MDM Implementation Service

To implement a successful MDM solution in a sustainable, repeatable, scalable, and supportable manner, D3Clarity uses an agile, use case focused approach. The objective is delivering rapid, measurable, business results in a predictable time frame or failing fast on use cases that lack required supporting data sets or quality within those data sets. This approach enables clients to validate ROI quickly and continually re-validate the business case for further solution expansion (i.e., integration expansion). Applying an agile approach has proven to be highly successful and is a direct result of our look-back analyses of MDM and data quality deployments that have gone right and wrong over the last 20 years. These learnings contribute to shorter implementation times and much higher adoption rates. The result achieves business benefits in tangible, measurable ways as quickly as possible and as thoroughly as required.

A typical D3Clarity MDM implementation plan consists of the following scope elements, although delivery style and scope can be customized to meet other preferred methods and/or schedules:

1. Solution Management and Project Kickoff

Within an agile methodology, requirements and solution development will occur through an iterative process and collaborative effort. The detailed tasks per sprint will be identified during each sprint planning meeting.  D3Clarity’s Solution Manager, in partnership with your project manager, shall develop and maintain an agile storyboard for tracking requirements, action items, risks and issues, development process, and feedback requests.

2. Discovery Workshops

Every implementation begins with a Discovery phase included in the overall project. The discovery workshops aim to define and understand the MDM requirements within your framework to make key decisions for the initial configuration, finalize requirements and overall project impact.  The goal is not to have every detailed requirement outlined, as additional requirement clarification activities will occur during each sprint cycle.  This discovery methodology accelerates the overall adoption of the solution and quickly identifies gaps to address sooner rather than later as part of a management of change process.

3. Implementation

During each sprint, data is profiled, modeled, match rules and business validations are applied and tested. At the completion of each sprint, client feedback is provided, and the sprint cycle would repeat either for that same data source and/or a new integration source, depending on the feedback.

As modeling matures, the data source moves into a workflow and user interface development cycle through additional sprints.

The sprint cycle continues for a set number of iterations based on the initial number of phases/sources identified.

Your subject matter experts participate collaboratively throughout the project lifecycle.

Installation is included in scope (either on-prem or within a cloud environment).

4. Knowledge Transfer

The client team is engaged during the entire engagement to ensure that the team has sufficient knowledge and capability to continue to grow and use the solution after implementation.

5. Deployment

After the accepted testing cycles have been completed, the final approved solution functionality is deployed to the production environment, and a maintenance approach is put in place with the team that is responsible for support. 

6. Hyper-Care

Several hyper-care activities are accomplished throughout the project lifecycle and immediately after deployment (i.e., post go-live support for break fixes, runbooks, and deliverables).