Information Management - Point of View

What type of data problem to solve?

• Product

• Is an asset, “a thing”

• Has versions, specifications

• Control

• Is automated rules

• Has interactions, by some attribute rules, (events and process management)

• Has events, status, decisions to make e.g. process out of SPC control, change behaviour

• Knowledge

• Tacit

• Is held in different locations and formats

Underpinning this

• Description of data

• Systems, scalability

• Management of data

• Volume and frequency

Value of information

Central to all this is the value of information

• Explicit value

• of transactions (actions taken) and assets (including knowledge)

• Implicit value

• Of insight, decisions and relationships

Value of data

• Customer experience

• Multi content

• Multi channel

• Customer branding

• Image and timeliness

• Right time, right place

• Better decision quality

• Better data sources – aggregated to point of use (not just visibility and access but purposeful use)

Data centric problems

• Data discovery and rediscovery

• Duplicating events / data

• Loss of information decision quality

• Non conformance

• Multiple process rules to create some data

• “ Take two approaches to create product specification and get two different answers – which is right? Which is the correct product specification ? “

This in particular is one of the core problems of business that information management seeks to resolve.

Identify “the right version of the truth”

The correct master data and the correct business rules logical.

Structured and unstructured data

• Structured data

• Has meta data,

• Is managed as an asset

• Has parameters

• Is processed

• Unstructured data

• Does not have specification

• You deploy it e.g. huge document

• Needs description and indexing

A view put forward by one IM consultant was that ESB is about structured data (?), and BPM is about managing unstructured data / document management. This is not so clear in that BPM is about invoking transactional event but could equally call document management solutions that manage unstructured data. Equally, an ESB can have FTP connectors or call large CAD or other image data with the appropriate connectors.

Enterprise Content Management (ECM) / Information Management (IM) solution space

• Enterprise Content Management (ECM)

• Data sync

• Data quality management (DQM)

• Business Intelligence (BI)

• Data Translation

• Data Transformation

• Knowledge management (KM)

• Search, desktop, mining

• Document imaging

• Digital rights management

• Data warehousing (DW)

• Data Mart (DM) - KPIs

• Enterprise Information Integration (EII)

• Master Data Management (MDM)

• DCM

• DRM (Digital rights management)

• DAM (Digital assets management)

• SOA

• SDK tools to control, visibility, reuse

• Vision – C level

• Customer channel access

• Security

• Data Aggregation

• Collaboration

• Multi-channel

• Mobile

• Reporting, query

• Syndication

• Standards, EAB, MDA , XML, SOA, WSDL, UDDI etc

Messages to market

• Get ready for supply chain management

• Get ready for Service oriented architecture

• System of record

• Master data coordination

“Data owners” versus “data users”

Not the same thing

Define once, use many

Governance of

• Rules

• Data owners

Loss of procedures

Lack of visibility of data

IM characteristics in Industry sectors - different problems

• Pharmaceutical industry

• Many FDA legal requirements

• Many trials and procedures

• Huge document audit trails

• “Complex document library” – large assets document management issues

• Legal issues to trace document

• Media industry

• “Digital products”

• Digital content delivery

• Collection of consumer data and behaviours

• New business models (content experience) – data delivery models, e.g. content online

• eBOM / Engineering Industry

• Product specification – structured data

• Image specification

• Processes to follow tight document lifecycle

• A document meta states management problem: to create data (and then throw it away”; to change data

IT Characteristics for IM

• Aim for infrastructure to be agnostic

• Data standards

• Service contracts (Logical information exchange contracts)

• Combining content and transactions

• Centralised (DW/DM) versus federated (DW/DM)

Strategic focus

• Which vertical markets ?

• What horizontal capabilities ?

• Which geographical markets

• What service offering to verticals/ horizontals

• Must be commercially oriented

• Short termist in value initiation

• Sustainable in execution

• Flexible and easy to do business with

• Many paths but specific depth in competency that is competitive

• Clear communication skills and positioning

• Track record in delivery

TOGAF

• Vision

• Business architecture

• Information management architecture

• Technical infrastructure framework

• Domain architecture(s)

What business problems to target

• Customer content – digital media

• Customer service – KM

• Organisational performance – 6 sigma

• Role orchestration

• Choreography of content – MVC

Solve business problems

• How to reduce TCO

• How to increase TTM

• Asset information centric shift through SOA

Capability offerings

• Though leadership

• Strategy studies

• C Level

• Value chain

• Business Processes

• Information management

• Infrastructure

• Service management oriented

• Communications e.g. webenars

• Migration governance

• Transformation

EAB

• Data, people, function, network, motivation , time

• Primatives, composites

MDA

• CSM (computationally independent model)

• PIM (Platform independent model)

• PSM (Platform specific model)

IM Maturity Roadmap

• Discovery of data, wrap basic services

• Define master data sources – develop common services

• Managed services of data

• Syndicated, domains

• Orchestrated, federated and managed

Specific ECM standards and notes

Image capture standards

• IBM HPTS

• NCR

• Unisys

• Banc Tec

• Standard register

Lock box apps

Content Formats

• AFP (MD: DCA)

• DJDE / Meta Code

• PDF

• PCL

• Port script

• Text

• XML formats

Media production tools

• Adobe

• Quark

• Virage

• Ethics

• Water marking

• Asset assembly

• Cataloguing support

Media network trends

• Convergence – single IP network, voice and data

• IP telephony

• Voice over IP

• (VoIP and WAN convergence)

Search direct or search meta data

Web services

• XML, SOAP, UDDI, WSDL

• HTML, CSS

• XSLT

• XSD

• XPath

• Used for

• Search

• Authentication

• Profiling

ECM (a definition)

• Document management

• Document imaging

• Web content management

• Digital assets management

• Records management

• User experience / journeys

• Administration

• Installation

• Workflow

• Repository services

• Meta data

• Security and provisioning

• Licensing

• Team collaboration

• BPM

• Content integration

• Enterprise search

• (e-Forms)

• Repository support

Key vendors in ECM (Mid 2006)

• EMC –documentum

• Filenet (Bought by IBM)

• Humingbird

• IBM – DB2 CM, Workspace, Workcentre management

• Interwoven

• Microsoft sharepoint

• Open Text

• Oracle

• Stellnet

• Vignette

Enterprise data integration platform

• Java transformation

• Enterprise Grid

• High availability

• Pushdown optimisation

Processing XML has size issues

• Type of transaction

• Size of documents

• Caching

• Number of concurrent users

• Server configuration

• Etc

• SLAs – common approach

• Hardware – use network accelerators e.g. Cisco, IBM

Ontological frameworks for IM

Information management is today driven by more that static data “data warehouse” perspectives. It is part of the “fabric” or “DNA” of the organisation.

We see the following drivers

• Virtualisation of information access and use

• Multi-channel media presentment and business commercial models

• Rapid reduction in costs of integration and connectivity of disparate data sources

• Server farms and grid computing supporting information virtualisation

What we need is the ability to see beyond the logical design into the placement and use of many different types of information, the one fact, one place many uses paradigm. We need to combine structured and unstructured information in its many forms (rules, transactions, content etc) into a framework that models these many dimensions of granularity.

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