45 lines
2.2 KiB
Markdown
45 lines
2.2 KiB
Markdown
# Verified Impact Evidence Capture
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> Metrics remain unverified until Dennis confirms them. Never estimate or infer a number.
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## Current Verified Qualitative Outcomes
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- Swisscom: production accountability for Fulfillment ETL components, including incidents, data quality, governance and on-call obligations.
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- Swisscom: migrated pipelines in owned domains onto the company's AWS platform as part of a wider programme.
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- Swisscom: promotion from Senior to Staff in April 2025.
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- Bosch: ML inference integration supported automated image-based defect classification and reduced manual classification workload qualitatively.
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- Bosch: Application Owner responsibilities included SLOs, vendors, training and documentation.
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- Generali: introduced BDD through a proof of concept and trained colleagues.
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## Questions to Confirm
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For each answer, provide a number/range, unit, period, source and whether it is safe for a public resume.
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### Swisscom
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- How many pipelines, components, source systems or data products are in your owned scope?
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- How many internal teams or regular stakeholder groups consume the outputs?
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- What SLA/on-call expectations can be stated publicly?
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- Did migration change runtime, failure rate, deployment time, infrastructure effort or operating cost? By how much?
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- How many domains/source systems did you personally migrate or onboard?
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- Is there a defensible before/after example for automation or root-cause resolution?
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### Bosch
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- How many applications or pipelines were in the Application Owner scope?
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- How many users/teams relied on the services or Spotfire environment?
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- Can the reduction in manual classification be expressed as a percentage, hours, cases or qualitative-only statement?
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- What deployment frequency, availability target or incident responsibility is safe to disclose?
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- Did the monitoring PoC find a concrete anomaly or change an operational decision?
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### Earlier Roles
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- Did Jenkins/BDD/test automation measurably change build time, release frequency, defect detection or manual work?
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- Is there verified adoption, user count or team count for any earlier tool?
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## Evidence Record Template
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| Claim ID | Metric/result | Value or range | Period | Source | Public? | Verified date |
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|---|---|---|---|---|---|---|
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