Ontology And Business Value John Yanosy 20110217

1,016 views
954 views

Published on

Presentation made on Business Value Model for Ontologies at Ontology Summit 2011 by John A Yanosy Jr

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
1,016
On SlideShare
0
From Embeds
0
Number of Embeds
17
Actions
Shares
0
Downloads
4
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Ontology And Business Value John Yanosy 20110217

  1. 1. Ontology and Business Value Track 3: Value Metrics, Value Models & the Value Proposition John A. Yanosy Jr. jayanosy@rockwellcollins.com 972-705-1807 Feb 17, 2011 1
  2. 2. Context and Presentation Goal• Context: Examples, not a comprehensive treatment of all business areas impacted by development and application of ontologies• Goal: Identify elements of a value model comprised of exemplary business areas impact of use of ontologies 2
  3. 3. Business Areas Affected by Enterprise Ontology 2. Extensible Business Model 3. Enables Actionable Representing Knowledge of Business Intelligence Operations Knowledge 4. Detection, Representation1. Common Understanding of and Reasoning of ComplexEnterprise Shared Information Business Events 5. Collaborative Operations & Processes enabled by Interoperable Exchange of 6. Extensible Ecology of New Consistent Ontology Interoperable Services Utilizing Information Subsets of Enterprise Ontology 3
  4. 4. Value Model - Ontology and Business Area Relationships 2. Business Model (Customer Satisfaction) 1. Common 3. Actionable Business IntelligenceUnderstanding (Accuracy, Comprehensiveness, Relevant) &Interoperability 4. Complex Business Events (Ontologies) (Accuracy, Composability) Metric: % Consistent 5. Collaborative Operations% Interoperable (Errors, Resource utilization, Supply Chain) 6. Interoperable Business Services (Value to enterprise, Reuse in Workflows) 4
  5. 5. 1. Common Understanding of Enterprise Shared Information• Enterprise level ontologies enable interoperability and consistent understanding of shared information across enterprise model consisting of workflows, actionable intelligence, complex events, operations, and services• Metrics of success include: – % of organization business elements such as workflows and collaborative processes and services compliant with enterprise ontologies 5
  6. 6. 2. Business Model• Better understanding of business model entities and external dependency relationships, i.e., customers, market conditions, products and services offered, internal operations, etc.• Customer Impacts – Increased customer satisfaction of due to improved customer knowledge (CRM) 6
  7. 7. 3. Actionable Business Intelligence• Enterprise Ontology enables improved knowledge and reasoning of relevant extraction and analysis of external market events• Mapping and merging of information into a common ontology from all supporting organizations across the enterprise enable more comprehensive and accurate knowledge of business performance 7
  8. 8. 4. Complex Business Events• Ability to evolve knowledge of complex business events enables the enterprise to adapt to changing conditions by combining and leveraging expertise of individual organizations• Individual organization events can be combined to create new complex enterprise level business events that inform business level intelligence 8
  9. 9. 5. Collaborative Business Operations• Common ontology elements and models reduce errors of interpretation for workflows and processes• Improved understanding of workflow information exchanges, events, and dependencies between different enterprise organization processes• Supply Chain Information improvements resulting in lower inventory, increased resource utilization, faster and more accurate order fulfillment 9
  10. 10. 6. Interoperable Business Services• Improved knowledge and understanding of value added services offered by each organization sales, marketing, manufacturing, engineering to the enterprise• Improved service interoperability due to common enterprise vocabulary, data element definitions, and interpretation from each enterprise organization’s perspective 10

×