Data-Ed: Data-centric Strategy & Roadmap

Copyright 2014 by Data Blueprint

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Data-centric Strategy & Roadmap

Date: February 11, 2014

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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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


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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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 Needs

•  Developing a Roadmap and Plan •  Q&A


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Simon Sinek: How great leaders inspire action

WHY

HOW

WHAT “…it’s not what you do, it’s why you do it”

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


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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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‘Why’ a Data Strategy? Data becoming inextricably linked to, and part of, the actual products & services being sold Customers see enhanced value in having relevant, accurate & meaningful information combined with the products and services they purchase Information is power in a competitive market place Situational awareness (e.g. a 360º view) of your customers, suppliers, competition & operating environment creates a competitive advantage that enables you to plan and react Volume and velocity of data impacting operating models Organizations are being put at greater operating and reputational risk because legacy business processes and systems are straining under the requirements to process and understand ever-increasing volumes and speed of data Read more at my blog: http://www.datablueprint.com/winning-todays-information-economy-data-centric-business-strategy/


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Putting the Data Strategy Together Get a true understanding of your organization’s competitive advantage and current business goals Working with business leaders, managers and operators, define specific opportunities to meet the organizational goals Collaborating with your business partners, define the metrics that measure levels of success Develop a comprehensive solution using people, process, data and technology 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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•  Developing a Solution to Address Needs –  Closing Foundational Gaps –  Solving for Specific Business Needs



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Understanding Your Company’s Competitive Advantage

•  Do you really know why your company has an advantage over the competition? –  You may be surprised! –  Its not about being the best, its about being different

(counter intuitive) –  Its about deciding between a set of trade-offs –  Data strategy must align

•  Frameworks for understanding competitive advantage –  Porter’s Five Forces –  Porter’s Competitive Strategic Matrix –  SWOT Analysis –  PEST Analysis –  Four Corners Analysis


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Porter’s Competitive Strategic Matrix

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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Porter’s Competitive Strategic Matrix - Examples



Narrow Buyer

Segment


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Porter’s Five Forces

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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An Example – The Automotive Industry

Overall Low-Cost Leadership

Strategy

Broad Differentiation

Strategy

Focused Low-Cost Strategy

Focused Differentiation

Strategy

Blue Ocean Brands



Narrow Buyer

Segment

Once you find your place in the four quadrants…. •  What is your competitive advantage against those around you?


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Applying the Five Forces

Porsche •  Customer relationship data is critical. Develop individualized customer interactions •  High quality & efficient data processing to support R&D to further differentiate products

5 Forces Porsche Hyundai Threat of New Entrants Very Weak Weak Bargaining Power of Buyers Moderate Very Strong Bargaining Power of Suppliers Weak Very Weak Threat of Substitutes Moderate Strong Competitive Rivalry Moderate Strong

Hyundai •  Price-sensitive customers. Use strength over suppliers to maintain low COGS. •  Reduce non-value added to keep operational costs low by eliminating inefficiencies

created by poor data quality


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Data Value Generation Take-Away

Source: http://www.cioupdate.com/insights/article.php/3936706/The-4-Principles-of-a-Successful-Data-Strategy.htm


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Summary: Same Page with Your Business Partners

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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One of two choices

•  Good business strategy –  Understand what it really is:

•  Organizational strategy •  IT strategy •  Data strategy

•  Got to figure out/improve the business strategy –  Analysis –  What changes would be seen

as useful/important? –  Plan to accomplishing

something useful …


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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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The Data Strategy Solution

With an understanding of business needs and measures of success criteria, align a solution leveraging the following: • Rethink the SDLC: Application- vs. Data-Centric • Make it Comprehensive:

–  People: Organizational Structure –  Data Management Practices: Foundational & Technical –  Data: Determine What is Important –  Process: Business Process Changes –  Technology: Engineering/Architectural Concepts

• Match your organization’s abilities to deliver


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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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People: Who is Involved? •  Open question: Who is responsible for creating and implementing

the company’s Data Strategy? -  Organizational Leadership is required – a Chief Officer that reports up through the business

lines -  Data strategy requires governance – Business, IT and Data team representation

•  Stakeholders -  CEO, CFO, COO, CIO, etc.. -  Lines of Business Senior Management and Operational Managers -  Functional Areas Senior Management and Team Leads

•  The Data Team – formal and implicit -  Architects -  Modelers -  Developers -  Analysts -  Stewards

-  CDO


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harin

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initativ

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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

Job

Top Job

Top Finance Job

Top InformationTechnology

Job

Top Marketing

Job

Data Governance Organization

ChiefData

Officer


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Data: Determine What is Important

•  Think about it in terms of data ‘meta-types’: –  Transactional Data –  Workflow/Event Data –  Master & Reference Data –  Reporting & Analytical Data –  Metadata

•  Not all of your data is important! •  Concept of ROT •  Understanding your business and their needs

makes this easier to determine


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Data Management Practices •  Foundational Data

Management Practices create the organizational infrastructure that enforces the alignment of company strategies with data assets

•  Technology Data Management Practices enable an organization to leverage the data on the scale needed to support information-based strategies

Important Note: Not all DM Practices needed all the time. Tailor to meet the needs of the business.


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•  3-legged stool –  Strategy –  Architecture –  Governance

•  For example: –  Warehouses fail –  Missing governance –  Quality

Foundational Practices


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Health Care Provider Data Warehouse

•  1.8 million members •  1.4 million providers •  800,000 providers no key •  1 User

The average DW costs $30M and take 18 months to build!

"I can take a roomful of MBAs and accomplish this analysis faster!"


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Foundational Practice: Data Strategy

•  Your data strategy must align to your organizational business strategy and operating model

•  As the market place becomes more data-driven, a data-focused business strategy is an imperative

•  For example, you must have data strategy before you have a Big Data strategy


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Foundational Practice: Data Architecture •  Common vocabulary

expressing integrated requirements ensuring that data assets are stored, arranged, managed, and used in systems in support of organizational strategy [Aiken 2010]

•  Most organizations have data assets that are not supportive of strategies

•  Big question: •  How can organizations more effectively use their

information architectures to support strategy implementation?


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Foundational Practice: Data Governance •  Data governance is the

exercise of authority and control over the management of your mission critical data assets.

•  Governance can seem like an added bureaucratic layer with little value-add. The little ‘g’ approach - develop governance where it matters the most.

•  Focus on organizational roles and responsibilities as well as organizational change management initiatives.


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Technical Practices

•  Think like an engineer –  Holistic –  Integrated –  Driven by Requirements

•  For example: –  Unwinding Mainframes –  Analytical Platforms


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Technical Practices: Data Quality •  Quality is driven by fit for

purpose considerations •  Improved directional accuracy is

the goal •  Focus on your most important

data assets and ensure our solutions address the root cause of any quality issues – so that your data is correct when it is first created

•  Experience has shown that organizations can never get in front of their data quality issues if they only use the ‘find-and-fix’ approach


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Technical Practices: Data Integration •  Data integration requires a

common language and semantic understanding

•  Needs to support multiple perspectives on the same data

•  Creates the broad, 360 degree view – where insight comes from

•  An area where governance can enable and sustain

•  A challenge in organizational thinking


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Technical Practices: Data Platforms •  Incorporate engineering/

architectural concepts into holistic systems thinking

•  Decouple functionality. No one data platform can answer all questions (commonly misunderstood & expensive)

•  Engineered components can only be as strong as their weakest component


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Getting Data into the Cloud

Transform

LessCleanerMore shareable ... data


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Technical Practices: Business Intelligence •  Highly dependent on quality,

metadata, governance, integration and platforms

•  Exploratory in nature. Small ‘failures’ and on-going learning are part of the process

•  Often exists in spread-marts and shadow IT solutions – difficult to share and have a common understanding


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Process: Business Process Impacts

•  A CRUD matrix shows business processes and their data activity type

•  Leverage business process analysis, design and development techniques

•  Capture baseline measures against existing business processes to effectively measure improvements

•  The Data Strategy Solution will impact existing business processes and may create new business processes.

•  Business processes are how the data get Created, Read, Updated and Deleted (CRUD)


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Technology: Making the Right Choices

•  For example: Software selection •  When it is discovered that the new software doesn't

match existing organizational practices … 1.  Change software

2.  Change your business practices 3.  Some combination of both

4.  Ignore the problem

•  Data strategy would have revealed the problem in advance of the selection


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Match your Abilities to Deliver

Data Program Coordination

Feedback

DataDevelopmentStandard

Data

Organizational Strategies

Goals

BusinessData

Business Value

Application Models & Designs

Implementation

Direction

Guidance

OrganizationalData Integration

DataStewardship

Data SupportOperations

Data Asset Use

IntegratedModels

Leverage data in organizational activities

Data management processes andinfrastructure

Combining multipleassets to produceextra value

Organizational-entity subject area data

integration

Provide reliable data access

Achieve sharing of data within a business area

Understanding your level of Data Management Practice is critical in developing achievable solutions


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Summary: The Data Strategy Solution

•  Thinking differently about the solution •  Its Comprehensive: People, Data Management,

Data, Process & Technology •  Address foundational gaps to sustain solutions •  Match your organization’s abilities to deliver

Next Step: •  Outline an achievable implementation plan


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Implementation Plan & Roadmap •  Outline a long-term vision and implementation milestones

•  Achievable, realistic plans

•  Build momentum with specific, short-term win projects

–  Approach: Crawl, Walk, Run

•  More to come at EDW…


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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


Sessions: • Implementing a Data-Centric Strategy & Roadmap – Focus on What Really Matters

–  3 hour workshop with Peter & Lewis

• Choosing the Right Data Warehouse Modeling Strategy based on your business needs: Kimball, Inmon, Data Vault

–  Lighting Talk with Data Blueprint Team

•  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.edw2014.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

Emerging Trends in Data Jobs March 13, 2014 @ 2:00 PM ET/11:00 AM PT

Data Quality Engineering April 11, 2014 @ 2:00 PM ET/11:00 AM PT

Sign up here: •  www.datablueprint.com/webinar-schedule •  or www.dataversity.net

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Data-Ed: Data-centric Strategy & Roadmap

Technology

Transcript of Data-Ed: Data-centric Strategy & Roadmap