysis being performed

The net result is that users perform an hit and miss, unstructured approach to problems presented to them which is not optimal ie:

 - First In First Out (FIFO) - Reactionary approach

 - Last In First Out (LIFO) - Time Based approach

 - iDoc Type based - Category based approach

- Off system analysis - Download to Excel for manual triage

None of the above approaches provide an efficient scientific outcome optimized driven approach to resolve the issues inline with business expectations.

Kagool iDoc Error Manager (IEM)

The Kagool IEM helps enterprises by specifically addressing the above problems and more, helping them prioritize remediation efforts directly inline with their goals. Every second, IEM will re-calibrate and present the top 10 iDoc issues by fix team that have the biggest impact to the enterprise - this ensures that the workforce is always aligned to fixing issues in a sequence that maximize value for the firm.

It performs this in the following ways:

Categorization - auto error assignment & ownership and providing metrics by:

  • Geographic Region
  • Programme/Plant
  • Brand
  • Business Domain
  • Resolution/Fix Team
  • Business Value Determination

Triage - Automatically sequenced based on business objective eg:

  • Prioritization by iDoc inter-dependencies (Fix Counts Vs Error Counts) fix one and resolve many
  • Prioritization by financial values (eg can prioritize Receipts over Payments)
  • Reporting/Metrics

  •  Full visibility on iDoc error metrics across Business and IT
  •  Visibility on business impact of the failures
  • Extremely fast response times navigating iDocs via Data Lake
  • Visibility on resolution team ownership split by iDoc counts and business financial impact
  • Bench-marking of fix times across Regions, Domains etc
  •  Efficient auto-triage of error resolution prioritized inline with business objectives
  •  eg Fix these 6 iDocs and release £1.5m of receipts
  •  eg Fix 1 idoc and it will auto resolve 200 dependent failures automatically

Solution Architecture

Utilizes the Kagool SAP to Data Lake Direct real-time syndication which is a server-less data transfer mechanism removing the need for any new technologies on the client landscape. ie no ETL, SAP BW/BI required - only SAP and Lake tech.

The process supports the transfer of huge data payloads and enables a near real-time dataset in the chosen Lake. Implementation is fast and the integration process can be finely tuned directly in the Lake by admins.

Supported Systems

  • SAP Systems- All are supported
  • Data Lake - MS Azure, Google Cloud Platform, Oracle Cloud
  • Visualisation - PowerBI, Tablaeu, Qlikview

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