Copyright © 2007, SAS Institute Inc. All rights reserved. The Information Management Roadmap Bill...

Copyright © 2007, SAS Institute Inc. All rights reserved.

The Information Management RoadmapBill Laberis, Host, ComputerworldThornton May, IT Leadership AcademyMark Moorman, SASHenry Morris, IDC


Q&A

Please send your questions using the “Ask a question” text area


Panelists Bill Laberis, Vice President of Customer Content Strategy,

Computerworld

Thornton A. May, Futurist, Executive Director and Dean of the IT Leadership Academy

Mark Moorman, Advisor, Office of the CTO, SAS

Henry Morris, Senior Vice President for IDC’s Worldwide Software and Services Research Groups


Technologies Viewed as Components of Information Management

78%

76%

73%

71%

64%

62%

31%

6%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Other

Enterprise Service Bus(ESB)

Business intelligence

Data storage

Document/contentmanagement

Access, search and delivery

Data/application integration

Data warehousing and datamanagement

Information management is defined in the involvement screener as efforts focused on assessing, monitoring and improving data integrity and the flow of information. This would include data management and data integration efforts as well as business intelligence, analytics and aspects of performance management initiatives.Q6: Which of the following technologies do you view as components of information management? Base: 182


Importance of IM Efforts to Overall IT Strategy

41%

45%

11%

1% 2%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Veryimportant

Important Somewhatimportant

Not veryimportant

Not at allimportant

Q9: Please rate the importance of your organization’s information management efforts to its overall IT strategy. Base: 182

(NET) Very Important/Important = 86%


Key Challenge to Information Management Efforts

4%

3%

4%

5%

7%

18%

18%

20%

21%

0% 5% 10% 15% 20% 25%

Other

Securing executive support

Worker skill sets

Data access

Data quality

Budget contraints

Corporate culture

Standardizing datamanagement processes

Integrating disparatesystems

Q11: What is the key barrier of your organization’s information management efforts? Base: 182


The Information Management Roadmap

What is IM and why should it matter to IT management?

Relationship between IM and operational BI

Leveraging what you already have in place

IM roadmap – getting there from here

© 2007 IDC

Unified Access, Analysis & ManagementUnified Access, Analysis & Management

Structured

Unstructured

Rich Media

Clickstream

Annotations

Video

Audio

Image

ERP

CRM

SCM

HR

PLM

XML

Documents

Spreadsheets

Email

RSS

Forms

ExecutivesManagers

LOB Staff

Suppliers

Partners

Customers

Government

Business Analysts

Quantitative Analysts

Financial Analysts

IT Staff

Web

Industry standards(UCCNet, HL7 SWIFT, FIX)

Unified AccessUnified Access

Semi-structuredUnifiedMgmt

(Policy Hubfor retention,

security,master data

management)

UnifiedMgmt

(Policy Hubfor retention,

security,master data

management)

EnrichedMetadata(Semantic

+Structured)

© 2007 IDC 9

Managing Master Data via a Policy HubManaging Master Data via a Policy Hub

Publish

Collect

Collect

Publish

Publish

Collect

Publish

Collect

Tra

nsa

ctio

nal

Mar

keti

ng

Metadata

Masterdata

Trans.data

Fin

ance

Pro

cure

men

tMetadata

Masterdata

Trans.data

Metadata

Masterdata

Trans.data

DW

Metadata

Masterdata

Trans.data

Metadata

Masterdata

Trans.data

Query & ReportingA

nalytic

Budgeting

Planning

BP

M

Metadata

Masterdata

Trans.data

Metadata

Masterdata

Trans.data

Metadata

Masterdata

Trans.data

Collect

Publish

Collect

POLICY HUB

Master Data:Hierarchies, Rules, Policies, References

Collect

Publish

CollectPublish

Publish

Collaborative

© 2007 IDC

Business Analytics ForecastBusiness Analytics Forecast

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

2005 2006 2007 2008 2009 2010 2011

Performancemanagementtools andapplications -10.7% CAGR

Data warehouseplatform - 9.9%CAGR

10.5% Total CAGR


Unstructured and Semistructured Data The Dark Matter for IT

Structured data Relational databases, structured data files, system/application data and logs that reside in a data store, defined by a catalog (table definitions)/data model accessible via SQL or Object definitions.

This data has a characteristic of being contextualized by the heading (field name) and possibly defined in relation to other "fields.” This data is also capable of being processed in a simple manner, summed or aggregated, etc.

Semistructured data houses structure with freeform elements (e.g., e-mails) and has structure and context to specific elements in the header, but is freeform text in the body. Semistructured data comes in many forms.

Semistructured data is also formed when unstructured data is combined with metadata, making it accessible by search engines via indexing schemas. This is the ideal state for naturally unstructured data within organizations.

Unstructured data Most of the information that resides in organizations is unstructured

in nature – images, content of Web documents, standard

documents, audio, video and correspondence.

This type of information is typically difficult to find

effectively if nothing has been done to make the data

accessible, such as putting it into a content management

system and tagging it with metadata.

70%

25%

5%













© 2007 IDC

Intelligent Process AutomationCombining BI and Business Process ManagementIntelligent Process AutomationCombining BI and Business Process Management

Automating repeatable, operational decisions Roots in operations research (e.g., airlines, supply chain) Continuous in-process, rather than after the fact data integration Agents are knowledge/information workers Integrated collaboration

In response to events Run-time event-driven capabilities, including business activity

monitoring or BAM Event-monitoring triggers process Exception handling (branch of straight-through process) Access to structured and unstructured data in context

Where analytics drives the workflow Predictive models evaluate alternatives Optimization considers risks, probabilities Complex rules definition, review, and execution

© 2007 IDC

More BI Adoption in an OrganizationMore BI Adoption in an Organization













© 2007 IDC

Process Visibility and ComplianceProcess Visibility and Compliance

Source: “ROI, Automation, and the Financial Close Process” (Kathleen Wilhide and Scott Tiazkun, IDC #204604, December 2006).













© 2007 IDC

Towards a Unified View of the CustomerTowards a Unified View of the Customer

Macro Variances

Customer Segmentation

Promotional History

What does the transaction data tell us?

Analytic

Sta

ge

Tw

o

What should the business do?Change the business process

Make changes based on external disruptive influences

Decision

Sta

ge

Th

ree

Make tactical/strategic changes based on analytics

Bu

sin

es

s P

roc

ess

es Im

pa

ct

Who are our customers?

Contact Information

Customer Purchase History

Billing Information

Transaction

Sta

ge

On

e


Five Levels of EvolutionLevel 5: Innovate - Expand top line

Level 4: Optimize - Optimize bottom line

Level 3: Integrate - Enterprise view

Level 2: Consolidate – Departmental silos

Level 1: Operate - Individual focus

Four Critical Dimensions• Human Capital• Knowledge Processes• Culture• Infrastructure

Organizational Readiness Information Evolution Model

Human Capital

Knowledge

Processes

Infrastructure

Culture








Challenge Solution Results

" SAS is helping us make discoveries so that we can address the core issues before they ever become problems – and we can make sure that we are addressing the right causes. We're talking about hundreds of millions of dollars in savings. "

Detect and contain warranty and call center issues before they become widespread.

SAS spots patterns in a wide range of data and text to pinpoint problems early, ensuring safety, quality and customer satisfaction.

Automotive


Q&A

Please send your questions using the “Ask a question” text area



To ask more questions of our presenters, or to request a copy of today’s slides, the written answers to the Q&A, or the list of references for further reading…

Contact Jessica Horton at [email protected]@sas.com


The Information Management RoadmapBill Laberis, Host, ComputerworldThornton May, IT Leadership AcademyMark Moorman, SASHenry Morris, IDC

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