Through-out his career Seth Earley has been passionate about the crucial role of information management would play in a world hurtling toward digital transformation. He provides challenging insights to executives who are tasked with leading their organizations forward in an age in which the digital experience offered to customers determines the winner.As CEO of Earley Information Science, a consulting firm he founded over 20 years ago, Seth guides some of the worlds most recognized brands on how to leverage their information assets to deliver state of the art customer experiences through integrated enterprise architectures. Seth has a long history of industry education and research in emerging fields. His current work covers cognitive computing, knowledge engineering, data management systems, taxonomy, ontology and metadata governance strategies.Seth Earley is a sought-after speaker, writer, and influencer. His writing has appeared in IT Professional Magazine from the IEEE where, as former editor, he wrote a regular column on data analytics and information access issues and trends. He has also contributed to the Harvard Business Review, CMSWire, Journal of Applied Marketing Analytics, and he co-authored “Practical Knowledge Management” from IBM Press and his new book "The AI Powered Enterprise" recently won the Axiom Silver Medal for books on business and AI.
Organizations have understood the value of their structured data - mostly financial transactions ... more Organizations have understood the value of their structured data - mostly financial transactions - since the first mainframes were developed in the 40's. Data quality issues have always been a challenge and the increasing numbers of applications consuming and producing structured transactional data has grown exponentially. Unstructured information has been given less significance and strategic importance and therefore fewer resources and less attention on the part of leadership. All of that has changed and is changing faster than anyone imagined. Unstructured content is what humans produce. They create the documents: strategies, proposals, support documents, marketing content, white papers, engineering specifications, etc. that form the intelligence and core knowledge capital of the enterprise. Many organizations have left business units to fend for themselves and “go figure it out” with little guidance or support. These has led to terabytes of content that people cannot find their way through and that leaves the organization open to risks, liabilities and costs of e discovery. According to the Minnesota Journal of Law, Science & Technology, a gig of data costs $30,000 in e discovery costs. The cost of storage is ten cents. The problem is that the enterprise does not understand the hidden costs of not making data accessible and usable - lost time, lost IP, inefficiency, poor customer service that can lead to lost customers, slower growth, etc. As newer collaboration technologies are deployed, they expose the bad habits and sins of the past. Deploying a new search engine shows that the content is not curated. Standing up a new content management application like SharePoint reveals the haphazard shanty town of an information architecture with inconsistencies in models, terminology and applications. Today's landscape of marketing and customer experience technologies is complex and interconnected and requires those upstream knowledge processes that produce unstructured content as the fuel. Customer experience entails everything that happens before you purchase (marketing, education and outreach), when you purchase (e commerce with product content and data), and after you purchase (self-service systems and knowledge bases that support the call center). This is the customer lifecycle and at each step in the process systems and tools need to be harmonized as they gather information about the users using attribute models that are consistent and that serve the business and the customer. They take content and data as input and then output more data. One applications exhaust is another applications fuel. Organizations are also purchasing data streams to enrich their internal information sources. Social media is an enormous virtually untapped reservoir of data about customers and what they think about organizations. This can be mined for sentiment and to gauge marketing effectiveness. Increasingly, much of this is being placed into the hands of the marketing organization. In fact, a study by Gartner Group said that by 2017 the CMO will spend more money on IT than the CIO. What all of this means is that information, content and data governance need to be considered as part of a whole and not as separate initiatives. Elements of good information governance include: Deployment and Operationalization; Alignment with User Needs; Business Value; Buy-In and Change Management; Sponsorship and Accountability Leads to the following outcomes: Manages conflicts in business priorities (between initiatives, business units, drivers, etc); Allows for ongoing input from various stakeholders and constituencies in order to evolve capabilities with the needs of the business; Prioritizes efforts and allocation of resources; Assigns roles and responsibilities with accountability to critical functions; Takes into consideration various levels of maturity in the organization - no one size fits all; Ensures that investments in systems, processes and tools are providing sufficient return to the business; Balances centralized standards with decentralized decision making; Aligns incentives to use a system with business goals This session will review governance concepts, discuss how they apply to various types of data and content and provide a framework for developing governance processes and structures.
• Governance requires a strategic perspective aligned with business objectives • Senior managemen... more • Governance requires a strategic perspective aligned with business objectives • Senior management participation is essential for success • Governance standards need to be operationalized through clear policies and procedures with metrics and compliance mechanisms • Governance programs need to include a roadmap for continuous improvement • The business value orientation supports specific capabilities rather than functional silos • More information at www.earley.com • https://www.earley.com/knowledge/articles/developing-content-maintenance-and-governance-strategy • https://www.earley.com/blog/making-case-taxonomy-governance.
Information governance does not typically receive the needed attention and resources from organiz... more Information governance does not typically receive the needed attention and resources from organizational leadership. By linking information governance efforts to data and process metrics frameworks, the value of these efforts can be made more evident to stakeholders.
This article discusses the increasing sophistication of search technology and its role in cogniti... more This article discusses the increasing sophistication of search technology and its role in cognitive computing. It provides a concrete example of a personal assistant that is context-aware and can retrieve the information most likely to solve users' problems. It also addresses how search engines predict what information users are likely to need, and how the software retrieves and presents the information. Finally, the article discusses personalization and how machine learning can contribute to this process.
Organizations have understood the value of their structured data - mostly financial transactions ... more Organizations have understood the value of their structured data - mostly financial transactions - since the first mainframes were developed in the 40's. Data quality issues have always been a challenge and the increasing numbers of applications consuming and producing structured transactional data has grown exponentially. Unstructured information has been given less significance and strategic importance and therefore fewer resources and less attention on the part of leadership. All of that has changed and is changing faster than anyone imagined. Unstructured content is what humans produce. They create the documents: strategies, proposals, support documents, marketing content, white papers, engineering specifications, etc. that form the intelligence and core knowledge capital of the enterprise. Many organizations have left business units to fend for themselves and “go figure it out” with little guidance or support. These has led to terabytes of content that people cannot find their way through and that leaves the organization open to risks, liabilities and costs of e discovery. According to the Minnesota Journal of Law, Science & Technology, a gig of data costs $30,000 in e discovery costs. The cost of storage is ten cents. The problem is that the enterprise does not understand the hidden costs of not making data accessible and usable - lost time, lost IP, inefficiency, poor customer service that can lead to lost customers, slower growth, etc. As newer collaboration technologies are deployed, they expose the bad habits and sins of the past. Deploying a new search engine shows that the content is not curated. Standing up a new content management application like SharePoint reveals the haphazard shanty town of an information architecture with inconsistencies in models, terminology and applications. Today's landscape of marketing and customer experience technologies is complex and interconnected and requires those upstream knowledge processes that produce unstructured content as the fuel. Customer experience entails everything that happens before you purchase (marketing, education and outreach), when you purchase (e commerce with product content and data), and after you purchase (self-service systems and knowledge bases that support the call center). This is the customer lifecycle and at each step in the process systems and tools need to be harmonized as they gather information about the users using attribute models that are consistent and that serve the business and the customer. They take content and data as input and then output more data. One applications exhaust is another applications fuel. Organizations are also purchasing data streams to enrich their internal information sources. Social media is an enormous virtually untapped reservoir of data about customers and what they think about organizations. This can be mined for sentiment and to gauge marketing effectiveness. Increasingly, much of this is being placed into the hands of the marketing organization. In fact, a study by Gartner Group said that by 2017 the CMO will spend more money on IT than the CIO. What all of this means is that information, content and data governance need to be considered as part of a whole and not as separate initiatives. Elements of good information governance include: Deployment and Operationalization; Alignment with User Needs; Business Value; Buy-In and Change Management; Sponsorship and Accountability Leads to the following outcomes: Manages conflicts in business priorities (between initiatives, business units, drivers, etc); Allows for ongoing input from various stakeholders and constituencies in order to evolve capabilities with the needs of the business; Prioritizes efforts and allocation of resources; Assigns roles and responsibilities with accountability to critical functions; Takes into consideration various levels of maturity in the organization - no one size fits all; Ensures that investments in systems, processes and tools are providing sufficient return to the business; Balances centralized standards with decentralized decision making; Aligns incentives to use a system with business goals This session will review governance concepts, discuss how they apply to various types of data and content and provide a framework for developing governance processes and structures.
• Governance requires a strategic perspective aligned with business objectives • Senior managemen... more • Governance requires a strategic perspective aligned with business objectives • Senior management participation is essential for success • Governance standards need to be operationalized through clear policies and procedures with metrics and compliance mechanisms • Governance programs need to include a roadmap for continuous improvement • The business value orientation supports specific capabilities rather than functional silos • More information at www.earley.com • https://www.earley.com/knowledge/articles/developing-content-maintenance-and-governance-strategy • https://www.earley.com/blog/making-case-taxonomy-governance.
Information governance does not typically receive the needed attention and resources from organiz... more Information governance does not typically receive the needed attention and resources from organizational leadership. By linking information governance efforts to data and process metrics frameworks, the value of these efforts can be made more evident to stakeholders.
This article discusses the increasing sophistication of search technology and its role in cogniti... more This article discusses the increasing sophistication of search technology and its role in cognitive computing. It provides a concrete example of a personal assistant that is context-aware and can retrieve the information most likely to solve users' problems. It also addresses how search engines predict what information users are likely to need, and how the software retrieves and presents the information. Finally, the article discusses personalization and how machine learning can contribute to this process.
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