A Guide to Measuring Data Quality for Purchased Product Master – Part 2
This is Part 2 of a 2 part blog post. Read Part 1 on A Guide to Measuring Data Quality for Purchased Product Master – Part 1
In my previous post I outlined some metrics for the purchased product / material master – both objective measures (like completeness, accuracy, and timeliness) and qualitative measures – attributes and attribute values that add practical business value to material management, engineering and strategic sourcing teams.
I left off stating the emerging challenge for the Chief Data Officer – or the executive champion responsible for the Purchased Product / Material Master – is to collaborate with the data consumers to define acceptable measurements and levels.
Data Consumers for the PP or Material Master vary consistently (this is not an oxymoron) based on the business of the company. Different types of consumers will have different requirements and the responsibility for success changes with each data type / consumer type pairing.
For simplicity’s sake let’s break the world into 4 types of companies:
- Discrete Manufacturing
- Process Manufacturing
- Distribution / Wholesale
- Field Services
And divide the broad definition of Purchased Products / Material Masters into 4 sub-types
- Off the shelf OBCD Parts for Finished Products
- Engineered to Specification parts for Finished Products
- Off the shelf Maintenance, Repair and Overhaul parts (and spares)
- Fabricated / Machined components for Operations and Maintenance
And group Data Consumers into 3 categories of stakeholders
- Procurement / Strategic Sourcing
Each Consumer will have a different sense of ownership for successful data management practices. Noticeably, Engineering and Operations will have the most interest in Engineered or Fabricated components. They will also have the greatest vested interest in attribute mapping, attribute value completion and of course completeness. The challenge is identifying those key individuals who may have access to tribal knowledge in cases where the technical attributes and characteristics are not currently captured in maintenance (operations) or PDM/PLM systems (Engineering).
The table below shows the primary Data Consumer
In my next post we will cover the key measures and levels acceptable to each consumer across these areas.
White Paper – Empower end-users with Master Data Management
Latest posts by Arthur Raguette (see all)
- The need for effective Material Master Data Management – Part 2 - January 16, 2018
- The need for effective Material Master Data Management - January 4, 2018
- Material Master Data Governance Teams - December 26, 2017