Ahh… February. An interesting month with a variety of happenings. From the significant – Black History Month and President’s Day, to the exciting – the Super Bowl…well sometimes. From the romantic -Valentine’s Day, to the silly – that tenacious ground hog trying to find his shadow…AGAIN. Not to mention that Spring is just around the corner and brings us the glorious event known as “March Madness!”
Why am I babbling about February? <segue> Because it is also the month that introduced Data Governance and Collaborative Workflows with the release of Enterprise Data Management Cloud Service (EDMCS) v19.02. <segue>
As we continue this journey to Enterprise Performance Management (EPM) Cloud, the addition of Data Governance to EDMCS is a major step forward, especially for those of us who have worked with the classic on-premise solutions (Data Relationship Management (DRM) and Data Relationship Governance (DRG)) and who have been awaiting a similar offering in EDMCS to support our Cloud clients. From what I’ve seen so far, a major gap between DRM/DRG and EDMCS has been addressed with this release.
In this blog series, I’d like to further explore Data Governance in EDMCS. At a high level, this is how I see this series unfolding:
- Part 1 will provide the foundation, background, and basic concepts for EDMCS and Data Governance
- Part 2 will get more into the “techy” stuff and dive deeper into Approval Policies and Security
- Part 3 will provide a recap and closing thoughts/lessons learned
So, with that said, onto Part 1…
Before diving head first into configuring Data Governance and collaborative workflows in EDMCS, there are a few things to consider.
- Don’t forget people and process. I’m a big believer that people and process are just as (and usually much more) important as the tool. Please refer to this blog post for a quick read on this: The Data Governance Triple Crown.
I believe the same tenets apply to EDMCS and that it’s important to start thinking about a formal data governance program that includes a charter, executive sponsorship, roles & responsibilities, metrics, and much more. Data Governance can be a challenging cultural shift for many organizations which requires strong change management to handle the inevitable resistance. This is where a formal data governance framework can help.
- Establish the foundation. As with building a house, it’s important to lay a solid foundation before you install the wiring and plumbing. Build your EDMCS application(s) and dimensions, and populate your primary and alternate hierarchies first. Get the client comfortable with the tool and the content. Then you can start to layer in the workflows.
- Start to identify the “who” (e.g. the people involved and the roles they will play: who will be submitting requests? Who will be approving? Who will do both?
- Start to think about the “what.” What applications/dimensions/hierarchies will be governed? What are the use cases and typical scenarios that require data governance? Start to collaboratively mock up and storyboard some typical workflows with the client to visualize how the workflows will function. And don’t try to build a workflow for every possible scenario. Start with the big hitters and low hanging fruit first. You can always add more workflows later.
What’s Included in EDMCS Workflows?
Are you wondering what EDMCS includes as far as data governance functionality? In summary, EDMCS supports:
- Two types of roles – submitters and approvers
- Separation of duties – workflows can be configured to prevent submitters from approving their own requests
- The “four eyes” principle: EDMCS data governance adheres to the principle that requests must be approved by at least two people
- Default application views and maintenance views: workflows can work with both types of views
- Subscriptions: workflows can be triggered by Subscription requests
- Email-based notifications
- Serial and Parallel approvals:
- Serial approval means a sequential order of approvals is required. For example, Approver #2 can’t approve until Approver #1 approves, Approver #3 can’t approve until Approver #2 approves, and so on.
- Parallel approval means the approvals can occur in any order and at the same time.
- With either method, all approvals must occur before the request is committed.
- Configuration of Reminder and Escalation intervals
- Multiple Workflow Stages:
- Submit – initiate the request and add/edit/delete line items in the request. Note that with the 19.02 release, you can also attach documents and insert comments at the line item level. These enhancements are helpful to attach policies, supporting details, and other documentation related to the workflow request.
- Approve – similar to DRG, an approver can approve, push back, or reject a request. Pushing back will send the request back to the submitter for additional changes. Rejecting will close the request and end the workflow.
- Commit (implied) – once the request is fully approved, it is committed, hierarchies are updated, and the request history can be viewed like any other request.
- Approval Policies – this is really the brains of how workflows are configured in EDMCS, and the next blog post cover this in greater detail. But here is a screenshot of the Approval Policy screen showing the available options:
I hope you found this blog post helpful as an introduction to EDMCS and data governance, and that you will keep reading as the rest of the series is posted. Please contact me with any questions and comments!
And don’t forget to follow me on Twitter (@kblackEPM) and check out/subscribe to my blog (along with the blogs authored by my very talented colleagues at Alithya).
Interested in better understanding EDMCS, the RESTful API, and Cloud Data Management? Be sure to check these excellent blog posts by Tony Scalese, aka FDM Guru: https://ranzal.blog/author/ascalese/
Looking for an outstanding resource for all things master data-related and more? Look no further! https://datarestless.com/