Brief intro – I have 30+ years of IT experience and spent the last 25 years working at Merck & Co., Inc. in the US. During this time, I’ve collaborated with various business groups, including manufacturing, distribution and logistics, accounts payable, procurement, and human resources. However, the focus of this blog is on the last seven years, where I’ve been responsible for establishing and running a department dedicated to governing the decommissioning and retirement of IT applications.
Our team consists of specialists from diverse IT disciplines, including data analytics, validation and compliance, integration and data migration, Agile consulting, and data science. Our mission is to ensure that the company’s data assets remain secure, locatable and consumable throughout their entire retention period, which can span decades. We work across all divisions, requiring a deep understanding of both modern and legacy technologies. We also navigate the complex intersection of data governance, technology, and legal requirements while balancing cost and risk for the company. It’s a highly talented, skilled, and effective group.
OK, OK … I’m not fooling anyone —we’re the IT garbagemen.
The intent of the blog is to share my thoughts and experiences on a variety of challenges that we face in the process of decommissioning and retiring applications and archiving their data. Working in the Life Science industry we have strict regulations to meet in terms of data preservation, with a higher bar than many other industries. This affects some of the cost/benefit calculations that have to be considered in terms of data retention and presentation, but many of the challenges will be common across all industries.
Time permitting these are some of the topics I plan to cover:
- Data governance experts masquerading as IT garbagemen
- The challenges of divorcing from a SaaS vendor
- What does good data governance look like?
- Best practices – archive entire applications or only the needed data?
- Risks of maintaining technical debt versus the cost of archiving
- Access management to data archives.
- Using standard ERP archiving blueprints
- Rules for what can be archived and the transfer of stewardship for archived assets
- Zombie applications … when the business wants to keep dead applications alive
- Getting political – the best example of bad data governance and the consequences
- Live archiving and good data governance
- Live archiving versus dormant application archiving
- Delivering value through good data planning and architecture
- Creating a cost containment plan for the end of the application’s life.
- The challenge of unclaimed, unstructured data
- The potential role of AI in data archiving
- SaaS revisited … building good data governance by design
- Virtualization and other techniques
- Orphaned applications – how to deal the applications everyone has forgotten
- The challenges of governing data from M&A activity
- Data privacy obligations for archived data
- Importance of sponsorship for the Garbagemen function
- Structure of the Garbagemen organization
- Running out the clock – avoiding the cost of archiving by keeping applications running
- The backup fallacy
