Optimal designOf processes and data governance
Two starting points, one way to the best design.
An existing company starts from its as-built map; a new one starts from its documents. Both go through the same mapping to the best design of their processes and data governance.
The design pathThe same three moves, whichever way you start
Break it down, match it, combine the best.
Follow the gold line from either starting point: buckets of standard processes, matched to the dictionary, combined into the best fit.
- Existing companyStart from the as-builtThe mapped processes and data governance are the starting point.
- New companyStart from company documentsNo as-built yet: we design from the documents, from scratch.
The same mapping for both
- 1Break into bucketsStandard industry processes and data governance.
- 2Map to the dictionaryEach bucket matched to standard processes and data governance.
- 3Mix and matchThe best fit per bucket, even across several industries.
The best design of the corporate processes and the corporate data governance
Best-match engineWhat the design is matched against
Best practice for this company, not a template.
On the left, what the company really does. On the right, what the industry and the state say it should do. The engine meets them in the middle.
A · The company as built
- As-built process map
- As-built data governance
B · What it should be
- ISO
- APQC
- EFQM
- Sovereign and regulatory policies
Best practice for this company
- For processes
- For data governance
Data governanceWhy we design a supply chain, not a data hub
Govern the data supply chain, not a data hub.
A hub stores data in one place and governs it after it lands. A supply chain names an owner at every link and checks quality at every handoff.
Others
Governance as a data hub
“Where is the data, and who can access it?”
- ERP
- WMS
- TMS
- MES
- Finance
- IoT
- Suppliers
- External
- Data treated as an asset at rest, stored in one place
- Governed after it lands: catalog, classify, grant access
- One central team becomes owner, gatekeeper and bottleneck
AIx2
Governance as a data supply chain
“Is the right data flowing, at the right quality, to the right decision, on time?”
- Supply
- ERP / SalesCommercial director
- WMS / TMSLogistics manager
- MES / IoTPlant manager
- Ingest and validate
- Data contract at the handoffData engineering
- Transform and model
- Features, models, rulesData science
- Data products
- API, forecast, optimizerProduct owner
- Consume
- Planning
- Operations
- Partners
- An owner at every link
- A quality gate at each handoff
- Feedback flows upstream to the owner
What you receiveThe outputs of the design
What you hold at the end.
- The best design of your corporate processes, bucket by bucket
- The best design of your data governance, with an owner and a quality gate at every handoff
- Controls and human approval points built into the design