dataed webinar: implementing successful data strategies - developing organizational readiness and...

Micheline Casey & Peter Aiken, PhD

Developing Your Data Strategy

Ensuring Alignment with Business Strategy, and Making it Practical and Actionable

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Micheline Casey• Micheline Casey is a senior executive with over 20 years

experience helping organizations use data and information technology to grow and achieve strategic objectives. She is passionate about pushing boundaries with data, analytics, and tech, and applying design thinking to improve data product and service delivery. As principal at CDO, LLC, she works with a variety of organizations in multiple industries advising on the role of the chief data officer, data and analytics strategy, and organizational design considerations.

• Ms. Casey was the first Chief Data Officer at the Board of Governors of the Federal Reserve System. She headed the Office of the Chief Data Officer (OCDO) and was responsible for the FRB enterprise data strategy and innovation; overseeing data governance policy development; transforming data management practices; and, integrating data architecture. Ms. Casey was the first state government Chief Data Officer in the country, and part of the Governor’s Office in the State of Colorado. Prior to her work in public service, Ms. Casey worked for several technology companies, including ChoicePoint (now LexisNexis), iXL Holdings, and IBM Global Services.

• Ms. Casey has been profiled in several industry articles on the role of the chief data officer. She was named to DC’s Top 50 Women in Tech by FedScoop magazine and on the 2011 Top 25 Information Managers list by Information Management magazine.

2Copyright 2016 by Data Blueprint Slide #

• 30+ years in data management • Repeated international recognition • Founder, Data Blueprint (datablueprint.com) • Associate Professor of IS (vcu.edu) • DAMA International (dama.org) • 9 books and dozens of articles • Experienced w/ 500+ data

management practices • Multi-year immersions:

– US DoD (DISA/Army/Marines/DLA) – Nokia – Deutsche Bank – Wells Fargo – Walmart – …

Peter Aiken, Ph.D.

• DAMA International President 2009-2013

• DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd

• DAMA International Community Award 2005

PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA

MONETIZINGDATA MANAGEMENT

Unlocking the Value in Your Organization’s

Most Important Asset.

The Case for theChief Data OfficerRecasting the C-Suite to LeverageYour Most Valuable Asset

Peter Aiken andMichael Gorman


Copyright 2016 by Data Blueprint Slide #

Developing Your Data Strategy: Ensuring Alignment with Business Strategy, and Making it Practical and Actionable

• What is a Data Strategy?

• Implementing a Data Strategy

• Why is it so hard?

• Q&A


Data StrategyItShould BeConcise,Actionable, andUnderstandablebyBusinessandIT!

PeterJ.Aiken•ToddHarbour

4

Peter Aiken • Todd HarbourForward by Micheline Casey, CDO#1




PeterJ.Aiken•ToddHarbourPeter Aiken • Todd HarbourForward by Micheline Casey, CDO#1




• Q&A


IT Business

Data

As Is State of Data (as Perceived)

|————— Project-based —————| |——— Program-based ———|

|——————————————— Program-based ——————————————|


IT Business

Data

|————— Project-based —————|

Desired To Be State of Data (as Understood)

Data Strategy Framework


• Benefits & Success Criteria • Capability Targets • Solution Architecture • Organizational Development

Solution

• Leadership & Planning • Project Dev. & Execution • Cultural Readiness

Road Map

• Organization Mission • Strategy & Objectives • Organizational Structures • Performance Measures

Business Needs• Organizational / Readiness • Business Processes • Data Management Practices • Data Assets • Technology Assets

Current State

• Business Value Targets • Capability Targets • Tactics • Data Strategy Vision

Strategic Data Imperatives

Business Needs

Existing Capabilities

ExecutionBusiness Value

New Capabilities

What is a Strategy?

• Current use derived from military • "a pattern in a stream of decisions" [Henry Mintzberg]


Former Walmart Business Strategy


Every Day Low

Price

Guiding Principle


Strategy must be the Business and

the Business must be the Strategy

Simon Sinek: How great leaders inspire action


• “It’s not what you do, it’s why you do it”

• “People don't buy what you do - they buy why you do it”

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

What

How

Why

Mike Tyson

• “Everybody has a plan until they get punched in the face.” – http://f--f.info/?p=23071


Organizational Assets• Cash & other financial instruments • Real property • Inventory • Intellectual Property • Human

– Knowledge – Skills – Abilities

• Financial • Organizational reputation • Good will • Brand name • Data!!!


We believe ...

Data Assets

Financial Assets

RealEstate Assets

Inventory Assets

Non-depletable

Available for subsequent

use

Can be used up

Can be used up

Non-degrading √ √ Can degrade

over timeCan degrade

over time

Durable Non-taxed √ √

Strategic Asset √ √ √ √

• Today, data is the most powerful, yet underutilized and poorly managed organizational asset

• Data is your – Sole – Non-depletable – Non-degrading – Durable – Strategic

• Asset – Data is the new oil! – Data is the new (s)oil! – Data is the new bacon!

• Our mission is to unlock business value by – Strengthening your data management capabilities – Providing tailored solutions, and – Building lasting partnerships


Asset: A resource controlled by the organization as a result of past events or transactions and from which future economic benefits are expected to flow [Wikipedia]








• Q&A

What is a data strategy and why have one?✤ A data strategy aligns with these priorities, goals, and objectives

to scope and prioritize key data and analytics initiatives and activities. Ensures investment strategy into the right data capabilities and technologies.

✤ A data strategy is about leveraging data to create business value.

✤ Data is your competitive advantage - you need a strategy for ensuring it stays that way!

✤ “deepen the moat”

✤ change what it means for companies to compete against you

High-performing companies are more data driven

✤ Companies that put data at the center of marketing and sales decision improve marketing ROI by 15-20% (McKinsey, “Big Data, Analytics, and the Future of Marketing and Sales”, 2013)

✤ Companies that successfully use data outperform peers by up to 20% (EY, “Ready for takeoff?”, 2014)

✤ Firms that adopt data-driven decision making have output and productivity that is 5-6% higher than what would be expected given other investments and, in other performance measures such as asset utilization, ROE, and market value (MIT, “Strength in Numbers: How does DDD Affect a Firm’s Performance”, Brynjolfsson/Hitt/Kim, 2011)

✤ High performing organizations report significantly more advanced capabilities across all data capability areas (McKinsey, “The need to lead in data and analytics”, 2016):

✤ Five times likelier than their low-performing peers to have tools and expertise to work with unstructured and real-time data

✤ Twice as likely to make data accessible across the organization

✤ More diligent in measuring results

Industry leaders who do more with data and analytics deliver the following value:

What are key characteristics of a good data strategy?✤ aligns with business goals and

objectives

✤ is actionable, measurable, and relevant

✤ identifies key support, resources, and constraints

✤ is a living document

✤ adds value to the organization!

Data strategy development - the process

✤ pre-planning

✤ alignment with organization strategy

✤ components and prioritization

✤ development

✤ lessons learned

Gatherinputsandar.facts

Conductinterviews

andassessments

Developanditeratestrategy

Socializefinalplan

Finalizestrategyand

budget

Conductstakeholderreviews

The pre-planning process

✤ What will the data strategy development process look like and how will it be gated?

✤ Identify key stakeholders and participants

✤ Create communications plan

✤ Have an idea before you set out of when it’s ‘good enough’

Align with organizational strategic planning processes

✤ Most organizations have a formal strategic planning process and cycle - understand it, leverage it!

✤ All organizations have a budgeting process - you need it!

Development process

Gatherinputsandar.facts

Conductinterviews

andassessments

Developanditeratestrategy

Socializefinalplan

Finalizestrategyand

budget

Conductstakeholderreviews

Key components of a data strategy

✤ Background

✤ Vision, business case, and benefits

✤ Goals, objectives, strategies, and initiatives

✤ Implementation roadmap and priorities

✤ Risks and success enablers

✤ Budgets estimates

✤ KPIs and Metrics

Prioritizing initiatives

Prioritizing initiatives

✤ Value add to the organization based on business goals and objectives

✤ Key data capabilities or products your organization needs

✤ Look at existing projects to identify what is leverageable or creates multiplier effects

✤ Other dimensions could include: business unit-focused work; data domain work; functional work; systems work

✤ Identify key value points along the way!

Tell the story!

✤ Promote empathy - design thinking construct

✤ What are the narratives that will strike a chord with your stakeholders?

✤ What are the user personas or use cases that will get people excited?

✤ Stories reveal the hopes, dreams, and aspirations of organizations

Perform a post-mortem

✤ What worked?

✤ What didn’t work?

✤ Where can we improve next time?

✤ Gather lessons learned








• Q&A

Seven Deadly Data Sins1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic Means of

Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data

Strategy Implementation 7. Failing To Address

Cultural And Change Management Challenges


Critical Factors• There Are No Unicorns • Changing is Hard • Compensate for the Lack of Data Competencies


Changing is Hard


adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987

Culture is the biggest impediment to a

shift in organizational thinking about data

The Enterprise Data Executive Takes One for the Team


Two Phase Approach to Data Strategy


1. Not Understanding Data-Centric Thinking 2. Lacking Qualified Data Leadership 3. Not implementing a Robust, Programmatic

Means of Developing Shared Data 4. Not Aligning The Data Program with IT Projects 5. Failing to Adequately Manage Expectations 6. Not Sequencing Data Strategy Implementation 7. Failing To Address Cultural And Change

Management Challenges

My Barn had to pass a foundation inspection

• Before further construction could proceed • No IT equivalent in most organizations


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

greaterrisk(with thanks to Tom DeMarco)

Data Management Practices Hierarchy

Advanced Data

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

Foundational Data Practices

Data Platform/Architecture

Data Governance Data Quality

Data Operations

Data Management Strategy

Technologies

Capabilities







• Q&A



PeterJ.Aiken•ToddHarbour

39

Peter Aiken • Todd HarbourForward by Micheline Casey, CDO#1

Two Books


PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA

MONETIZINGDATA MANAGEMENT

Unlocking the Value in Your Organization’s

Most Important Asset.

Thanks!

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

Copyright 2016 by Data Blueprint Slide # 42