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  Data Quality Program DMA  

ENCYCLOPEDIA→   Enterprise Intelligence  →   -  Data Quality  →   -  Data Quality Program  → 

Data Quality Program Initiation

Data Quality Program initiation & Scoping is similar to a typical project initiation phase. This phase includes a project trigger, identifying sponsor, project manager, information gathering and finally coming-up with signed-off project agreement. Due to various reasons mentioned in the topic, objective of this phase is mainly to get the sponsorship for analyze phase, so get a clarity on the plan and costs.

Project Initiation phase for a Data Quality Program is different from a typical project. The primary target here is not to get the commitment for the entire project. The goal here is to look for funding for analyze phase. Typically a high confidence estimate & plan is expected at ‘Project Initiation Stage’ . This works for projects (like implementing SAP, implementing a CRM initiative..) as they are related to something new and have similar implementations at other sites.

The Data quality program is mostly related to changes in the existing set-up and most of them not structural , but at the lower level of processes. Secondly, the changes needed are very specific to the given organization, and one cannot use a parallel to do a good estimation. The other reason is that the whole approach of the data quality initiative will be dependent upon what you discover in the analyze phase. Unlike a typical systems initiative, one cannot predict the underlying issues and scope unless one does a relatively detailed assessment of the quality of data and its root cause

Therefore a project initiation phase in a Data Quality Program will be mainly to get the sponsorship for the analysis phase. A high level approach and estimate of the entire program is definitely part of the project agreement (an outcome of the initiation phase), the stakeholders should be ready for a sizeable change post analysis.

The stages of the Data Quality Program initiation phase are:

Project Trigger:

A data quality program gets triggered, when company has gone through Data- quality crisis, OR audit has given an adverse report, OR in a rare case due to pro-active step by management.

Identifying a Data Quality Program sponsor:

A senior business manager, who has a strong stake in the process. One should try to make the CEO OR functional head as the sponsor for best outcome. CFO OR Head of internal control may not be the best choices, as it dilutes the sense of ownership from the business managers. A sponsor provides the direction and resources for the initiative, and ensures that it keeps its rightful place in the priorities list.

Identifying the project manager:

A project manager is responsible for successful execution of entire project life cycle. The project manager is chosen in terms of the his/her stake in the initiative, project management skills, relevant subject matter expertise.

Understanding Data & Information Quality/Benchmarks:

One needs to know at a high level on which data is important and what is the quality benchmark is needed. This information guides the Data Mapping & Assessment exercise in the Analysis Phase.

Please note that this assessment is done at a high level and also mostly in the back-ground. You really cannot afford to go to each data customer (the internal functions using the data) for his/her quality requirements. 99.9% of the customers will need 100% quality. One needs to use the diverse domain experts to come to an assessment of quality requirements.

Define the scope of the data quality program:

Data quality program typically focuses on a certain section of an enterprise. This is driven by the criticality of the data OR visible issues. (For example- Data quality of all field operations OR distribution data OR data quality of all user administration and set-up data..)

Define a high level state and gaps on Data Quality-

This is done at a high level. Following are the pointers (which are also used in the analysis phase):

  • Customer complaints.
  • Production Defects.
  • Internal control/audit remarks.
  • Interview with some business heads and CIO.

Define high level data quality approach-

This is generated applying the broad principles. The data quality approach is firmed-up only after the analysis phase. Typically at the initiation stage, the top two OR three items (..improving the data capture process at front-office, one time review and clean-up for entire agents data..) are listed and some general principles (onetime clean-up of critical data..)

Detailed plan for analysis phase and high level plan for entire project.

(Details along with a template of WBS for DQ Analysis phase plan will be added later)

Estimated cost for analysis phase and overall high level cost (optional) for the entire program.

(Details along with a template of WBS for DQ Analysis phase plan will be added later)

The combined output of all of the above is in form of a ‘project agreement’.

(Details along with a template of WBS for DQ Analysis phase plan will be added later)

 

  Data Quality Program DMA  
 
 
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