Part of the solution. Bringing it all Together - Informa2on and Data Management

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Part of the solution

Bringing it all Together

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Information vs. Data

2 Part of the solution

•  ”Knowledge, meaning”

•  The input needed to make business decisions

The Focus Area of ’The Business’

•  Factual information

•  Organized for analysis or optimised for system design & operation

The Focus Area for IT Departments

Information is ‘trusted’ data put into a business context

Data

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Information Model vs Data Model !

Data Model

•  A formalized description of the information used by a business

•  Shows the most important information objects •  Includes constraints imposed by business rules •  includes a complete description of each object i.e.

Business Definitions

•  Shows relationship between information objects

•  How data is held within a system

•  Contains constraints imposed to optimise the technical implementation

•  Include attributes (i.e. lower level of detail)

•  Multiple Data Models map to the same Information Model

Information Model

A model of the information

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Enterprise Information Management

Set the strategy for how information is managed

•  Planning, organizing, staffing, leading, and controlling

Establish control over the information

•  Organizing, retrieving, acquiring, integrating, maintaining information

S tr at e g y Delivery

“Treating Information and therefore data as an enterprise asset”

Data Governance

Information Management

Ensure effectiveness of data delivery

•  Data is available, accessible, and has quality fit for purpose

Ensure efficiency of data delivery

•  Define processes for timely and efficient delivery of reusable data

Set the strategy to enable delivery of trusted information to be used by the entire organization

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Other Data Master Data

Common Information Model

October 27, 2011 5

Building Blocks

EN A BL ES World Class Customer Services Data Governance

Master Data Management Trusted Information 360 degree business view

Competitive Advantage

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Master Data and MDM

Master Data

•  Key data for the operation of the business

•  Core entities needed to conduct business,

•  Used by several functional groups and systems across an organization.

•  Examples: customers, products, employees, material, suppliers etc.

Why does it need ‘Managing’ ?

•  Exists in silos without coordination

•  Reflects historical circumstances rather than current situation

Master Data Management

•  Processes and tools to manage master data

•  Aim: a unified view of each master data object

  A single version of the truth for master data objects

How?

•  Identify authorised sources, or rules to achieve a Master Record

•  Integrate disparate master data sources

•  Perform Matching, merging,cleansing, cross-referencing

•  Identify and apply centralised DQ business rules

•  Automate where possible

•  Use workflow to resolve unclear cases – link to data governance

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The Logic behind Data Governance

“Most data still originates with

humans. Governance is a

way to raise the quality. Identify,

measure, have clear processes to fix things.” “DG means putting people in charge of fixing and preventing issues with data so that the enterprise can

become more efficient.”

This Requires TRUSTED DATA

Need trusted information

  Clear Ownership of data and definitions   Clear responsibilities

  A clear process for decision making   Centralised DQ business rules   Established metrics and monitoring Need to make Business Decisions!

  Has agreed definitions   Has traceable origin   Has good quality:

  ‘Clean’ – i.e. according to standards   Not contain duplicates

  Is correctly integrated TRUSTED DATA

Achieved through

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Bringing it all Together

2011-05-25 8

Customer Interfacing Layer Business Intelligence Layer

Master Data Layer (Customer, Product ,…)

Systems, Data Sources

D e m an d Information Management

•  Put people, processes, goals in place

•  Assign Roles, Responsibilities, accountabilities

•  Ensure alignment to the business’ strategic direction and KPI’s

•  Demand Supply Planning & Balancing

•  Ensure common business information definition s (Information Model)

•  Drive optimum business value

•  Ensure efficient delivery of trusted information

Suppl

y

Data Governance

•  People, processes, and technology required to deliver trusted data

•  Formally manage data assets

•  Assign accountability for data quality

•  Put people in charge of fixing and preventing issues with data

•  Use technology when necessary to aid the process.

Master Data Management

S tr ae tg y Delivery

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With and Without Data Governance and MDM!

With

•  Data cannot be trusted

•  Business inflexibility and inefficiency •  Poor customer experience

•  Incorrect business decisions

•  Inefficient use of resources (effort spent on trial and error, investigation, workarounds)

•  Dependence on a few key individuals

•  Data is trusted

•  More confident, efficient business decisions •  Reduction of data management complexity & cost •  Reduced cost of errors based on bad data

•  Less time for key resources spent chasing DQ issues

•  Less dependency on individuals •  More reuse of data assets

Without

Can’t find trusted data Can’t make decisions

Create point to point solutions

Don’t want to reuse data

Fragmented, non-integrated data

Data is trusted

New data sources are certified and added

Data is reused New, trusted, well

understood data is integrated

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Implementation Tips

Define your information model first

Use the information model as a to guide the DG and MDM strategy. •  Which areas to start with

•  Map system data to information areas

Design

Start small think big or even better think 'value’:

•  Find high impact areas i.e. Information area with most value, or most pain •  Incremental business value approach:

  Pick a quick win area to start demonstrating business value early   Use this as Input to business case

  Use smaller business cases as springboards to expansion of MDM and improve overall DQ

Think ‘Value’

Strategy comes before execution!

•  The Information Management strategy in this case.

•  Once that is defined, then define process, then people and technology •  Continuously assess performance against the strategy

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Information Builders approach

Information Builders leverage DG and MDM integration to enable BI since this is the same data being integrated.

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Experts in IT Project Delivery

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Our Focus: Business Value

We are experts in IT project delivery. Our pragmatic approach ensures that

our customers get the most business value from their IT solution.

Our primary areas of expertise are:

• System Integration

• Data and Process Modelling

• CRM

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Services

• Project Establishment

 

Pre-study, requirements, project definition

• Project Implementation

 

Technical Project Management, architecture, test management

• Software delivery

 

Development, test, support

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Customers

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Customer Cases

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Reference Engagements (1 of 3)

•  Information Modeling for Major international telco

•  Polar Cape has been helping with the definition and implementation of a

Common Information Model across the multiple business areas and countries.

•  The objective is to improve communication between business areas, improve

communication between business and IT, and to speed up the requirements gathering process

•  Focus on active uptake of the model as a tool to improve quality and efficiency

•  Long term objectives: Provide a foundation for DG and MDM

•  Information and Process Modeling for software service provider

•  In Q1 and Q2 2011 Polar Cape will help one of it's new customers, a software

service provider, to define their information and process models across their business. This business-driven exercise will enable the company to use a common language across the business units and systems and lay the

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Reference Engagements (2 of 3)

•  Business Intelligence and Data Warehouse consolidation at international telecoms

operator for major EDW consolidation

•  Manager of business requirements

•  Facilitator of more than 60 workshops together with all level 1-3 managers

from the business and management consultants from the suppliers

•  Part Responsible for RFP (business requirements, scope, and acceptance test

procedures)

•  Coordination of detailed Data Governance pre-study

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Reference Engagements (3 of 3)

•  Implementation of a CRM and service fulfillment platform at major telecoms

operator

•  Services such as ADSL, LAN, IPTV and VoIP

•  Rolled out in 7 countries

•  CSR and self-service order entry

Part of the solution. Bringing it all Together - Informa2on and Data Management