Strategy and roadmap slides

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Copyright 2014 by Data Blueprint 1 Data-centric Strategy & Roadmap Date: January 13, 2015 Time: 2:00 PM ET 11:00 AM PT Presenters: Peter Aiken, Lewis Broome

Transcript of Strategy and roadmap slides

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Data-centric Strategy & Roadmap

Date: January 13, 2015

Time: 2:00 PM ET 11:00 AM PT

Presenters: Peter Aiken, Lewis Broome

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Commonly Asked Questions

1)  Will I get copies of the slides after the event?

2)  Is this being recorded so I can view it afterwards?

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Get Social with Us! Live Twitter Feed #dataed

Like Us www.facebook.com/datablueprint Join the Group Data Management & Business Intelligence

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Building a Data-centric Strategy & Roadmap What needs to be done… avoiding a haphazard approach Presented by Peter Aiken, Ph.D. and Lewis Broome

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•  30+ years DM experience

•  9 books/ many articles

•  Experienced with 500+ data management practices

•  Multi-year immersions: US DoD, Nokia, Deutsche Bank, Wells Fargo, & Commonwealth of VA

Lewis Broome Peter Aiken •  CEO Data Blueprint

•  20+ years in data management

•  Experienced leader driving global solutions for Fortune 100 companies

•  Creatively disrupting the approach to data management

•  Published in multiple industry periodicals

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Outline •  Data Strategy Overview •  Determining the Business Needs •  Measurement & Success Criteria •  Current State Analysis •  Developing a Solution to Address Needs •  Developing a Roadmap and Plan •  Q&A

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"The significant problems we face cannot be solved at the same level of thinking we were at when we created them." - Albert Einstein

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Wayne Gretzky’s Definition of Strategy

He skates to where he thinks the puck will be ...

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The Importance of Strategy

Organizational Strategy

IT Strategy

Data Strategy

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Summary: Enterprise Data Strategy Choices

Q3

Using data to create strategic opportunities

Q4

Both (Cash Cow)

Q1

Keeping the doors open (little or no proactive data

management)

Q2

Increasing organizational efficiencies/effectiveness

Improve Operations

Inno

vatio

n

Only 1 in 10 organizations has a board approved data strategy!

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Understanding WHY Data is Important to the Business

•  Data linked to, and part of, the products & services being offered

•  Information is power (Analytics!) •  Data creatively destructs how we work; skills & the

workforce needed are drastically different •  Data volume, velocity & variety exerting

pressure on operating models & infrastructure

“…it’s not what you do, it’s why you do it” – Simon Sinek

http://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action.html

Why Vision

How Process

What Outcome

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Putting the Data Strategy Together

Comprehend your organization’s competitive advantage, operating model & business goals

Define specific business opportunities that impact these Define the metrics that measure improvement in business performance Requires people, process, data and technology while recognizing strengths and limitations of culture & capability

Outline an achievable implementation plan in a roadmap with timelines, milestones and level of effort estimates

Get on the same page with

business partners

Measure Business Value

Develop a holistic solution and

approach

Note: For many organizations this requires a transformation in how they think and operate – this is the greatest challenge in becoming a ‘data-driven’ organization

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Outline •  Data Strategy Overview •  Determining the Business Needs

–  Foundational Business Understanding –  Identify Specific Business Needs –  Example Data Strategy Goals

•  Measurement & Success Criteria •  Current State Analysis •  Developing a Solution to Address Needs •  Developing a Roadmap and Plan •  Q&A

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Aligning Data Management Goals to the Business

•  Competitive Advantage –  Its not about being the best, its about being different

•  Operating Models –  The interactions across processes, business units, customers

and products

•  Business Strategy and Goals –  Short and Long Term; Leadership’s Dynamic priorities and investments

•  Use Frameworks for Understanding

Start with Analyzing the Business…..

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Porter’s Competitive Strategic Framework

Cost: Are you competing on cost? How cost-sensitive is your market?

Market Scope: Are you focused on a narrow market (i.e. niche) or a broad market of customers?

Overall Low-Cost Leadership

Strategy

Broad Differentiation

Strategy

Focused Low-Cost Strategy

Focused Differentiation

Strategy

Blue Ocean Brands

Lower Cost Differentiation

Broad Range of Buyers

Narrow Buyer

Segment

Product Differentiation: How specifically focused are your products?

Note: (Typically) Can’t be all things to all consumers – where are you?

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Competitive Strategic Framework - Example

Overall Low-Cost Leadership

Strategy

Broad Differentiation

Strategy

Focused Low-Cost Strategy

Focused Differentiation

Strategy

Blue Ocean Brands

Lower Cost Differentiation

Broad Range of Buyers

Narrow Buyer

Segment

•  Its all about how value is created! •  Works for Non-profits as well (Substitute ‘Mission’ for Value)

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Porter’s Five Forces Framework

Bargaining Power of Buyers: The degree of leverage customers have over your company

Bargaining Power of Suppliers: The degree of leverage suppliers have over your company

Threat of New Entrants: How hard is it for new competition to enter the market?

Threat of Substitute Products: How easy (or hard) is it for customers to switch to alternative products?

Competitive Rivalry: How competitive is the market place?

Once you find your place in the four quadrants…What is your competitive advantage?

http://www.strategy-keys.com/michael-porter-five-forces-model.html

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Five Forces - Example

Whole Foods •  Customers (weak influence) will seemly pay any price for specially sourced commodities •  Fewer suppliers (strong influence) to support Whole Foods’ customer demands

5 Forces Whole Foods Wal-mart Threat of New Entrants Weak Weak Bargaining Power of Buyers Weak to Moderate Moderate to Strong Bargaining Power of Suppliers Moderate to Strong Very Weak Threat of Substitutes Strong Moderate to Strong Competitive Rivalry Moderate Weak

Wal-mart •  Price-sensitive customers. Use strength over suppliers to maintain low costs. •  Heavy investment in keeping operational cost low. Highly efficient internal processes

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Operating Model Framework Coordination • Shared customers, products or suppliers • Impact on other business unit transaction • Operationally unique business units or functions • Autonomous business management • Business unit control over process design • Consensus processes for designing IT infrastructure services • IT application decisions made in business units

Unification • Customers and suppliers may be local or global • Globally integrated business processes often with support of enterprise systems • BU’s with similar or overlapping operations • Centralized management often applying functional/process/business unit matrices • Centrally mandated databases • IT decisions made centrally

Diversification • Few, if any, shared customers or suppliers • Independent transactions • Operationally unique business units • Autonomous business management • Business unit control over business process design • Few data standards across business units • Most IT decisions made within business units

Replication • Few, if any, shared customers • Independent transactions aggregated at high level • Operationally similar business units • Autonomous BU leaders with limited discretion over processes • Centralized control over business process design • Standardized data definitions but locally owned • Centrally mandated IT services

Business Process Standardization Low High

Hig

h Lo

w

Bus

ines

s P

roce

ss In

tegr

atio

n

*Source: Gartner

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Operating Model - Examples Coordination Unification

Diversification

Replication

Business Process Standardization Low High

Hig

h Lo

w

Bus

ines

s P

roce

ss In

tegr

atio

n

*Source: Gartner

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Business Strategy and Goals

•  A cohesive declaration of organizational direction, strategies, goals, targets, objectives, approaches and plans

•  Usually tied to a time frame

•  Constrained by competitive advantage and operating models

•  Dynamically created as a result of opportunities and challenges

•  Aligns to overall mission and brand

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Business Strategy and Goals - Example

Strategy for a large publicly traded logistics company “We forge long-term partnerships with key customers that include supply-chain management as an integral part of their strategy. Working in concert, we drive out cost, add value and function as an extension of their enterprise. Our strategy is based on utilizing an integrated, multimodal approach to provide capacity-oriented solutions centered on delivering customer value and industry-leading service. We believe our unique operating strategy can add value to customers and increase our profits and returns to stockholders.”

Brand Promises to their Customers •  Undeniable Flexibility •  Unmatched Capacity •  Unrivaled Service •  Undisputed Experts •  Unprecedented Control

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Data Strategy Goals – Example-1 Enterprise

Divisional

•  An 360° enterprise level understanding of customers, capacity, orders & vendors •  Asset and driver utilization maximized across the enterprise •  IT solutions leveraged across the enterprise to reduce costs and cycle-time •  Customers seamlessly leverage services across divisions

•  A 360° divisional level understanding of customers, capacity, orders & vendors •  IT solutions leveraged to support operational uniqueness of each division •  Minimize cost and maximize revenue per load per division

Division A Division B Division C Division D

Enterprise

Rolls Up To

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Data Strategy Goals – Example-2

Increase Operational Efficiencies

As-

Is

To-B

e

As-Is Efficiency Challenges •  Complex & un-integrated business processes •  Suboptimal data structures & controls creates poor data

quality •  Lack of transparency and controls creates work-around’s

To-Be Efficiency Improvements •  Eliminate non-value added manual work-around’s •  Maximize auto-accepts (i.e. straight-through-processing) •  Simplify & automate workflows •  Create transparency to enable proactive processes

Increasing operational efficiencies will… •  Lower cost per order/load •  Increase capacity utilization within & across divisions

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Summary: Aligning Data Management Goals to the Business

A Data Strategy must be Business Focused •  Understand the business fundamentals of your organization

•  Develop a common language and shared perspective with your business partners – enabling collaboration

•  Identify specific business opportunities or areas of improvement

•  Focus the data strategy solution on improving those specific business needs

Next Step: •  Measuring business value of

making improvements:

•  Metrics, Object of Measurement and Methods

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Outline •  Data Strategy Overview •  Determining the Business Needs •  Measurement & Success Criteria

–  An Overview –  An Example

•  Current State Analysis •  Developing a Solution to Address Needs •  Developing a Roadmap and Plan •  Q&A

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Measuring Business Value

If something is important to the business it can be observed. If it can be observed, it is measureable! • Understanding ‘measurement’; reducing uncertainty, not necessarily an exact value • Object of Measurement; often too ambiguously defined • Methods of Measurement; become familiar with multiple methods and apply in the right context

Define success criteria as specific metrics

•  Not always intuitive and at first seems difficult

•  Must be done in collaboration with your business partners

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Great point of initial inspiration ... •  Formalizing stuff forces

clarity •  Special shout out to

Chapter 7 –  Measuring the value of

information –  ISBN: 0470539399 –  http://www.amazon.com/

How-Measure-Anything-Intangibles-Business

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Measuring Business Value – An Example

•  $1billion (+) chemical company •  Develops/manufactures additives

enhancing the performance of oils and fuels ...

•  ... to enhance engine/machine performance

–  Helps fuels burn cleaner –  Engines run smoother –  Machines last longer

•  Tens of thousands of tests annually ($25K to $250K each)

International Chemical Company Engine Testing

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Objects of Measurement & Metrics •  Test Execution: Number of tests per customer

product formulation. Grouped by product types and product complexity.

•  Customer Satisfaction: Amount of time to develop a certified custom formulated product; time from initial request to certification

•  Researcher Productivity: Tested and certified formulations per researcher

Note: Baseline measures were taken from historical data and anecdotal information

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Overview of Existing Process

1.  Manual transfer of digital data 2.  Manual file movement/duplication 3.  Manual data manipulation 4.  Disparate synonym reconciliation 5.  Tribal knowledge requirements 6.  Non-sustainable technology

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Solution and Business Value Results •  Solution:

–  Business process improvements –  Data Architecture Development –  Data Quality Improvements –  Integrated System Development

•  Results: –  Reduced the number of tests needed to develop products –  Increase the number of tests per researcher –  Reduce the time to market for new product development

•  According to our client’s internal business case development, they expect to realize a $25 million gain each year thanks to this data integration

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Summary – Measuring Business Value •  If it’s important to the business, it’s measureable •  Learning to measure business value requires:

–  Understanding fundamentally what it means to ‘measure’ –  Being clear about what is going to be the object of

measurement and the specific metrics –  Methods that will ensure the metrics captured are

meaningful and consistent •  The old adage – “if you don’t measure it, it can’t be

managed” is true

Next Step: •  Develop a holistic solution and approach to address the

business needs identified in the data strategy

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Outline •  Data Strategy Overview •  Determining the Business Needs •  Measurement & Success Criteria •  Current State Analysis

–  Analysis Framework Overview –  Examples

•  Developing a Solution to Address Needs •  Developing a Roadmap and Plan •  Q&A

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Analyzing the Current State (ACS) Why we are analyzing the current state…

• Identify existing assets to be leveraged • Identify gaps in assets and capabilities • Identify constraints & interdependencies in the operating environment • Measure Cultural Readiness – scope of change management efforts • Ensures solutions are achievable

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Data Strategy Framework (DSF)

Business Need

Current State

Solution

Target Source

Value Capabilities

DATA STRATEGY

Road Map

•  Org. Readiness •  Bus. Processes •  Bus. & Data

Practices •  Data Assets •  Tech Assets

•  Bus. Strategy & Objectives

•  Competitive Advantage

•  Bus. Structures •  Bus. Measures

1

3

4

2

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Analyzing the Current State (ACS)-1

What we are analyzing… •  People and Organization •  Business Processes •  Data Management Practices •  Data Assets •  Technology Assets

Note: Scope of the analysis, across all facets of the current state environment, is constrained by the business needs definition. This mitigates the risk of over analyzing the current state.

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Analyzing the Current State (ACS)-2

People & Organization

Data Assets Technology Assets

Data Mgmt. Practices

Business Processes

Business Goals and Objectives

Creates

Enables

Informs

Enables

Enables

Measures

Delivers

Enables

Enables

Provides Context

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Typical Thinking: Application-Centric •  In support of strategy, organizations develop specific

goals/objectives

•  The goals/objectives drive the development of specific systems/applications

•  Development of systems/applications leads to network/infrastructure requirements

•  Data/information are typically considered after the systems/applications and network/infrastructure have been articulated

•  Problems with this approach:

–  Ensures data is formed to the applications and not around the organizational-wide information requirements

–  Process are narrowly formed around applications

–  Very little data reuse is possible Data/Information

Network/Infrastructure

Systems/Applications

Goals/Objectives

Strategy

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New Thinking: Data-Centric •  In support of strategy, the organization develops specific

goals/objectives

•  The goals/objectives drive the development of specific data/information assets with an eye to organization-wide usage

•  Network/infrastructure components are developed to support organization-wide use of data

•  Development of systems/applications is derived from the data/network architecture

•  Advantages of this approach:

–  Data/information assets are developed from an organization-wide perspective

–  Systems support organizational data needs and compliment organizational process flows

–  Maximum data/information reuse

Data/Information

Network/Infrastructure

Systems/Applications

Goals/Objectives

Strategy

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ACS: People What we are looking for…

•  Organizational Structures •  Skills and capabilities •  Culture

Why we look at People…

•  Understand current roles, responsibilities & accountability

•  Assess skills & capabilities to determine what’s achievable

•  Determine how adaptable the organization is to change

•  How the cultural nuances drive the operating environment

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CDO Reporting

1.  Dedicated solely to data asset leveraging

2.  Unconstrained by an IT project mindset

3.  Reporting to the business

Top Operations

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Top Finance Job

Top InformationTechnology

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Data Governance Organization

ChiefData

Officer

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ACS: Business Process What we are looking for… •  Process flows (Diagrams) from a business perspective •  Process actors, including data creators and data consumers •  Pain points in the existing business processes •  Existing performance measures of business processes

Why we want to look at business processes… •  Business value of data is realized via a business process •  Most important events in the life of data – when it is created

and when it is used (Dr. Tom Redman) •  Describes the activities underpinning the competitive

advantage

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ACS: Automating Business Process Discovery

Benefits •  Obtain holistic perspective on roles

and value creation •  Customers understand and value

outputs •  All develop better shared understanding

Results •  Speed up process •  Cost savings •  Increased compliance •  Increased output •  IT systems documentation

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ACS: Data Management Practices-1 What we want to look at… •  Level of importance of data and information in

organizational strategy – is it explicitly identified as an asset to be leveraged?

•  How data requirements are derived •  Degree to which data is shared across organization •  How data quality issues identified and remediated. •  How data assets are designed and implemented •  How data assets are controlled, protected and maintained

once they are operational – e.g. compliance, security, business continuity

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ACS: Data Management Practices

Analyzing your Data Management Practices will be critical in developing achievable solutions

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<- CMM Level 2

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Assessment Components Data Management Practice Areas

Data program coordination

DM is practiced as a coherent and coordinated set of activities

Organizational data integration

Delivery of data is support of organizational objectives – the currency of DM

Data stewardship Designating specific individuals caretakers for certain data

Data development Efficient delivery of data via appropriate channels

Data support Ensuring reliable access to data

4

Capability Maturity Model Levels Examples of practice maturity

1 – Initial Our DM practices are ad hoc and dependent upon "heroes" and heroic efforts

2 - Repeatable We have DM experience and have the ability to implement disciplined processes

3 - Documented We have standardized DM practices so that all in the organization can perform it with uniform quality

4 - Managed We manage our DM processes so that the whole organization can follow our standard DM guidance

5 - Optimizing We have a process for improving our DM capabilities

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Data Management Practices Hierarchy

You can accomplish Advanced Data Practices without becoming proficient in the Basic Data Management Practices but this will: •  Take longer •  Cost more •  Deliver less •  Present

greater risk

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Basic Data Management Practices

Advanced Data

Practices • MDM • Mining • Big Data • Analytics • Warehousing • SOA

50

Data Program Management

Data Stewardship Data Development

Data Support Operations

Organizational Data Integration

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ACS: Data Assets-1 What we are looking for… • Broad view of the data assets (Structure and unstructured)

–  Business Entity Inventory –  Business Entity Diagram

–  Data Ecosystem –  Enterprise data architecture –  Application architecture describing systems and their relationships

• Narrow view of data assets in the context of the business needs –  Not all data impacts the business needs equally –  Data Dictionary

–  Data Profiling –  Data models –  Tools to automate discovery such as Global ID’s

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ACS: Data Assets – Data Quality Considerations

Prevention at Source

Find and Fix

Ad-Hoc Processes

An interpretation from Dr. Tom Redman’s ‘Three Approaches to Data Quality’

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ACS: Data Assets-2 Why we want to look at data assets… •  Trying to find pain points •  Set the boundaries for what data and information is

possible under current conditions •  Understand how well the organization understands what

data exists •  Compartmentalize and decouple data from systems •  Provides a data-centric business perspective that cannot

be seen easily from business processes •  Provides a measure of complexity and potential risk of the

current operating environment

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ACS: Technology Assets-1 What we want to look at… •  Broad view of technology assets –  Enterprise and application architecture artifacts

–  Inventory of technology, software, tools and environments

–  Current standards vs. legacy vs. “bolt-on” technology

–  Process for buying technology

–  Pain points and constraints

• Narrow view of technology assets in the context of business needs –  Identify specific systems, technology, etc… in scope

–  Assess capabilities and constraints

–  Implementation approach – e.g. customized or off the shelve

–  Ability to non-functional requirements – e.g. performance, capacity

Why we want to look at technology assets… •  ….

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ACS: Technology Assets-2 Why we want to look at technology assets…

• What technology assets are currently available for the solution

• What technology standards needs to be considered in the solution

• Informs as to the complexity of the current environment

• Highlights ‘shadow’ technology solutions

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How to Analyze the Current State

•  Interviews •  Surveys •  Document and artifact review •  Intranet and wiki reviews •  Facilitated sessions – i.e. Workshops •  Leverage existing organizational structures – i.e.

working groups, governance teams •  Requisite Skills: Critical Thinking, Inquisitiveness,

Collaboration, Tenacity, Organization and Technical Writing

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Outline •  Data Strategy Overview

•  Determining the Business Needs

•  Target Measurement & Success Criteria

•  Current State Analysis

•  Developing a Solution to Address Business Needs –  Closing Foundational Gaps –  Solving for Specific Business Needs

•  Developing a Roadmap

•  Q&A

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Data Strategy Framework (DSF)

Business Need

Current State

Solution

Target Source

Value Capabilities

DATA STRATEGY

Road Map

•  People & Org. •  Bus. Processes •  Data Mgmt.

Practices •  Data Assets •  Tech Assets

•  Bus. Strategy & Objectives

•  Competitive Advantage

•  Bus. Structures •  Bus. Measures

1

4

2

3

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Expected Results

Data Strategy Solution should… • Be tailored to solve specific business needs • Be measureable against set targets • Develop organizational capabilities, as necessary, to ensure the solution is sustainable • Be achievable given the current state capabilities • Define a solution with enough specificity to develop an implementation road map

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Data Strategy Solution Framework (DSSF)

People & Organization

Data Assets Technology Assets

Data Mgmt. Practices

Business Processes

Business Goals and Objectives

Enables

Enables

Informs

Creates

Enables

Measures

Delivers

Enables

Enables

Provides Context

The solution architecture and change management plans result from this framework

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Change in a Complex Environment

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Outline •  Data Strategy Overview •  Determining the Business Needs

–  Foundational Business Understanding –  Identify Specific Business Needs –  An Example

•  Measurement & Success Criteria –  An Overview –  An Example

•  Developing a Solution to Address Needs –  Closing Foundational Gaps –  Solving for Specific Business Needs

•  Developing a Roadmap and Plan •  Q&A

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How To: Creating a Roadmap

•  Outputs from… –  Business Needs Assessment –  Current State Analysis

•  In support of the Business Strategy –  Inextricably Linked

•  Come up with a reasonable way to ID and close the gaps within the solution framework –  Outline a long-term vision and implementation milestones –  Achievable, realistic plans –  Build momentum with specific, short-term win projects

•  Approach: Crawl, Walk, Run

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The Approach of Crawl, Walk, Run •  Crawl:

–  Identify business opportunity and determine a scope that fosters early learning yet delivers measureable value

•  Walk: –  Develop foundational &

technical data management practices ensuring they are repeatable. Enlarge the scope of projects that expand capabilities

•  Run: –  Continuous improvement and expanded application of maturing

data management practices

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The Benefits of Crawl, Walk, Run •  ‘Pilot-like’ projects create a unique opportunity for

organizational learning while providing measureable value

•  Builds support for new approaches to data management – i.e. supports change management activities

•  More achievable approach to managing data as an asset •  Allows for foundational components to be developed

while concurrently executing more tactical solutions

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Road Map Framework •  High-level Road Map •  Road Map Activities •  Align Activities to Business Value Targets (i.e.

Traceability) •  Road Map Activity Details •  Level Of Effort Estimates (where possible) •  Budget Estimates (where possible)

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Copyright 2014 by Data Blueprint

Sessions: • Data Strategy 2.0: Focus on the Roadmap and Implementation • 3 hour workshop with Lewis Broome

• Addressing Data Challenges using the Data Management Maturity Model • Melanie A. Mecca, CMMI Institute Peter Aiken, Data Blueprint

•  120+ thought leaders

•  800 attending Senior IT Managers, Architects, Analysts, Architects & Business Executives

•  5 full days of in-depth education and networking opportunities

•  … and more!!!

•  Register here: www.edw2015.dataversity.net

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Questions?

+ =

It’s your turn! Use the chat feature or Twitter (#dataed) to submit

your questions now.

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Upcoming Events

Business Value from MDM February 10, 2015 @ 2:00 PM ET/11:00 AM PT

Data Architecture Requirements March 10, 2015 @ 2:00 PM ET/11:00 AM PT

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10124 W. Broad Street, Suite C Glen Allen, Virginia 23060 804.521.4056