Tim Woods Series #6: How to Avoid Overprocessed Data in SAP
By Clinton Jones on May 24, 2017
In previous posts in our Tim woods series, I have walked you through the aspects of SAP application data management with legacy tools like LSMW and how they contribute to the Tim Woods problem. In the 6th post in our Tim woods series, I’ll review the concept of overprocessing data.
It may be a stretch to describe data as “over-processed”, but users of LSMW understand that when you process data sets, items will “fall out” due to errors. When you strip out the successfully updated or processed records and reprocess the data file, you are re-processing data that the LSMW script has already processed. But you’ve put more effort into the data creation process and used more computing resources to attempt the load than necessary.
You may have several passes at reworking the data set before you’re able to fully process the original data set and update SAP. If this isn’t over processing – I don’t know what is.
Efficient data handling
In an efficient data management process, the record creation and maintenance tasks should be completed in one pass. The data set shouldn’t need to pass through the same pair of hands more than once, and you shouldn’t need to manipulate data more than once for that data maintenance cycle.
There are some exceptions. In instances where the requestor or initiator needs input from other participants or review and commentary, they will start the process to solicit inputs, collate the inputs, review them, distribute them and perform a final action. This is a classic workflow scenario and a standard data management process in many organizations.
If you choose to use LSMW to perform your SAP data management, you should know that it doesn’t allow you to easily implement workflow. This was not the intent when LSMW was originally created.
Economical use of scarce resources
You might argue that multiple incidents of handling the same dataset are ok, but data volumes are growing. Eventually, the existing resources you’re using to create and manage data will get overrun and swamped with requests.
People will become the bottleneck – even if you use robot-based process automation to process data in the final steps. This constraint is a big problem when there is an urgency around the data creation or retrieval process. This is also one of the reasons why ‘system’ access has become so ubiquitous and why user ids are provided to more employees than ever before.
Having a planner, accountant or IT as a gatekeeper is fine, as long as that role holds value. But systematic ways for accessing data and triggering data creation and maintenance activities is the best way to bring valuable data out of SAP and into the hands that can use it in meaningful ways.
Winshuttle offers several mechanisms to help with streamlining access. Winshuttle Studio provides business users with self-service mechanisms for extracting data from SAP in real-time based on predefined queries or self-service query creation. Studio can also be used to expose SAP reporting BAPIs for use with Microsoft Office.
At the time of record creation requests, particularly master records and master data, you can pass single records or mass data requests through several layers of contribution or oversight before the record is created. With Winshuttle Foundation, many SAP customers have implemented forms and workflow-based processes that support an active data governance strategy.
Winshuttle Foundation workflow processes also keep all participants in the workflow process informed – this insight reduces the need for follow-up and workflow processes based on automated routines or acceleration through escalation.
Because every step is recorded, you can create a view of solution usage and leverage this in a dashboard for process review and management.
Winshuttle has been used for many years for mass maintenance of SAP application data and continues to be relevant in this area even with S/4HANA. But companies hoping to eliminate inefficiency and waste need to establish good SAP application data governance practices that reduce duplicate efforts.
See how dashboard features in Foundation allow you to more efficiently manage your Winshuttle environments by identifying bottlenecks in key processes, tracking your KPIs against SLAs and better managing workload distribution.
Check out other posts in this series:
- Tim Woods Series: Reduce Waste With a Leaner Alternative to LSMW
- Tim Woods Series #2: Did you Accidentally Delete an LSMW Script?
- Tim Woods Series #3: What Keeps Your SAP ERP Relevant? Data Movement
- Tim Woods Series #4: How Long Are You Waiting for Customer, Vendor or Material Data in SAP?
- Tim Woods Series #5: Downstream Effects of Duplicate Records
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