October 15, 2012 -- The 2012 Master Data Management and Data Governance Summit is under way at the Marriott Marquis in midtown Manhattan.

8:00 a.m. Conference convenes with keynote from Aaron Zornes. Highlighted themes:

- Big data is a global business strategy, not a refresh.
- We’re coming out of a freeze in large project MDM spending that also involved entrenchment of data governance into organizations and eventually products.
- Organizations are moving past just CDI and PIM to embrace reference data management and broad use of data governance.
- MDM is proliferating innate to applications as opposed to standalone purchases to the point of being “free” (as Microsoft has embedded MDM in SQL Server).
- Now MDM & data governance needs to evolve past point products to enterprise. The overlap between PIM (supplier) and CDI already exist.
- Expect MDM enabled apps to migrate to public clouds especially for decentralized/geographically distributed organizations.

9 a.m. Keynote from Sriraj Rajaram MDM practice lead, Naveen Sharma, MDM solutions architect, from Cognizant

-New paradigm evolves from customer relationship management to customer managed relationship (CMR). In the case of CRM, events flow from enterprise to customer. In CMR, control shifts from enterprise to customer. Organizations are struggling to confront this and constructing systems for BMP, MDM but they lack an integrated strategy, which is CMR. Inward messages to tnterprises are being lost and not processed or connected to business activities.

 - The traditionally fragmented view of the customer has actually gotten worse. We have views coming in through traditional field CRM channel, to social media, to big data, where MDM can intervene and plug together with integrated view, coordinated message, decision process, business efficiency - it brings the customer closer and drives customer engagement.

 - More complaints will become common and will become visible via corporate and social channels like Twitter. Organizations can intercede and connect unstructured information to processes and improve operations with analytics.

- From people/process/technology, we evolve to process, data, governance, engagement. Engagement is the goal and end state.

- Cloud helps migrate from capital expense to operating expense, is outcome oriented, quicker.

10:45 a.m. Keynote from Carl Caruso, director of enterprise data management, Claude Viman, manager of NA enterprise master data, J&J Consumer Companies

- At J&J Consumer Companies the story is not big data, it is about modeling corporate data for 1) accuracy, and 2) timeliness. Central master data reports to supply chain and seeks common regional processes via centralized governance.

Caruso: Assuming you have an acceptable organizational model, before you can get to data quality, you need to have stable business processes and systems; they need to meet the requirements of the business (they have to manage change); and they need processes for retiring data.

- Using on demand reports for data quality is not a recipe for success. A data quality program embeds data quality checks into every step of the data lifecycle. Data needs to be checked at creation for validity; needs to be tested at all points it is promoted for use; same tests need to run against the entire list of active materials.   

2:00 p.m. Session with Express Scripts: Building a Business-Drven MDM/DG Program
Joe Federer, sr. director, PharmacoAnalytics, Elisa Pirylis, sr. manager, patient data steward

Mission of DG is to protect and improve data assets, make sound data practices a force of habit. Specific goals include accountability, responsibility; protection against misuse; monitoring; consistent enterprise definitions and management; ready access to information about the program.To get value, message, success out to users and stakeholders and senior management, built a fully functional intranet devoted to data governance.

See also, "When Mergers Meet MDM and Data Governance"

2:00p.m. A Quick-Start Guide from MDM Vendor Evaluation to Go-LiveSofia Hennay, director of MDM at Stryker, Tina McNeil, senior project manager at Stryker, and Ed Alburn, president and CEO of DataDeltaDue to U.S. health care regulation, Stryker needed to quickly implement MDM during 2011. In addition to the short time frame, they faced challenges of moving to a shared services environment and improving the capture of richer data with less effort.The primary lessons learned •The sooner the data governance structure can be set, the better•Executive leadership is critical•Building buzz around master data pays off•Have the right resources in place•Quarterly presentations are key to support down the road.2:00p.m. A Quick-Start Guide from MDM Vendor Evaluation to Go-Live

Sofia Hennay, director of MDM at Stryker, Tina McNeil, senior project manager at Stryker, and Ed Alburn, president and CEO of DataDelta

Due to U.S. health care regulations, Stryker needed to quickly implement MDM during 2011. In addition to the short time frame, they faced challenges of moving to a shared services environment and improving the capture of richer data with less effort.

The primary lessons learned at Stryker:

  • The sooner the data governance structure can be set, the better.
  • Executive leadership is critical.
  • Building buzz around master data pays off.
  • Have the right resources in place.
  • Quarterly presentations are key to support down the road.

 
4:15 Best Practices: Orchestrating a Roadmap from Reference Data to MDM

Donna Capella, project manager at Great American Insurance Group.

Donna states: “MDM is not a tool… MDM is a framework.”

The lessons learned so far:

Don’t: 

  • Overlook data governance
  • Implement scrum without coaching the full MDM team
  • Overlook what management buy-in really means at your company

Do: 

  • Get team training
  • Define the roles/responsibilities
  • Consider maturity models

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