Enterprise Architects are increasingly being asked to design, architect and de-risk more sophisticated and larger investments in data-centric innovation projects and digital data assets (the Data Domain).
More than any other group, Enterprise Architects should be aware of the value of data architecture components such as:
- Master Data Management (MDM)
- Reference Data Management (RDM)
- Data Analytics & Big Data
- Data Governance
- Data Quality Frameworks
- Business Glossary & Metadata Management
- Data Models, Data Business Rules
- Data Visualization & Data Reporting
- Data Warehouse & Data Marts
- Data Integration
These componenets are all subject to the high risk of failure due to poor quality data. This is globally well known and well understood, but often glossed over by IT departments and business cases, often to the frustration of the Enterprise Architect or Data Architect.
Unfortunately what Enterprise Architects are NOT being told is the extent of the incumbent damage caused by existing system/people/process failures that result in approximately 20% of the business workforce being unable to perform their primary job function due to poor quality data. This needs to be explored and the Enterprise Architect really needs to take a proactive, leadership stance in this effort.
Enterprise Architects (and their Data Architect subordinates) often attempt to proactively get involved in shaping or leading Data Governance and Data Quality frameworks to solve for the Data Quality problem. This is normally expected of this role.
However, to date,Enterprise Architects (and their Data Architect subordinates) have had no clear approach to measure this damage (factual metrics at scale, NOT anecdotal measurements), identify the root causes or remediate the commercial damage, which ironically is a funding component of the full list of data architecture component items above.
Worse still, CIO’s and other IT leaders are rarely incentivised or motivated to even measure or pursue the data cleanup effort, as it often exposes the immaturity of the IT leadership, and this can run counter to the efforts of the Enterprise Architect.
Enterprise Architects need visibility and unfettered access to the metrics and facts surrounding the damage of poor quality data, and an understanding of how data is an “engineered-product” that has a specific lifecycle to capture and unlock it’s business value. In turn the Enterprise Architect can politically and financially support their Data Architects in this effort.
It is most likely that a business leader, such as a COO or CFO will drive the ClearDQ engagement to hold the CIO to account, relative to the IT spend velocity and IT project priority. The Enterprise Architect can proactively act as a broker to this value-unlocking process.
CIO’s (and sometimes Enterprise Architects by proxy) may posture against ClearDQ as it swings the “power and control” over digital information squarely away from IT and deep into the business. This is a global trend and not new.
If you are an Enterprise Architect of a commercial (listed or non-listed) enterprise, a not-for-profit or government agency, we’d encourage you to download our briefing paper and arrange a confidential discussion with us to being the journey of repairing the damage to your organisation due to poor quality data.