peter aiken and michael gorman the case for the chief data ... · pdf...

Recasting the C-Suite to Leverage your most Valuable Asset

Presented by Peter Aiken, Ph.D.10124 W. Broad Street, Suite C

Glen Allen, Virginia 23060804.521.4056

The Case for the Chief Data Officer

Data

The Case for theChief Data O!cerRecasting the C-Suite to LeverageYour Most Valuable Asset

Peter Aiken andMichael Gorman

Copyright 2013 by Data Blueprint

2

Peter Aiken, PhD• 25+ years of experience in data

management• Multiple international awards &

recognition• Founder, Data Blueprint (datablueprint.com)

• Associate Professor of IS, VCU (vcu.edu)

• President, DAMA International (dama.org)

• 8 books and dozens of articles• Experienced w/ 500+ data

management practices in 20 countries• Multi-year immersions with

organizations as diverse as the US DoD, Nokia, Deutsche Bank, Wells Fargo, and the Commonwealth of Virginia

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The Case for theChief Data O!cerRecasting the C-Suite to LeverageYour Most Valuable Asset

Peter Aiken andMichael Gorman


CIOs

• Have accomplished astounding technological feats

• Have developed excellent organizational skill sets

• Have delivered phenomenal business value

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5

Wordle.net

• A bit of history- Clinger Cohen Act - how's it going?

• Motivations: - Poor data management performance to date

➡ (requires additional or different effort) - Recognition that data is not a project

➡ (requires a different approach)- Lack of domain expertise

➡ (requires different career preparation)• The role of a CDO - three necessary but insufficient

prerequisites: 1. Dedicated solely to data asset leveraging2. Unconstrained by an IT project mindset3. Reporting directly to the business


The Case for the Chief Data OfficerRecasting the C-Suite to Leverage your most Valuable Asset

6

Copyright 2013 by Data Blueprint 7

Motivation• Organizations:

– $600 billion annually due to poor DM practices– Remain unaware of the root causes of their losses

• IT Professionals/Data Managers must:– Gain executive-level approval for basic DM investments– Must monetize these lost opportunities and related costs

• To avoid an unfortunate loop: – Management focused on fixing symptoms– Cannot address the underlying problems

• Business performance will be positively influenced• IT projects will better support business missions• Top management is more likely to support DM • Practitioners can prioritize relative IS investments

and adjust portfolios according to business needs• The bigger the organization, the more important

data assets are to the organization • This is due to the increased leverage obtainable

by larger organizations


IT Project Failure Rates• Recent IT project failure rates statistics

can be summarized as follows: – Carr 1994

• 16% of IT Projects completed on time, within budget, with full functionality

– OASIG Study (1995)• 7 out of 10 IT projects "fail" in some respect

– The Chaos Report (1995)• 75% blew their schedules by 30% or more• 31% of projects will be canceled before they ever get completed• 53% of projects will cost over 189% of their original estimates• 16% for projects are completed on-time and on-budget

– KPMG Canada Survey (1997)• 61% of IT projects were deemed to have failed

– Conference Board Survey (2001) • Only 1 in 3 large IT project customers were very “satisfied"

– Robbins-Gioia Survey (2001)• 51% of respondents viewed their large IT implementation project as unsuccessful

– MacDonalds Innovate (2002)• Automate fast food network from fry temperature to # of burgers sold-$180M USD write-off

– Ford Everest (2004)• Replacing internal purchasing systems-$200 million over budget

– FBI (2005)• Blew $170M USD on suspected terrorist database-"start over from scratch" http://www.it-cortex.com/stat_failure_rate.htm (accessed 9/14/02)

New York Times 1/22/05 pA31

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1 in 3 IT projects suffers on• Price• Schedule• Functionality


IT Project Failure Rates (moving average)

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Source: Standish Chaos Reports as reported at: http://www.galorath.com/wp/software-project-failure-costs-billions-better-estimation-planning-can-help.php

0%

15%

30%

45%

60%

1994 1993 1998 2000 2002 2004 2009

16%

27% 26%28%

34%

29%

32%

53%

33%

46%

49%51%

53%

44%

31%

40%

28%

23%

15%

18%

24%

Failed Challenged Succeeded


"Most significant IT reform of the last decade"

10

1996 (passed)• Establish Agency CIOs

– Link IT investments to accomplishments

• Requires – CIO "Milestone Decision"

assessment– Establish process to select,

manage and control IT investments (CMM Level 2)

• Responsible– "developing, maintaining, and

facilitating the implementation of a sound and integrated information technology architecture"


The Clinger-Cohen Act: 10 Years Later

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2006 (assessed)• Mixed results

– Federal Enterprise Architecture

– "The landscape of federal information technology is not a clearly defined plain of reference points that can be empirically studied in pure isolation"

– Planned 5% decrease in IT costs– 9% increase instead

http://www.govexec.com/federal-news/2006/07/the-clinger-cohen-act-10-years-later/22227/

• Some guidance exists• Some experiences gained• Some progress has been made

£12bn NHS computer system is scrapped


• The biggest civilian IT project of its kind in the world, it has already squandered at least £12.7billion. Some estimates put the cost far higher.

• Analysts say the sum would have paid the salaries of more than 60,000 nurses for a decade.

• Following an official review, the ‘one size fits all’ IT project will be replaced by much cheaper regional initiatives, with hospitals and GPs choosing the IT system they need.

• Read more: http://www.dailymail.co.uk/news/article-2040259/NHS-IT-project-failure-Labours-12bn-scheme-scrapped.html#ixzz2R1yb9F1i

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Billion-Dollar Flop: Air Force Stumbles on Software Plan


• In policy circles, problems that are mind-bogglingly difficult or impossible to solve, like global warming, are formally termed “wicked.”

• For the United States Air Force, installing a new software system has certainly proved to be a wicked problem. Last month, it canceled a six-year-old modernization effort that had eaten up more than $1 billion. When the Air Force realized that it would cost another $1 billion just to achieve one-quarter of the capabilities originally planned — and that even then the system would not be fully ready before 2020 — it decided to decamp.

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A Digital Universe ...• Consists of two species of bits:

– Differences in space– Differences in time– Logic can be done using zeros and

ones [Leibniz 1679]

• Structure bits– Vary in space but are invariant across time– These are memory (data)

• Sequence bits– Vary across time but are invariant across space– These are code

• While both are equally important to technology, more research and attention has been focused on the code than on the data [articulation from Dyson 2012]

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Observation

• Fred Brooks Jr.'s argumentthat data representation is the essence of programming. – "Show me your flowchart and conceal

your tables, and I shall continue to be mystified. Show me your tables, and I won't usually need your flowchart; it'll be obvious."

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17

Two Views of the Same Individual

Business are being bombardedoffers for these services


Organizations Surveyed

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• Results from more than 500 organizations

• 32% government• Appropriate

public company representation

• Enough data to demonstrate European organization DM practices are generally more mature

Local Government4%

State Government Agencies17%

Federal Government11%

Public Companies 58%

International Organizations10%


Not Enough Data Management Involvement

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Data Warehousing

XML

Data Quality

Customer Relationship Management

Master Data Management

Customer Data Integration

Enterprise Resource Planning

Enterprise Application Integration

Initiative Leader Initiative Involvement Not Involved

0

0.09

0.18

0.27

0.36

0.45

SuccessfulPartial Success

Don't know/too soon to tellUnsuccessful

Does not exist

• In 25 years:– "Successful" DM organizations fell from 43% to 15%– "Unsuccessful" increased from 5% to 21%.


% of DM organizations labeled "successful"

20

19812007


CIOs are distancing themselves from DM

21

1981 2007

Percentage Reporting Directly

to the CIO74% 43%

Percentage reporting 3 or

more levels below the CIO

26% 57%


Why Data Projects Fail by Joseph R. Hudicka

• Assessed 1200 migration projects!

– Surveyed only experienced migration specialists who have done at least four migration projects

• The median project costs over 10 times the amount planned!

• Biggest Challenges: Bad Data; Missing Data; Duplicate Data

• The survey did not consider projects that were cancelled largely due to data migration difficulties

• "… problems are encountered rather than discovered"

$0 $125,000 $250,000 $375,000

Median Project Expense

Median Project Cost

Joseph R. Hudicka "Why ETL and Data Migration Projects Fail" Oracle Developers Technical Users Group Journal June 2005 pp. 29-31

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2/3rds have not formally established IA program

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Forrester information architecture research


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4% have almost all they need from IA


Root Cause Analysis

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• Symptom of the problem– The weed– Above the surface – Obvious• The underlying

Cause– The root– Below the surface – Not obvious• Poor Information

Management Practices

Asking "why" repeatedly!


Ishikawa Fishbone Diagrams

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• Why is infant mortality so high?– Malnourished mothers• Why are mothers malnourished?

– Substandard biology educations in high school• Why do are biology programs substandard?

– Poor education of high school biology teachers• Why do we have poor biology teacher education?

– Biology profession unaware of consequences

• Why are so many organizational technology experiences so poor?–Misunderstanding of data's role in IT• Why do so few understand data's role in IT?

–Little, if any, focus on enterprise-wide data use in the educational system

• Why is the educational system not addressing this gap?–Lack of recognition by the system• Why has the system not yet been made aware

of this deficiency?–Lack of understanding at the C-level of these

issues• Why do they not understand?

–Little, if any, focus on enterprise-wide data use in the educational system


Data InflationUnit Size What+it+means

Bit+(b) 1+or+0Short+for+“binary+digit”,+a=er+the+binary+code+(1+or+0)+computers+use+to+store+and+process+data

Byte+(B) 8+bitsEnough+informaCon+to+create+an+English+leEer+or+number+in+computer+code.+It+is+the+basic+unit+of+compuCng

Kilobyte+(KB) 1,000,+or+210,+bytes From+“thousand”+in+Greek.+One+page+of+typed+text+is+2KB

Megabyte+(MB) 1,000KB;+220+bytesFrom+“large”+in+Greek.+The+complete+works+of+Shakespeare+total+5MB.+A+typical+pop+song+is+about+4MB

Gigabyte+(GB) 1,000MB;+230+bytes From+“giant”+in+Greek.+A+twoWhour+film+can+be+compressed+into+1W2GB

Terabyte+(TB) 1,000GB;+240+bytesFrom+“monster”+in+Greek.+All+the+catalogued+books+in+America’s+Library+of+Congress+total+15TB

Petabyte+(PB) 1,000TB;+250+bytesAll+leEers+delivered+by+America’s+postal+service+this+year+will+amount+to+around+5PB.+Google+processes+around+1PB+every+hour

Exabyte+(EB) 1,000PB;+260+bytes Equivalent+to+10+billion+copies+of+The+Economist

ZeEabyte+(ZB) 1,000EB;+270+bytes The+total+amount+of+informaCon+in+existence+this+year+is+forecast+to+be+around+1.2ZB

YoEabyte+(YB) 1,000ZB;+280+bytes Currently+too+big+to+imagine

The prefixes are set by an intergovernmental group, the International Bureau of Weights and Measures. Source: The Economist Yotta and Zetta were added in 1991; terms for larger amounts have yet to be established

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Driver:


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• Increasing demand• Increasing amount• Heightened public

and corporate sensitivity to security, privacy, and compliance

• Data dependent IT initiatives (BI, SOA, Analytics, Big Data ...)

• New data emphasis • Leveraging data for

competitive advantage and profitability


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A likely state of your data

Very

Silo

’ed or

conf

lictin

g data

sour

ces

Multiple Data Sources

Inconsistent data definitions of

common terms

IT are data owners

Lots of Data….Minim

um Inform

ation

Inconsistent Data Quality

Difficult to report and mine against

Redundancy

Multiple changes to source system


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A likely state of your data management efforts

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016


5% Sales Increase Versus Data Volume

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Sales Data Volume


The Situation

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Aspirational Data in the Cloud

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• This is a the approximate level of detail but let's next examine two extreme implementation examples 1) forklift 2) optimal 3) problems with above a) no basis for decisions made b) no inclusion of architecture/engineering concepts c) no idea that these concepts are missing from the process


Getting into the Cloud

Transform

LessCleanerMore shareable ... data

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• "We want to move our data management program to the next level"– Question: What level are you now?

• You are currently managing your data,– But, if you can't measure it, – How can you manage it effectively?

• How do you know where to put time, money, and energy so that data management best supports the mission?


Strategic Motivation"One day Alice came to a fork in the road and saw a Cheshire cat in a tree. Which road do I take? she asked. Where do you want to go? was his response. I don't know, Alice answered. Then, said the cat, it doesn't matter."

Lewis Carroll from Alice in Wonderland

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36

Cruiser Collector


Cruiser Collector

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Data Program Coordination

Feedback

DataDevelopment


StandardData

Organizational DM Practices Value-added WorkproductsOrganizational Strategies

Goals

BusinessData

Business Value

Application Models & Designs

Implementation

Direction

Guidance

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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


Five Integrated DM Practice Areas

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Manage data coherently.

Share data across boundaries.

Assign responsibilities for data.Engineer data delivery systems.

Maintain data availability.


Organizational Data Integration

Data Stewardship Data Development

Data Support Operations

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0.4%

0.4%

0.3%0.3%

0%

0.5%

0%

1.0%

1.5%

5.4%

1.3%3.0%

4.9%4.9%

1.7%

9.8%8.6%

7.6%

15.7%

20.5%

Tota

l % o

f non

-rela

tiona

l pro

cess

ing

Percentage of non-relational processing (excluding mission-critical)Percentage of mission-critical, non-relational processing


"The rumors of the demise of non-relational processing are greatly exaggerated" (Mark Twain)

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• 68% using hierarchical (typically IMS or Adabase)

• 20% reporting operational network DBMS• Virtually no textbook education

Percentage of organizations relying on x amount of non-relational database processing


5 Basic Data Structures

Indexed Sequential File: Built-in index permits location of records of persons with last names starting with "T"

Index

Program: Where is the record for person "Townsend?"

Index: Start looking here where the "Ts" are stored

Relational Database: Records are related to each other using relationships describable using relational algebra

Flat File: Records are typically sorted according to some criteria and must be searched from the beginning for each access

Program: Must start at the beginning and read each record when looking for

person "Townsend?"

Network Database: Records are related to each other using arranged master records associated with multiple detail records using linked lists and pointers

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AssociativeConcept-orientedMulti-dimensional

Star schemaXML database

Hierarchical Database: Records are related to each other hierarchically using 'parent child' relationships


Feedback

DataDevelopment


StandardData

Organizational DM Practices and their Inter-relationshipsOrganizational Strategies

Goals

BusinessData

Business Value


Implementation

Direction

GuidanceIdentifying, modeling, coordinating, organizing, distributing, and architecting data shared across business areas or organizational boundaries.

Ensuring that specific individuals are assigned the responsibility for the maintenance of specific data as organizational assets, and that those individuals are provided the requisite knowledge, skills, and abilities to accomplish these goals in conjunction with other data stewards in the organization.

Initiation, operation, tuning, maintenance, backup/recovery, archiving and disposal of data assets in support of organizational activities.

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Specifying and designing appropriately architected data assets that are engineered to be capable of supporting organizational needs.


DataStewardship


Data Asset Use

IntegratedModels

Defining, coordinating, resourcing, implementing, and monitoring organizational data program strategies, policies, plans, etc. as coherent set of activities.


Feedback

DataDevelopment


StandardData

Organizational DM Practices Value-added WorkproductsOrganizational Strategies

Goals

BusinessData

Business Value


Implementation

Direction

Guidance

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DataStewardship


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

Data becomes a fuel!


Various Maturity Frameworks

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Usage basis Make it Happen

Make it Happen Faster

What Happened

?

Why did it happen?

What will happen?

Make it happen by

itself

What do I want to

happen?

How do we make it

happen better?

What should we do next?

Content basis Events Trans- actions Reporting Analyzing Predictive Operation-

alizeClosed

loopCollabor -

ative Foresight

Capability basis Initial Defined

Organization Basis Innovate Operate: Consolidate OptimizeIntegrate

OptimizedManagedRepeatable

Data is a lubricant!

Adapted from John Ladley


Data Management Capability Maturity Model Levels

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

Initial(1)

Repeatable(2)

We have DM experience and have the ability to

implement disciplined processes

We have experience that we have standardized so that all in

the organization can follow itDefined

(3)

Managed(4)

We manage our DM processes so that the whole organization can follow our standard

DM guidance

Optimizing(5)We have a process for improving our DM capabilities

One concept for process improvement, others include:

• Norton Stage Theory• TQM• TQdM• TDQM• ISO 9000

and focus on understanding current processes and determining where to make improvements.


Assessment Components

Data Management Practice AreasData 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 stewardshipDesignating specific individuals caretakers for certain data

Data development Efficient delivery of data via appropriate channels

Data support Ensuring reliable access to data

Capability Maturity Model Levels Examples of practice maturity

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

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

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

4 - ManagedWe 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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• CMU's Software Engineering Institute (SEI) Collaboration

• Results from hundreds organizations in various industries including:✓ Public Companies ✓ State Government Agencies✓ Federal Government✓ International Organizations

• Defined industry standard• Steps toward defining data management

"state of the practice"

Data Management Practices Measurement (DMPA)

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Organizational Data Integration

Data Stewardship

Data Development

Data Support Operations

Focus: Implementation

and Access

Focus: Guidance and

Facilitation

Optimizing (V)

Managed (IV)

Documented (III)

Repeatable (II)

Initial (I)

Client Industry Competition All Respondents


Development guidance

Data Adminstration

Support systems

Asset recovery capability

Development training

0 1 2 3 4 5

Data Management Practices Assessment

Challenge

Challenge

Challenge

Result 1

Result 2

Result 3

Result 4

Result 5

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Comparison of DM Maturity 2007-2012

50

1

2

3

4

5

Data

Prog

ram

Coor

dinati

on

Orga

nizati

onal

Data

Integ

ratio

n

Data

Stew

ards

hip

Data

Deve

lopme

nt

Data

Supp

ort O

pera

tions

2007 Maturity Levels 2012 Maturity Levels


Conclusion must be?1. CIOs are unaware of the

strategic nature of data; or

2. CIOs are not concerned about how data management is accomplished in their organizations; or

3. CIOs think data management is being adequately accomplished in their organizations

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• Approximately, 10% percent of organizations achieve parity and (potential positive returns) on their DM investments

• Only 30% of DM investments achieve tangible returns at all

• Seventy percent of organizations have very small or no tangible return on their DM investments


Largely Ineffective Investments

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Investment <= Return10%

Investment > Return20%

Return ≈ 070%


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• 60 GB of data/second• 200,000 hours of big data

will be generated testing systems

• 2,000 hours media coverage/daily

• 845 million Facebook users averaging 15 TB/day

• 13,000 tweets/second• 4 billion watching• 8.5 billion devices

connected

2012 London Summer Games

• Faster processors outstripped not only the hard disk, but main memory – Hard disk too slow– Memory too small

• Flash drives remove both bottlenecks– Combined Apple and Yahoo have

spend more than $500 million to date

• Make it look like traditional storage or more system memory– Minimum 10x improvements– Dragonstone server is 3.2 tb flash

memory (Facebook)

• Bottom line - new capabilities!


"There’s now a blurring between the storage world and the memory world"

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• von Neumann bottleneck (computer science)– "An inefficiency inherent in

the design of any von Neumann machine that arises from the fact that most computer time is spent in moving information between storage and the central processing unit rather than operating on it"[http://encyclopedia2.thefreedictionary.com/von+Neumann+bottleneck]

• Michael Stonebraker– Ingres (Berkeley/MIT)– Modern database

processing is approximately 4% efficient

• Many "big data architectures are attempts to address this, but:– Zero sum game– Trade characteristics

against each other• Reliability• Predictability

– Google/MapReduce/Bigtable

– Amazon/Dynamo– Netflix/Chaos Monkey– Hadoop– McDipper

• Big data exploits non-von Neumann processing


Non-von Neumann Processing/Efficiencies

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IBM's Data Baby


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A likely state of your data

Very

Silo

’ed or

conf

lictin

g data

sour

ces

Multiple Data Sources

Inconsistent data definitions of

common terms

IT are data owners

Lots of Data….Minim

um Inform

ation

Inconsistent Data Quality

Difficult to report and mine against

Redundancy

Multiple changes to source system

• 5 Data management practices areas / data management basics ...

• ... are necessary but insufficient prerequisites to organizational data leveraging applications that is self actualizing data or advanced data practices


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

Hierarchy of Data Management Practices (after Maslow)

Basic Data Management Practices– Data Program Management– Organizational Data Integration– Data Stewardship– Data Development– Data Support Operations

http://3.bp.blogspot.com/-ptl-9mAieuQ/T-idBt1YFmI/AAAAAAAABgw/Ib-nVkMmMEQ/s1600/maslows_hierarchy_of_needs.png









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Application-Centric Development

Original articulation from Doug Bagley @ Walmart

60

t

t

Strategy

Goals/Objectives

Systems/Applications

Network/Infrastructure

Data/Information

t

• In support of strategy, the organization develops 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 that data is formed

around the application and not the information requirements

– Process are narrowly formed around applications

– Very little data reuse is possible


Payroll Application(3rd GL)Payroll Data

(database)

R& D Applications(researcher supported, no documentation)

R & DData(raw) Mfg. Data

(home growndatabase)

Mfg. Applications(contractor supported)

FinanceData

(indexed)

Finance Application(3rd GL, batch

system, no source)

Marketing Application(4rd GL, query facilities, no reporting, very large)

Marketing Data(external database)

Personnel App.(20 years old,

un-normalized data)

Personnel Data(database)

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Typical System Evolution


Silos

• Not an acronym for SIngle LOcation

62


History Lesson

• "In the first decades of computing, the programs in a corporation became an unruly mess, far removed from the orderliness one would normally associate with an engineering discipline." – James Martin 1981

63


Comments from CIOs• What a Mess!• CIOs have demanding jobs as information

systems in an organization are often taken for granted until something breaks down.

• The CIO is responsible for explaining to executive management the complex nightmare this industry has gotten itself into over the past 40 years and why equipment must be constantly retrofitted or replaced.

64

Einstein Quote


65

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


What does it mean to treat data as an organizational asset?• Assets are economic resources

– Must own or control– Must use to produce value– Value can be converted into cash

• An asset is a resource controlled by the organization as a result of past events or transactions and from which future economic benefits are expected to flow to the organization [Wikipedia]

• With assets:– Formalize the care and feeding of data

• Cash management - HR planning

– Put data to work in unique and significant ways• Identify data the organization will need

[Redman 2008]

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Data-Centric Development Flow


67

t

t

Strategy

Goals/Objectives

Data/Information



t

• 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


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Data Centric Principles1. Help organizations prepare for future change by implementing a flexible and

adaptable organizational data architecture;2. Focus data assets to efficiently and effectively support organizational strategy;3. Increase the percentage of time available to accomplish this by a lower

percentage of time on maintenance activities;4. Reducing organizational data ROT;5. Remaining data will receive more "attention" with respect to quality/security/reuse;6. Reducing the amount and complexity of the organizational code-base;7. Reducing the amount of time and efforts and risk associated with IT projects;8. Engineer flexibility and adaptability into data architectures instead of attempting to

retrofit them in after they are in production;9. Produce more, reusable data-focused work products;10.When faced with a choice between chaos versus understanding, organizations will

gravitate towards a cheaper, more understandable solution;11.Same comment when comparing complexity versus ease of implementation;12.Decrease the time spend understanding versus time spent considering the data-

focused portions of organizational strategy;13.Uncertain benefits versus engineerable benefits.

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Data Centric Principles• Faster

– Planning for data-focused aspects of IT will require less fact-finding/guesswork

– Many data transformations can be "ironed out" of processing

– Error correction is faster due to less data volume/more understandable data

• Better– Quality of the remaining data can be more easily improved– Resulting data architecture will be more understandable/responsive– Strategy can be explicitly linked to KPIs (or whatever)

• Cheaper– Maintain only what is important – can experience 80% reduction in volume– Less data leads to fewer physical processing/governance requirements– Less diagnostic/planning time required to address challenges

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Strategy

Goals/Objectives

Data/Information




Strategy

Goals/Objectives



Data/Information


This represents a gradual shift from

application to data-centric

71









72


History (such as it is)• Automate existing manual processing • Data management was simple

– Running millions of punched cards through banks of sorting, collating and tabulating machines

– Results printed on paper or punched onto more cards

– Data management meant physically storing and hauling around punched cards

• Tasks (check signing, calculating, and machine control) were implemented to provide automated support for departmental-based processing

• Creating information silos

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Data Processing Manager

75

• Fifty years ago, data management was simple. Data processing meant running millions of punched cards through banks of sorting, collating and tabulating machines, with the results being printed on paper or punched onto still more cards. And data management meant physically storing and hauling around all those punched cards (Hayes 2002).


Chief Information Officer

76

CIO Responsibilities


77

• A job title commonly given to the most senior executive in an enterprise responsible for the information technology and computer systems that support enterprise goals


CFO Necessary Prerequisites/Qualifications• CPA

• CMA

• Masters of Accountancy

• Other recognized degrees/certifications

• These are necessary but insufficient prerequisites/qualifications

78


CIO Qualifications• No specific qualifications• Typically technological fields: computer science,

software engineering, or information systems • Many have Master of Business Administration or

Master of Science in Management degrees• Recently CIOs' leadership capabilities, business

acumen and strategic perspectives have taken precedence over technical skills.

• It is now quite common for CIOs to be appointed from the business side of the organization, especially if they have project management skills.

79


Qualifications

Leadership capabilities, business acumen and strategic perspectives have taken precedence over technical skills

80

Data


What do we teach knowledge workers about data?

81

What percentage of the deal with it daily?


What do we teach IT professionals about data?• 1 course

– How to build a new database

– 80% if UT expenses are used to improve existing IT assets

• What impressions do IT professionals get from this education?– Data is a technical

skill that is used to develop new databases

• This is not the best way to educate IT and business professionals - every organization's– Sole, non-depletable,

non-degrading, durable, strategic asset

82

Associate Productivity

Customer Insights

Human Capital Corp. Reputation Acquisition Strategic Planning

Real estate CRM CRM

Analytic and reporting processes

Corporate Reputation - Risk Management, Compliance, Marketing, IT and Data Governance

Corporate Processes

Corporate Data

Inventory Mgmt

Tran

sfor

mat

ion

Por

tfol

io

Supply Chain

Multi ChannelMerchant Tools Supply Chain

Strategic Initiatives

AcctingSales

Transactional Processing

Logistics Associate Locations and Codes

Item

Customer Suppliers

Retail Planning


No clear connection exists between to business priorities and IT initiatives

83

Grow expenses slower than

sales

Grow operating income faster

than sales

Pass on savings

Drive efficiency with technology

Leverage scale globally

Leverage expertise

Deploy new formats

Grow productivity of existing assets

Attract new members

Expand into new channels

Enter new markets

Make acquisitions

Produce significant free

cash flow

Drive ROI performance

Deliver greater shareholder

value C

usto

mer

P

ersp

ectiv

e Open new stores

Develop new, innovative formats

Appeal to new demographics

Integrate shopping

experience

Develop new, innovative formats

Remain relevant to all

customers

Increase "Green" Image

Inte

rnal

P

ersp

ectiv

e

Create competitive advantages

Improve use of information

Strengthen supply chain

Improve Associate

productivity

Making acquisitions

Increase benefit from our global expertise

Present consistent view and

experience

Integrate channels Match staffing

to store needs Increase sell through

Fina

ncia

l P

ersp

ectiv

e Reduce expenses

Inventory Management

Human and Intell. Capital investment

Manage new facilities

Improve Sales and margin by facilities

Increased member-base

revenues

Revenue growth Cash flow Return on

Capital

Walmart Strategy Map

See more uniform brand and retail experience

Leverage Growth Return

Gross Margin Improvement

CE

O P

ersp

ectiv

e

Attract more customers & have customer purchasing more

( Alignment Gap )

Adapted from John Ladley

Data


Comments from CIOs• On CIOs as strategic business partners

• A small percentage of CIO’s have truly attained that status, despite many who claim they have. I would guess fewer than 10% of the CIO population achieves that goal. Perhaps we are expecting the CIO to wear too many hats. When they fail to effectively perform in all of those roles their time in position is limited, which might help explain why CIO longevity is so short (CIO = “Career Is Over”).

84


Q1Keeping the doors open

(little or no proactive data management)

Q2Increasing organizational efficiencies/effectiveness

Q3Using data to create

strategic opportunitiesQ4

Both(Cash Cow)

Improve Operations

Inno

vatio

n

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

Enterprise Data Strategy Choices


Innovation• Innovation is the development of new customers value

through solutions that meet new needs, inarticulate needs, or old customer and market needs in new ways. This is accomplished through different or more effective products, processes, services, technologies, or ideas that are readily available to markets, governments, and society.

• Innovation differs from invention in that innovation refers to the use of a better and, as a result, novel idea or method, whereas invention refers more directly to the creation of the idea or method itself.

• Innovation differs from improvement in that innovation refers to the notion of doing something different (Lat. innovare: "to change") rather than doing the same thing better.

86


87

Bills of Mortality by Captain John Graunt


88

Bills of Mortality


89Mortality Geocoding

Where is it happening?


90

Plague Peak

When is it happening?

("Whereas of the Plague")


91

Black Rats or Rattus Rattus

Why is it happening?

Black Rats or Rattus Rattus

Why is it happening?


92

What will happen?


93

John Snow's 1854 Cholera Map of London


International Chemical Company Engine Testing

94

• $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– Test costs range up to

$250,000!

95

1.Manual transfer of digital data2.Manual file movement/duplication3.Manual data manipulation4.Disparate synonym reconciliation 5.Tribal knowledge requirements 6.Non-sustainable technology


Overview of Existing Data Management Process


Data Integration Solution• Integrated the existing systems to

easily search on and find similar or identical tests

• Results:– Reduced expenses– Improved competitive edge

and customer service– Time savings and improve operational

capabilities

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

96


Data Data

Data

Information

Fact Meaning

Request

A Model Specifying Relationships Among Important Terms

[Built on definition by Dan Appleton 1983]

Intelligence

Use

1. Each FACT combines with one or more MEANINGS. 2. Each specific FACT and MEANING combination is referred to as a DATUM. 3. An INFORMATION is one or more DATA that are returned in response to a specific REQUEST 4. INFORMATION REUSE is enabled when one FACT is combined with more than one

MEANING.5. INTELLIGENCE is INFORMATION associated with its USES.

Wisdom & knowledge are often used synonymously

Data

Data

Data Data

97


Data Leverage

• Permits organizations to better manage their sole non-depleteable, non-degrading, durable, strategic asset - data– within the organization, and – with organizational data exchange partners

• Leverage – Obtained by implementation of data-centric technologies, processes, and human skill

sets– Increased by elimination of data ROT (redundant, obsolete, or trivial)

• The bigger the organization, the greater potential leverage exists

• Treating data more asset-like simultaneously 1. lowers organizational IT costs and 2. increases organizational knowledge worker productivity

98

Less ROT

Technologies

Process

People

He who doesn’t lay his foundations before hand, may by great abilities do so afterward ...... although with great trouble to the architect and danger to the building.


Machiavelli, Niccolo. The Prince. 19 Mar. 2004 http://pd.sparknotes.com/philosophy/prince

99

Niccolo Machiavelli (1469-1527)

You cannot architect after implementation!


100

USS Midway & Pancakes


101

What is this?

• It is tall• It has a clutch• It was built in 1942• It is still in regular use!


102

http://www.youtube.com/watch?v=Hdpf-MQM9vY&feature=player_embedded#!

360 hours or 15 days of continuous buildingThe Role of Engineering/Architecture in Rapid Development

Data Architectures are Developed in Response to Organizational Needs

! ! ! !


103

Organizational Needs

become instantiated and integrated into an Data/Information

Architecture

Informa(on)System)Requirements

authorizes and articulates sa

tisfy

spe

cific

org

aniz

atio

nal n

eeds


An organization's data architecture ...

104

Software Package 1

Software Package 2

Software Package 3

Software Package 4

Software Package 5

Software Package 6

Data Architecture

... maps between and across software packages


Comments from CIOs• Most CIO’s today are challenged with

being “experts” on technology (infrastructure and application), business process, relationship management and data management). None are successful at all and most have a bent towards only one of those areas, depending upon where they began their career and the path they took to attain their CIO role.

105









106


Out of degree and intensity, grows the organizational "data challenge"

1. Complexity

Trivial to complex

2. Intensity

Degree

107

Data Challenge

Complexity

Inte

nsity


108


CIO's are generally unsuccessful at remaining data-focused

• Question:– What is the hardest part of doing analysis?

• Answer:– Not doing design!

• Question:– What is the hardest part of a

CIO's job?• Answer:

– Remaining data focused!• Anything the CIO does that is not ...

– ... applying organizational data assets to the implementation of organizational strategy ...... is a similar distraction

109


Someone Notable Thinks DM is Important

110

excerpt from President Obama's 2012 State of the Union Address


58 Commonly Used Chief Officer Titles

111

• Chief Accounting Officer, Chief Administrative Officer, Chief Analytics Officer, Chief Audit Officer, Chief Brand Officer, Chief Business Officer, Chief Channel Officer, Chief Commercial Officer, Chief Communications Officer, Chief Compliance Officer, Chief Creative Officer, Chief Data Officer, Chief Executive Officer, Chief Financial Officer, Chief Human Resources Officer, Chief Information Officer, Chief Information Security Officer, Chief Innovation Officer, Chief Investment Officer, Chief Immigration Officer, Chief Geospatial Information Officer, Chief Knowledge Officer, Chief Leadership Officer, Chief Learning Officer, Chief Legal Officer, Chief Marketing Officer, Chief Marketing Information Officer, Chief Medical Officer, Chief Merchandising Officer, Chief Networking Officer, Chief Operating Officer, Chief Process Officer, Chief Procurement Officer, Chief Product Officer, Chief Research Information Officer, Chief Risk Officer, Chief Science Officer, Chief Stores Officer, Chief Strategy Officer, Chief Technology Officer, Chief Visionary Officer, Chief Web Officer


The "Chief Officer" Title

112

• Chief– The head or leader of an organized body of people; the person

highest in authority: the chief of police

• Chief Financial Officer (CFO)– Individual possessing the knowledge, skills, and abilities to be both

the final authority and decision-maker in organizational financial matters

• Chief Risk Officer (CRO)– Individual possessing the knowledge, skills, and abilities makes

decisions and implements risk management

• Chief Medical Officer (CMO)– Responsible for organizational medical matters. The organization,

and the public, has similar expectations for any of chief officer – especially after the Sarbanes-Oxley bill.

[dictionary.com]

ChiefCopyright 2013 by Data Blueprint

113

C-levelCopyright 2013 by Data Blueprint

114

C OXCopyright 2013 by Data Blueprint

115

ESPOQR


58 Commonly Used Chief Officer Titles

116

• Chief Accounting Officer, Chief Administrative Officer, Chief Analytics Officer, Chief Audit Officer, Chief Brand Officer, Chief Business Officer, Chief Channel Officer, Chief Commercial Officer, Chief Communications Officer, Chief Compliance Officer, Chief Creative Officer, Chief Data Officer, Chief Executive Officer, Chief Financial Officer, Chief Human Resources Officer, Chief Information Officer, Chief Information Security Officer, Chief Innovation Officer, Chief Investment Officer, Chief Immigration Officer, Chief Geospatial Information Officer, Chief Knowledge Officer, Chief Leadership Officer, Chief Learning Officer, Chief Legal Officer, Chief Marketing Officer, Chief Marketing Information Officer, Chief Medical Officer, Chief Merchandising Officer, Chief Networking Officer, Chief Operating Officer, Chief Process Officer, Chief Procurement Officer, Chief Product Officer, Chief Research Information Officer, Chief Risk Officer, Chief Science Officer, Chief Stores Officer, Chief Strategy Officer, Chief Technology Officer, Chief Visionary Officer, Chief Web Officer


The "Chief Officer" Title

117

• Chief– The head or leader of an organized body of people; the person

highest in authority: the chief of police

• Chief Financial Officer (CFO)– Individual possessing the knowledge, skills, and abilities to be both

the final authority and decision-maker in organizational financial matters

• Chief Risk Officer (CRO)– Individual possessing the knowledge, skills, and abilities makes

decisions and implements risk management

• Chief Medical Officer (CMO)– Responsible for organizational medical matters. The organization,

and the public, has similar expectations for any of chief officer – especially after the Sarbanes-Oxley bill.

[dictionary.com]


Skills Desired of CIOs• Technical/business

competencies • Timely and effective

execution• Being collaborative• Business knowledge• Creating a strategic vision• Inspire/leadership

responsibilities• Politically astute• Business acumen• Know of funding flows and

critical levers • Human capital management

• Talent evaluation, development, goal-setting and performance management

• Strategic-value creation• Creating revenue-generating

opportunities • Leadership• Influence others through

consensus building, storytelling, communications, modeling

• Networking, self-promotion, negotiating, empathy

118

Data


CIO Concerns 2007

1. People leadership2. Managing budgets3. Business alignment4. Infrastructure refresh5. Security

6. Compliance7. Resource management8. Managing customers9. Managing change10. Board politics

119

Data


Gartner 2008 CIO Business & Technology Priorities

120

Top 10 Business Priorities Top 10 Technology Priorities

Business process improvement Business intelligence applications

Attracting and retaining new customers Enterprise applications (ERP, CRM, etc.)

Creating innovative products and services Servers and storage technologies

Expanding into new markets or geographies Legacy modernization/enhancement

Reducing enterprise costs Technical infrastructure

Improving enterprise workforce effectiveness Security technologies

Expanding current customer relationships Networking, voice and data

Increasing the use of information/analytics Collaboration technologies

Targeting customers/markets more effectively Document management

Acquiring new companies/capabilities Service-oriented architecture SOA

Data

1. Integrating systems and processes2. Strategic planning/aligning IT and organizational goals3. Project management improvements4. Security and privacy measures5. Lowering costs6. Line of business initiatives7. Staff development/retention/recruitment


Initiatives that will provide greatest value in FY 2008

121

TechAmerica’s Nineteenth Annual Survey of Federal Chief Information Officers February 2009

Data

83.00%

76.00%

71.00%

68.00%

68.00%

66.00%

64.00%

64.00%

61.00%

60.00%

BI/Analytics

Virtualization

Governance/Risk/Compliance

Customer Collaboration

Mobility Solutions

Self-service Portals

Applications Harmonization

Business Process Management

Service-oriented Architecture

Unified Communications


CIOs have visionary plans/CIO innovation is not limited to IT solutions

122

Data


2010 Gartner Top 10 CIO Technology Priorities1. Cloud computing2. Virtualization3. Mobile technologies4. IT management5. Business intelligence6. Networking7. Voice and data communications8. Enterprise applications9. Collaboration technologies10.Infrastructure, and Web 2.0

123

Data


Global CIO: The Top 10 Issues For 20111. Seeing And Shaping The Future: Analytics2. The Budget Trap Becomes The Competitive-Performance Gap:

Doing more with less3. The iPad Explosion: Mobile Strategies4. Digitizing The Enterprise5. Social Media: From Grudging Acceptance To Hair-On-Fire

Evangelism6. Customer Engagement Soars To

Unprecedented Levels7. Enabling The Massively Adaptable

Data Center8. The CIO As Chief Acceleration Officer9. The Importance Of Being Global10.Optimizing Opportunities With Optimized Systems

http://www.informationweek.com/news/global-cio/interviews/229000361?pgno=1

124

Data


CIO Roles

125

Data


CIO's top 3 selection of business strategies in 2011 and projected for 2014

126

Data


CIO Infrastructure Focus

Help DeskMobileDesktop

User N

eeds

Conne

ctivit

y

Networking Telephony

Back

End

Sys

.

VirtualizationCloud SupportData Centers

127


Comments from CIOs• Gartner has been pontificating on the

evolution of the CIO role towards CPO – Chief Process Officer. So now the CIO would own all technology, all processes and all data. No other organization is experiencing this evolution into other spheres of influence. The CHRO does HR work. The CFO does financial work. The COO does operations work. However, the CIO is expected to be the head of technology, the architect of all business processes and the intelligence behind leveraging data.

128


Top Five CIO Concerns 2005-2011

129

2005 2006 2007 2008 2009 2010 2011Grant Thornton-State CIO Survey 1 1 1 1 1 1 6Ameritech ITAA Annual CIO survey 1 1 1 1 1 1 6CIO Magazine-State of the CIO 1 1 1 1 1 5UK CIO Survey 1 1Gartner Annual Priorities 1 1 1 1 1 1 1 7Informationweek Global CIO top 10 issues 1 1 1 3Accenture CIO Survey 1 1KPMG & Harvey Nash 1 1 1 1 1 1 6NASCIO Survey 1 1 1 1 1 1 1 7Robert Half Technology 1 1 1 1 1 1 6

3 6 9 7 8 8 7 48

2005 2006 2007 2008 2009 2010 2011 0.000

0.200

0.400

0.600

0.800

IT/Infor

mation S

ecurity

/Privacy

Virtualiz

ation

Data ce

nter/IT

effici

encie

s/Clou

d

Social M

edia

Impro

ving p

eople

/leade

rship

BI/ana

lytics

Standa

rdizat

ion/co

nsolida

tion

IT workfor

ce de

velop

ment

IT gover

nance

Risk m

anag

emen

t

Mobile

applic

ations/

techn

ologie

s

Inform

ation S

harin

g

Imple

menting

plans/

initativ

es/ach

ieving

resul

ts

Acquisit

ion/pr

oject m

gt

Process

/syste

m integ

ration

Strateg

ic plan

ning


Top Five CIO Concerns 2005-2011

130


131

CIOs aren't ...• The ultimate authority

on organizational informational assets

• Able to devote the required time/attention to the management of organizational informational assets

• Possessed of the requisite expertise to manage organizational informational assets

• Situated to achieve success organizationally as long as they have a technology development perspective









132

projectcartoon.comCopyright 2013 by Data Blueprint

• Original business concept• As the consultant described it• As the customer explained it• How the project leader

understood it• How the programmer wrote it• What the beta testers received• What operations installed• As accredited for operation• When it was delivered• How the project was documented• How the help desk supported it• How the customer was billed• After patches were applied• What the customer wanted

Traditional Systems Life Cycle Challenges

133

SystemRequirements

SoftwareRequirements

PreliminaryDesign

DetailedDesign

Coding &De-Bugging

Integration& Testing

Operations &Maintenance

"Waterfall" model

134Copyright 2013 by Data Blueprint

46


Correctimplementations

Correctfunctionality

Correct designs

Correct specifications

Implementations based on

erroneous design

Implementations based on

erroneous specs

Incorrect implementations

Uncorrectableerrors

Hiddenerrors

Correctable functionality

(Adapted from [Mizuno 1983] as reproduced by Davis 1990.)

Design

Implementation

Requirements

Testing

imperfect program products

Cumulative Effect of Errors in Systems

Development

Erroneous designs

Erroneous specifications

the "real" problem

Designs based on erroneous specs

135


Relative Cost/Effort to Repair System in Relation to Development Stage

(Adapted from [Davis 1990.)

$0.00

$2.00

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00

$18.00

$20.00

Coding UnitTest

AcceptanceTest

Maintenance

Nearly 50% of problems are detected only after

completion of acceptance tests

Requirements

Design

136


Evolving Data is Different than Creating New Systems

137

Common Organizational Data (and corresponding data needs requirements)

New Organizational Capabilities

Systems Development

Activities

Create

Evolve

Future State

(Version +1)

Data evolution is separate from, external to, and precedes system development life cycle activities!

Results

Increasing scope and depth of information architecture utility

Individual SDLC Effort


Individual SDLC efforts make increasing use of IA

• Over time the:– Number of requests increase– Utility of the results increase– Amount of metadata contributed by

new systems development increases

138

Requirements

Design

Implement

Requests

Results


Requirements

Design

Implement

Requests

Results


Requirements

Design

Implement

Requests

Organized system metadata




Data is not a Project• Durable asset

– An asset that has a usable life more than one year

• Reasonable project deliverables – 90 day increments– Data evolution is measured in years

• Data– Evolves - it is not created– Significantly more stable

• Readymade data architectural components– Prerequisite to agile development

• Only alternative is to create additional data siloes!

139









140

The Top Job• Finance• Operations• Sale/Marketing• HR• Risk• Technology/CIO

– Align IT initiatives with business goals– Improving IT operations performance– Cultivating the IT/business partnership– Cost control/expense management– Implementing new systems– Leading change efforts– Driving business innovation– Redesigning business processes– Developing and refining business strategy– Negotiating with IT vendors– Managing IT crises– Developing market strategies & technologies– Security management– Studying trends to identify opportunities


Where does data go?

141... data

Information


Reporting Particulars1. Report outside of IT

and the current CIO altogether;

2. Report to the same organizational structure that the CFO and other "top" jobs report into; and

3. Focus on activities that are outside of (and more importantly) upstream from any system development lifecycle activities (SDLC).

142

Top Operations

Job


CDO Reporting

143

Top Job

Top Finance Job

Top InformationTechnology

Job

Top Marketing

Job

• There is enough work to justify the function• There is not much talent• The CDO provides significant input to the Top Information Technology Job

Data Governance Organization

ChiefData

Officer


Comments from CIOs• I think the need for a newly defined executive level role of

data/information ownership is clear, and is distinct from the role of leading the IT function. However, if you propose changing the CIO’s title to something that is much more appropriate for the vast majority of CIO’s, like CTO, and reusing the CIO title for the new function you will meet with a firestorm of dissent. That dissent will not be in opposition to your core suggestion that each organization needs to establish this new function in the business. That need can be clearly articulated and proven. The dissent will be around moving today’s CIO in that direction, or, worse, stripping them of that “honorable” title. That will be a debate full of sound and fury but signifying nothing, other than distracting everyone from the core argument at hand - - the need for the creation of that role in the organization.

144


Reporting Particulars1. Report outside of IT and

the current CIO altogether;2. Report to the same

organizational structure that the CFO and other "top" jobs report into; and

3. Focus on activities that are outside of (and more importantly) upstream from any system development lifecycle activities (SDLC).

145


1. IT does not feel the true impact of poor DM practices– Data problems can and often do delay IT projects and this causes

the organization to pay more for IT services than it should. However the impact to the business of unmanaged/unmanageable data is greater than on IT. The business is more likely to suffer publicly from data problems while the impact of IT-related data failures is less likely to become know outside of the organization.

2. IT does not that they do not know organizational business rules that govern data and its use. – IT's focus on technical knowledge leaves little resources and few cycles to devote to

understanding how data is used by the business for various decisions.

3. IT does not own or control access to the subject matter expertise ultimately needed to implement business driven data centric data development practices. – Again, the focus on technical implementation details, keeps IT fully occupied with "how" concerns.

There is very little time for understanding business oriented, "what" problems.

4. Only the business can competently assign values on various data uses. – Defining what “good enough” for data management practices cannot be done from an IT perspective.

5. Reporting to IT has been expected because IT owned the method. – Since IT specializes in methods, IT was assumed to be the function to also manage the data. Most

non-IT folks have no idea that methods can be used to develop flexible, adaptable, and reusable data.

6. CIOs are already slammed. – Since CIOs are generally unsuccessful at remaining data-focused it is best to create a position solely

dedicated to just that function.

146

Arguments for not reporting to IT

1. Appropriate division of labor. • Since IT has its hand full with the how's of the

systems, it is appropriate that the business take ownership of defining the organizational "what."

2. Reduction in organizational system requirements translations. • The current organizational cycle begins with the

business defining system requirements to IT who codifies these and relates them back to the business for verification.

3. Encourages business to learn appropriate IT-derived methods. • Maintaining the requirements (the "whats") in the business will reduce

translations and encourage broadly based, information systems-oriented thinking.

4. Better encourages data and architectural component reuse. • The longer-term focus of data is – at odds with IT development cycle –

DM is a program not a project.


Arguments for reporting to the business

147


148

New division of labor• Reporting to IT

– Data Development– Database Operations

Management• Shared with the

business– Metadata

Management– Data Security

Management• Reporting to

Business– Data Architecture

Management– Reference & Master

Data Management– Data Warehousing &

BI Management– Document & Content

Management– Data Quality

Management– Data Governance


Separating the Wheat from the Chaff

149


Separating the Wheat from the Chaff• Harvard Business School wisdom

– 20% of your customers cause 80% of your problems– Eliminating those 20% (the problem customers) should

increase profitability without any additional cost– The key question is how to identify the correct 20%– Very few try this strategy

• Poor data management practices are costing organizations much money/time/effort

• Data that is better organized increases in value• Pareto analysis dictates that 80% of organizational data is ROT

– Redundant– Obsolete– Trivial

• The question is the same - which data to eliminate?

150


What to do first?1. Providing effective and efficient

data management to the organization. • Understanding the current and future data needs of

an enterprise and making that data effective and efficient in supporting business activities.

2. Separating the data into ROT and non-ROT. • 80% of organizational data is ROT: Redundant;

Obsolete; or Trivial. Moving to reduce organizational data ROT significantly reduces the complexity of the organizational data management challenge.

3. Remaining data focused. • The TDJ maintains a sole focus on understanding, marshaling, and applying

organizational data resources in support of business strategies. Laser like focus on data will help the organization to understand how data fuels various organizational processes and permits meaningful l enhancements to organizational data inventory. Any time the TDJ is paying attention to anything other than data support for strategy, they are diluting their own effectiveness.

4. Individuals possessing experience in this area will commend a premium as their specialized knowledge skills, and abilities will be in demand and experienced individuals will be in short supply

151


CDO Survey: What key qualifications are necessary to be a successful CDO?

152

88.5% 83.2%

66.4% 62.8% 61.1% 59.3% 59.3%

55.8% 51.3%

46.0% 44.3% 41.6%

38.9%

29.2%

0.0%$

50.0%$

100.0%$

Experience in operationalizing

Data Governance,

Data Stewardship and

Data Quality

Strong leadership and C-suite/board

communication skills

Expertise in creating and

deploying best practices and

methodologies

Experience in defining business

requirements for information

management projects

Extensive industry

knowledge, including

expertise at the intersection of risk and other

domains

Experience in leading major information

management programs in key business areas related to the

industry

Information management program life

cycle experience

Familiarity with Enterprise Metadata

Management (business and IT) and OMG

standards

Expertise in creating and

leading best of class business

and IT teams for information

management

Familiarity with process

modeling, semantic

modeling and data modeling

Familiarity in setting up and

supporting information

analytics teams

Familiarity with industry data

models

Expertise in business and IT

architecture, including

familiarity with leading

architectural standards such as TOGAF, FEA and/or Zachman

End-to-end data warehousing

program execution

knowledge and leadership

93.8% 85.8% 82.3% 82.3%

74.3% 72.6% 66.4%

54.9%

45.1% 38.9%

29.2%

0.0%$

50.0%$

100.0%$

Possess a balance of

technical skills, business

knowledge and people skills

Outstanding relationship building and


Politically savvy

Leader and visionary

Team builder Understands privacy, data security, and

risk management

components of data

Understand core

information domains of

risk, industry knowledge,

product/service and customer

Can work with pure IT and information

management specialists to

bridge the information gap

SME in requisite

business side as well as

methodologies and practices

needed to effectively connect business

requirements to IT

Not too technical but

not a technical novice

Entrepreneurial

93.8% 85.8% 82.3% 82.3%

74.3% 72.6% 66.4%

54.9%

45.1% 38.9%

29.2%

0.0%$

50.0%$

100.0%$






Politically savvy



risk management

components of data

Understand core







SME in requisite




requirements to IT



Entrepreneurial


CDO Survey: What key traits are necessary to be a successful CDO?

153

93.8% 85.8% 82.3% 82.3%

74.3% 72.6% 66.4%

54.9%

45.1% 38.9%

29.2%

0.0%$

50.0%$

100.0%$






Politically savvy



risk management

components of data

Understand core







SME in requisite




requirements to IT



Entrepreneurial


73% of CDO Functions Are Less that 1 Year Old

• Does your CDO have a budget?

154

• Does your CDO have a staff?


Chief Electrification Officer

155

• Chief Electrification Officer – responsible for electrical generating and distribution systems. The title was used mainly in developed countries from the 1880s to 1940s during the electrification of industry, but is still used in some developing countries.

Not all roles are needed always!


Propositions• A rather serious gap exists

in most organizations• The TDJ should be a

business function• Any time the TDJ is paying attention

to anything other than data supportfor strategy, they are diluting their own effectiveness

• The TDJ is be a business leader who is the CTO's primary customer; requiring new, not-widely available KSAs

• New titles are required for most existing CIOs • Most current CIOs should have their job titles changed to CTOs• The vast majority of organizations lack qualified personnel and/

or organizational focus on improving the process by which organizational strategy is informed by organizational data resources.

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CDO Success1. Dedicated solely to data asset

leveraging

2. Unconstrained by an IT project mindset

3. Reporting to the business

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10124 W. Broad Street, Suite CGlen Allen, Virginia 23060804.521.4056

peter aiken and michael gorman the case for the chief data ... · pdf...

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