DataEd Online: Show Me the Money - The Business Value of Data and ROI

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Welcome!

Date: December 11, 2012Time: 2:00 PM ETPresenter: Dr. Peter Aiken

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Monetizing Data Management: Business Value of Data and ROI

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Get Social With Us!

Live Twitter FeedJoin the conversation!

Follow us: @datablueprint

@paikenAsk questions and submit your comments: #dataed

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Business IntelligenceAsk questions, gain insights and collaborate with fellow

data management professionals

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Meet Your Presenter: Dr. Peter Aiken

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• Internationally recognized thought-leader in the data management field with more than 30 years of experience

• Recipient of the 2010 International Stevens Award

• Founding Director of Data Blueprint (http://datablueprint.com)

• Associate Professor of Information Systems at Virginia Commonwealth University (http://vcu.edu)

• President of DAMA International (http://dama.org)• DoD Computer Scientist, Reverse Engineering Program Manager/

Office of the Chief Information Officer • Visiting Scientist, Software Engineering Institute/Carnegie Mellon

University• 7 books and dozens of articles• Experienced w/ 500+ data management practices in 20 countries

DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION

Monetizing Data Management:

Business Value of Data and ROI

Professional Development: Business Value of Data and ROI

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Outline1. Data Management Overview2. Root Cause Analysis3. Ineffective Data Management

Investments4. Success Stories & Monetization

Examples5. Guiding Principles6. Take Aways and Q&A

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Tweeting now: #dataed

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The DAMA Guide to the Data Management Body of Knowledge

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Data Management

Functions

Published by DAMA International• The professional

association for Data Managers (40 chapters worldwide)

DMBoK organized around • Primary data

management functions focused around data delivery to the organization

• Organized around several environmental elements

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The DAMA Guide to the Data Management Body of Knowledge

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Environmental Elements

Amazon:http://www.amazon.com/DAMA-Guide-Management-Knowledge-DAMA-DMBOK/dp/0977140083Or enter the terms "dama dm bok" at the Amazon search engine

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What is the CDMP?• Certified Data Management

Professional• DAMA International and ICCP• Membership in a distinct group made

up of your fellow professionals• Recognition for your specialized

knowledge in a choice of 17 specialty areas

• Series of 3 exams• For more information, please visit:

– http://www.dama.org/i4a/pages/index.cfm?pageid=3399

– http://iccp.org/certification/designations/cdmp

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Data Management

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Data Management

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Manage data coherently.

Share data across boundaries.

Assign responsibilities for data.Engineer data delivery systems.

Maintain data availability.

Data Program Coordination

Organizational Data Integration

Data Stewardship Data Development

Data Support Operations

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Outline1. Data Management Overview2. Ineffective Data Management

Investments3. Root Cause Analysis4. Success Stories & Monetization


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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

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– 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”

IT Project Failure Rates

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Recent IT project failure rates statistics can be summarized as follows:

– 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"

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http://www.it-cortex.com/stat_failure_rate.htm; (accessed 9/14/02); New York Times 1/22/05

More IT Project Failure Rates

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Click to edit Master text styles

IT Project Failure Rates (moving average)

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

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% of DM Organizations labeled “successful”

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0

0.45

Successful Partial Success Don't know/too soon to tell Unsuccessful Does not exist1981 2007

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DM Origins – Which arrives first: DM or DBMS?

• A key indicator of organizational awareness• 75% reacting instead of anticipating • Best practices are obvious

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Data Management Involvement

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Expanding DM Scope

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

$0 $125,000 $250,000 $375,000 $500,000

Median Project Expense

Median Project Cost

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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

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Organizations Surveyed

Local Government4%

State Government Agencies17%

Federal Government11%

Public Companies 58%

International Organizations10%

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Polling Question #1 What percentage of Data Management investments achieve tangible returns?

a. 30%b. 10%c. 65%

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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.

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Largely Ineffective EIM Investments

Investment <= Return10%

Investment > Return20%

Return ≈ 070%

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Root Cause Analysis• Symptom of the

problem– The weed– Above the surface – Obvious

• The underlying Cause– The root– Below the surface – Not obvious

• Poor Information Management Practices

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Asking "why" repeatedly!

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Ishikawa Fishbone Diagrams• 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

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Toyota versus Detroit Engine MountingDetroit• 3 different bolts• 3 different

wrenches• 3 different bolt

inventories

Toyota• Same bolts used

for all three assemblies

• 1 bolt inventory• 1 type of wrench

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Academic Research Findings0% 12.500% 25.000% 37.500% 50.000%

49.00%

39.00%

21.00%

20.00%

20.00%

20.00%

19.00%

18.00%

18.00%

17.00%

Retail

Consulting

Air Transportation

Food Products

Construction

Steel

Automobile

Publishing

Industrial Instruments

Telecommunications

A 10% improvement in data usability on

productivity (increased sales per

employee by 14.4% or $55,900)

Measuring the Business Impacts of Effective Data by Anitesh Barua,, Deepa Mani,, Rajiv Mukherjee

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Projected impact of a 10% improvement in data quality and

sales mobility on Return on Equity


Academic Research Findings

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Projected Impact of a 10% increase in intelligence and accessibility of

data on Return on Assets


Academic Research Findings

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Monitization: Time & Leave Tracking

At Least 300 employees are spending 15 minutes/week

tracking leave/time

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Capture Cost of Labor/Category

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Computer Labor as OverheadRoutine Data EntryRoutine Data EntryRoutine Data Entry

District-L (as an example) Leave Tracking Time AccountingEmployees 73 50Number of documents 1000 2040Timesheet/employee 13.70 40.8Time spent 0.08 0.25Hourly Cost $6.92 $6.92Additive Rate $11.23 $11.23Semi-monthly cost per timekeeper

$12.31 $114.56

Total semi-monthly timekeeper cost

$898.49 $5,727.89

Annual cost $21,563.83 $137,469.40

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• Range $192,000 - $159,000/month

• $100,000 Salem

• $159,000 Lynchburg

• $100,000 Richmond

• $100,000 Suffolk

• $150,000 Fredericksburg

• $100,000 Staunton

• $100,000 NOVA

• $800,000/month or $9,600,000/annually

• Awareness of the cost of things considered overhead

Annual Organizational Totals

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ERP Implementation Success

• Most ERP implementations today result in cost and schedule overruns; courtesy of the Standish Group

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On time, within budget, as planned 10%

Cancelled 35%

Overrun 55%

100% 100%41%

178%230%

59%

0%

50%

100%

150%

200%

250%

300%

350%

Cost Schedule PlannedFunctionality

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Platform: UniSysOS: OS1998 Age: 21 Data Structure: DMS (Network)Physical Records: 4,950,000Logical Records: 250,000Relationships: 62Entities: 57Attributes: 1478

New System

Legacy System #1: Payroll

Legacy System #2: Personnel

Platform: AmdahlOS: MVS1998 Age: 15 Data Structure: VSAM/virtual database tablesPhysical Records: 780,000Logical Records: 60,000Relationships: 64Entities: 4/350Attributes: 683

Characteristics Logical PhysicalPlatform: WinTel Records: 250,000 600,000OS: Win'95 Relationships: 1,034 1,0201998 Age: new Entities: 1,600 2,706Data Structure: Client/Sever RDBMS Attributes: 15,000 7,073

Predicting Engineering Problem Characteristics

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"Extreme" Data Engineering• 2 person months = 40 person days• 2,000 attributes mapped onto 15,000• 2,000/40 person days = 50 attributes

per person dayor 50 attributes/8 hour = 6.25 attributes/hour

and• 15,000/40 person days = 375 attributes

per person dayor 375 attributes/8 hours = 46.875 attributes/hour

• Locate, identify, understand, map, transform, document, QA at a rate of -

• 52 attributes every 60 minutes or .86 attributes/minute!

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Reverse Engineering PeopleSoft

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InstalledPeopleSoftSystem

• Queries toPeopleSoft Internals

• PeopleSoft external RDBM Tables

• Printed PeopleSoft Datamodel

Metadata Uses

• System Structure Metadata - requirements verification and system change analysis

• Data Metadata - data conversion, data security, and user training

• Workflow Metadata - business practice analysis and realignment

implementationrepresentation

Componentmetadata integration

data metadata

system structure metadata

workflow metadata

post derivationmetadata

analysisand

integration

TheMAT

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Home Page

Business Process Name

Business Process Component

Business Process Component Step

PeopleSoft Process Metadata

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Home Page Name

(relates to one or more)

Business Process Name


Business Process Component Name


Business Process Component Step Name

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Example Query Outputs

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Resolution

Quantity System Component

Time to make change

Labor Hours

1,400 Panels 15 minutes 3501,500 Tables 15 minutes 375984 Business

process component steps

15 minutes 246

Total 971

X $200/hour $194,200

X 5 upgrades $1,000,000

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Improving Data Quality during System Migration

• Challenge– Millions of NSN/SKUs

maintained in a catalog– Key and other data stored in

clear text/comment fields– Original suggestion was

manual approach to text extraction– Left the data structuring problem unsolved

• Solution– Proprietary, improvable text extraction process– Converted non-tabular data into tabular data– Saved a minimum of $5 million– Literally person centuries of work

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Determining Diminishing Returns

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Unmatched Items

Ignorable Items

Items Matched

Week # (% Total) (% Total) (% Total)1 31.47% 1.34% N/A2 21.22% 6.97% N/A3 20.66% 7.49% N/A4 32.48% 11.99% 55.53%… … … …14 9.02% 22.62% 68.36%15 9.06% 22.62% 68.33%16 9.53% 22.62% 67.85%17 9.50% 22.62% 67.88%18 7.46% 22.62% 69.92%

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Time needed to review all NSNs once over the life of the project:Time needed to review all NSNs once over the life of the project:NSNs 2,000,000Average time to review & cleanse (in minutes) 5Total Time (in minutes) 10,000,000

Time available per resource over a one year period of time:Time available per resource over a one year period of time:Work weeks in a year 48Work days in a week 5Work hours in a day 7.5Work minutes in a day 450Total Work minutes/year 108,000

Person years required to cleanse each NSN once prior to migration:Person years required to cleanse each NSN once prior to migration:Minutes needed 10,000,000Minutes available person/year 108,000Total Person-Years 92.6

Resource Cost to cleanse NSN's prior to migration:Resource Cost to cleanse NSN's prior to migration:Avg Salary for SME year (not including overhead) $60,000.00Projected Years Required to Cleanse/Total DLA Person Year Saved

93Total Cost to Cleanse/Total DLA Savings to Cleanse NSN's: $5.5 million

Quantitative Benefits

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Seven Sisters from British Telecom

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Thanks to Dave Evans

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Friendly Fire deaths traced to

Dead Battery

Date: Tue, 26 Mar 2002 10:47:52 -0500From: Jamie McCarthy <[email protected]>Subject: Friendly Fire deaths traced to dead battery

In one of the more horrifying incidents I've read about, U.S. soldiers andallies were killed in December 2001 because of a stunningly poor design of aGPS receiver, plus "human error."

http://www.washingtonpost.com/wp-dyn/articles/A8853-2002Mar23.html

A U.S. Special Forces air controller was calling in GPS positioning fromsome sort of battery-powered device. He "had used the GPS receiver tocalculate the latitude and longitude of the Taliban position in minutes andseconds for an airstrike by a Navy F/A-18."

According to the *Post* story, the bomber crew "required" a "secondcalculation in 'degree decimals'" -- why the crew did not have equipment toperform the minutes-seconds conversion themselves is not explained.

The air controller had recorded the correct value in the GPS receiver whenthe battery died. Upon replacing the battery, he called in thedegree-decimal position the unit was showing -- without realizing that theunit is set up to reset to its *own* position when the battery is replaced.

The 2,000-pound bomb landed on his position, killing three Special Forcessoldiers and injuring 20 others.

If the information in this story is accurate, the RISKS involve replacingmemory settings with an apparently-valid default value instead of blinking 0or some other obviously-wrong display; not having a backup battery to holdvalues in memory during battery replacement; not equipping users totranslate one coordinate system to another (reminiscent of the Mars ClimateOrbiter slamming into the planet when ground crews confused English withmetric); and using a device with such flaws in a combat situation

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Messy Sequencing Towards Arbitration

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Plaintiff(Company X)

Defendant(Company Y)

April Requests a recommendation from ERP Vendor

Responds indicating "Preferred Specialist" status

July Contracts Defendant to implement ERP and convert legacy data

Begins implementation

January Realizes a key milestone has been missed

Stammers an explanation of "bad" data

July Slows then stops Defendant invoice payments

Removes project team

Files arbitration request as governed by contract with Defendant

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Expert ReportsOurs provided evidence that :1. Company Y's conversion code introduced

errors into the data2. Some data that Company Y converted was of

measurably lower quality than the quality of the data before the conversion

3. Company Y caused harm by not performing an analysis of the Company X's legacy systems and that that the required analysis was not a part of any project plan used by Company Y

4. Company Y caused harm by withholding specific information relating to the perception of the on-site consultants' views on potential project success

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Expert Report

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The defendant knew to prevent duplicate SSNs

!************************************************************************! Procedure Name: 230-Assign-PS-Emplid!! Description : This procedure generates a PeopleSoft Employee ID! (Emplid) by incrementing the last Emplid processed by 1! First it checks if the applicant/employee exists on! the PeopleSoft database using the SSN.!!************************************************************************Begin-Procedure 230-Assign-PS-Emplid

move 'N' to $found_in_PS !DAR 01/14/04 move 'N' to $found_on_XXX !DAR 01/14/04

BEGIN-SELECT -Db'DSN=HR83PRD;UID=PS_DEV;PWD=psdevelopment'NID.EMPLIDNID.NATIONAL_ID

move 'Y' to $found_in_PS !DAR 01/14/04 move &NID.EMPLID to $ps_emplid

FROM PS_PERS_NID NID!WHERE NID.NATIONAL_ID = $ps_ssnWHERE NID.AJ_APPL_ID = $applicant_idEND-SELECT

if $found_in_PS = 'N' !DAR 01/14/04 do 231-Check-XXX-for-Empl !DAR 01/14/04 if $found_on_XXX = 'N' !DAR 01/14/04 add 1 to #last_emplid let $last_emplid = to_char(#last_emplid) let $last_emplid = lpad($last_emplid,6,'0') let $ps_emplid = 'AJ' || $last_emplid end-if end-if !DAR 01/14/04

End-Procedure 230-Assign-PS-Emplid

AJHR0213_CAN_UPDATE.SQR

The exclamation point prevents this line from

looking for duplicates, so no check is made for a duplicate SSN/National

ID

Legacy systems business rules allowed employees to

have more than one AJ_APPL_ID.

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Risk Response “Risk response development involves defining enhancement steps

for opportunities and threats.” Page 119, Duncan, W., A Guide to the Project Management Body of Knowledge, PMI, 1996

"The go-live date may need to be extended due to certain critical path deliverables not being met. This extension will require additional tasks and resources. The decision of whether or not to extend the go-live date should be made by Monday, November 3, 20XX so that resources can be allocated to the additional tasks."

Tasks HoursNew Year Conversion 120Tax and payroll balance conversion 120General Ledger conversion 80

Total 320

Resource HoursG/L Consultant 40Project Manager 40Recievables Consultant 40HRMS Technical Consultant 40Technical Lead Consultant 40HRMS Consultant 40Financials Technical Consultant 40

Total 280

Delay Weekly Resources Weeks Tasks CumulativeJanuary (5 weeks) 280 5 320 1720February (4 weeks) 280 4 1120

Total 2840

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The Defense's "Industry Standards"• Question:

– What are the industry standards that you are referring to?• Answer:

– There is nothing written or codified, but it is the standards which are recognized by the consulting firms in our (industry).

• Question:– I understand from what you told me just a moment ago that the

industry standards that you are referring to here are not written down anywhere; is that correct?

• Answer:– That is my understanding.

• Question:– Have you made an effort to locate these industry standards and

have simply not been able to do so?• Answer:

– I would not know where to begin to look.

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Published Industry Standards GuidanceExamples from the:• IEEE (365,000 members)

– Institute of Electrical and Electronic Engineers– 150 countries, 40 percent outside the United States– 128 transactions, journals and magazines– 300 conferences

• ACM (80,000+ members)– Association of Computing Machinery– 100 conferences annually

• ICCP (50,000+ members)– Institute for Certification of Computing Professionals

• DAMA International (3,500+ members)– Data Management Association– Largest Data/Metadata conference

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ACM Code of Ethics and Professional Conduct

1. General Moral Imperatives.1.2 Avoid harm to others • Well-intended actions, including those that accomplish assigned

duties, may lead to harm unexpectedly. In such an event the responsible person or persons are obligated to undo or mitigate the negative consequences as much as possible. One way to avoid unintentional harms is to carefully consider potential impacts on all those affected by decisions made during design and implementation.

• To minimize the possibility of indirectly harming others, computing professionals must minimize malfunctions by following generally accepted standards for system design and testing. Furthermore, it is often necessary to assess the social consequences of systems to project the likelihood of any serious harm to others. If system features are misrepresented to users, coworkers, or supervisors, the individual computing professional is responsible for any resulting injury.

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Outcome

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Jan 4, 2011

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Polling Question #2 Which is not a reason why data scientist add business value?

a. Act as a data-to-business translatorb. They work side-by-side with the IT departmentc. Conduct problem solving using a data-driven

approach

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3 Ways Data Scientists Add Business Value1. Refine target audiences. The more information that companies gather and

analyze about their customers, the more they learn about their behaviors, needs, and preferences. This information also provides greater knowledge about the lifecycle stage that a particular set of customers is at (e.g. dual-income with children nearing college age). This type of information can help companies identify the most likely customers for certain products and services. Data analysts are masters at distilling this type of information.

2. Conduct problem solving using a quantifiable, data-driven approach. For years, executives have made million-dollar decisions based on gut instinct. But that’s no longer necessary with the volume of data that’s available from so many channels and market sources for decision makers to pore over. Not only can data analysts help senior leaders make the right decisions based on facts, they can also provide impartial, data-led guidance for critical decisions when the top brass are deadlocked on the right path to take.

3. Acting as a data-to-business translator. Many companies struggle with communicating and interpreting the results from analytics efforts. Data analysts can fill a critical role here by helping senior executives make sense of the data that’s being presented to them as well as by helping them understand how the information can be applied to various areas of the business.

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Data Management: Why is it Important to Your Organization?

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• Why is it important?– Concretizing

• State Agency Time & Leave Tracking– $10 million USD annually

• ERP Implementation$1 million USD on a large project

• Data Warehouse Quality Analysis$5 billion USD US DoD (prevention)

• MDM British Telecom rollout– £ 250 (small investment)

• Non-Monetized Example– Different measures

• ERP Implementation Legal Case$ 5,355,450 CAN damages/penalties

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Questions?

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

your questions to Peter now.

+ =

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Upcoming Events

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January Webinar: Unlocking Business Value through Data Modeling and Data Architecture (Part I of II)2013 @ 2:00 PM – 3:30 PM ET(11:00 AM-12:30 PM PT)

February: Unlocking Business Value through Data Modeling and Data Architecture (Part II of II) 2013 @ 2:00 PM – 3:30 PM ET(11:00 AM-12:30 PM PT)

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

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Transcript of DataEd Online: Show Me the Money - The Business Value of Data and ROI