We are seeing a recurring data quality challenge in LeanIX and wanted to learn how other organizations are addressing it.
In our setup, application fact sheets are filled by Application Technical Owners and reviewed/approved by Business Owners. While most users complete the fields, many are not familiar with EA terminology and sometimes enter conflicting values in related fields.
A common example is:
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TIME = Eliminate
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6R = Retain
We’ve identified a few possible approaches and would like to understand what works best in practice:
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Automation / Rules-based warnings
Using LeanIX automations with defined rulesets to warn users (or block approval) when conflicting combinations are selected. -
User education
Creating and circulating cheat sheets, tooltips, or guidance documents explaining how related fields (TIME, 6R, Business Criticality, etc.) should be aligned. -
Approval-based governance
Relying on Business Owner review and quality seal approval to catch and correct inconsistencies.
Questions to the community:
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Which of these approaches are you using today?
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Have you implemented automated validation or warnings for conflicting field values? If yes, how effective has it been?
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Do users respond better to in-tool guidance (rules, warnings, tooltips) or to offline material (cheat sheets, training)?
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Are there any other patterns or best practices you’ve seen work well to improve data quality without overburdening users?
Our goal is to improve data consistency while keeping LeanIX user-friendly, so any real-world experiences or lessons learned would be greatly appreciated.
Thanks in advance!
