Conni Christensen - Automating Information Governance: What's Holding Us Back? - The Information Governance Conference 2014 - #InfoGov14
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The document discusses automating records management and information governance. While other business processes have been automated through technologies like ERP and CRM, records management remains labor-intensive. The document outlines some of the challenges preventing automation, including a lack of consistent metadata standards and methodologies. It also presents some solutions for intelligent data capture and management, such as using metadata modeling and data flow analysis based on business activity.
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Conni Christensen - Automating Information Governance: What's Holding Us Back? - The Information Governance Conference 2014 - #InfoGov14
- 1. Conni Christensen Founding Partner The Synercon Group Automating Information Governance What’s holding us back?
- 2. We live in a world of technology where process automation is the norm. So why, in 2014, is records management still a labour intensive process? What’s preventing us from automating recordkeeping practices?
- 3. Automation
- 4. The state we’re in Random adjective lacking any definite plan or prearranged order; haphazard at random in a purposeless fashion; not following any prearranged order Synonyms haphazard, chance, fortuitous.
- 5. Banking and Insurance Enterprise Resource Planning Accounting Human Resources Customer Relationship Management
- 6. Metadata is what makes it happen Metho-dologies Metadata Stan-dards Connec -tions
- 7. Methodologies ISO 15489 Retention schedules Analysis of Business Activity Classification Functional Faceted
- 8. Metadata standards Data structure standards Data value standards Data content standards Data interchange standards
- 9. Metadata connections Metadata modelling Data flow modelling
- 11. Based on Business Activity Analysis Mandates Stakeholders Records Classes & Disposition rules Activities Transactions Functions Processes Subject taxonomies Agents Record / document types Recordkeeping obligations
- 12. Data is intended for reading by machines, documents are intended for reading by humans Marcus Clark 2013
- 14. Conni Christensen @akabysynercon Conni@synercon.co www.synercon.co/insights www.a-k-a.co
Editor's Notes
- Automation refers to the automatic operation or control of equipment, a process, or a system. Things happen without manual input The biggest benefit of automation is that it saves labour, saves energy and materials, improves quality, accuracy and precision. But are we in a position to automate? We need to examine: The state of our Systems The state of our Instruments, and The state of our people
- Our industry is suffering from extreme randomness
- Hyperlink to accounts receivable process We could start by comparing electronic records management systems with highly automated business systems, such as accounting and enterprise resource planning By studying successful systems, we can better understand which design and functionality features will allow us to effectively automate recordkeeping processes such as appraisal, capture, retention and disposal.
- It’s all about metadata and how it’s standardised and connected. All of the metadata and relationships between data items is already set up in the system. Accounting and ERP systems show us that complex processes can be successfully automated. Furthermore these systems are set up in order to maintain rigour, accuracy, consistency and authenticity of data. Compliance is inbuilt into the system. We can learn from this in building recordkeeping compliance into information systems.
- Some we have already identified Some we are borrowing from other disciplines. Need to pull it altogether
- Standardisation enables connectivity - sharing and interoperability
- Building a better understanding of how to
- Synercon is currently undertaking a project with the National Archives of Australia to redesign disposal authorities to support automated (defensible) retention A metadata based approach is being followed. The first stage is to identify and capture sets keywords used by the business to describe and manage their information. For example: document types, processes, transactions, subjects, agents, publication status etc. Most agencies will already have metadata sets established throughout their systems – as process maps and workflows, data dictionaries, controlled lists, lookup sets etc. The second stage is to determine the significance of the metadata values either individually or in combination and link these to retention rules. The third stage is to appraise document sets using text analytics The race is on. We want to be first.
- If you want to follow the action, then connect with me on Linkedin or twitter, or follow my blog. Or go to our websites to read more. I’ll be around if you want to meet and chat.