Contemporary Issues in PM Maturity

8/10/2019 Contemporary Issues in PM Maturity

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Contemporary issues inproject management maturity

W

ebinar delivered for:Project Management InstituteOrganizational Project Management CoP

Dr. Beverly Pasian ([email protected])Utrecht University of Applied Sciences

Dr. Nigel L. Williams ([email protected])Bournemouth University

24 June 2014


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Research Centre forInnovations in Health Care

www.kenniscentrumivz.hu.nl

Outline for today...

1. Background of research: 4 main problems

2. Description of research design

3. Research findings4. Conclusions

5. Implications & outputs


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A little about me

Education (Toronto, OpenU, UTS)

Canadian & Irish (but

rooting for Netherlands!)

Current roles (AssociateProfessor @ HU)

Service (IPMA, WorldCongress, animal shelter)

Publications and Research


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Certain basic problems with currentconcept and modularization

of PM maturity


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Historical context of maturity

Came out of post-WW2 environment(Shewhart to Deming)

Emphasis and appeal: to manufacturers

serving a civilian community

Management focus:

high quality based on efficiency


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Process control was the key drive

(principle of SPC)

Achieve goals by minimizing variation

Focus of manufacturers was to achieve quality

bydefining, repeating and predicting processes


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Is this a good thing?

The process has an identity: its performance ispredictable, measurable, and open to communication.

Costs can be predictable.

Regularity of output is achievable. Productivity can be maximized.

Relationships can be greatly simplified (especially withvendors).

The effects of changes within the systemcan bemeasured with greater speed and reliability


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In PM research

Time management (Hameri & Heikkila, 2002) Fuzzy Front End (Nobelius and Trygg, 2002) Buffer Management (Goldratt, 1986). Cost

Kwak et al.(2008) explore the role that a cost estimatingframework can play

Mavrotes et al. (2005) explore cash flow forecasting tomanage funds in information and communicationstechnology (ICT) projects

Sanchez and Perez (2004) further examine EWS as a wayto hypothesize or predict variation


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The project management communityadopted process control

as a sign of maturity

Problem #1.


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Defining project management maturity...

Much debate and interpretation


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Different views

Technical meanings the extent to which an organizational project

management capability has explicitly and consistentlydeployed processes that are documented, measured,controlled and continually improved(Cooke-Davies2004).

Maturity in project management is the development ofsystems and processes that are repetitive in nature andprovide a high probability that each project will be a

success.(Kerzner 2004)


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Organizational View company receptivity to project management (Saures

1998) Project management maturity is the sophistication

level of an organizations current project managementpractices and processes. (Ibbs, Reginato & Kwak 2004)

Broader / abstract view

as the sum of action, attitude and knowledge in the real world, we will not find the fully maturedorganization (Andersen & Jensen 2003)


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Conceptual view varies acrosspractitioners and researchers

(How do you assess maturity without clear definition?)

Problem #2.


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The initial attempt to modularize and

measure maturity came from

Philip Crosbys

Qual ity Management Matur i ty Grid (1979)

Qual i ty is Free


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An new era for the PM community

Managing the software process (1989)Watts S. Humphrey

The Capability Maturity Model (SEI/CMM)

***Help US DoD assess contractorsprocesses

in performing software projects.***


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OptimizingContinuous process improvement is enabled by quantitative

feedback from the process and from piloting innovative ideas andtechnologies.

ManagedDetailed measures of the processes and product quality are

collected. Both the process and products are quantitatively

understood and controlled.

DefinedProcesses are documented, standardized, and integrated into a

standard process for the organization. All projects use anapproved, tailored, version of the organizations standard processfor developing and maintaining software.

Repeatable

Basic project management processes are established to track

cost, schedule, and functionality. The necessary process disciplineis in place to repeat earlier successes on projects with similarapplications.

InitialThe process is characterized as ad hoc, and occasionally even

chaotic. Few processes are defined, and success depends onindividual effort.

A tool for measuring maturity: as

processes become...

Incre

asingMatu

rity


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Process Capability

Process under statistical control has a definablecapability,

Implies repeatability, predictability

Associated advantages: these processes would beefficient and more effective

Implies that a controlled process is being (or can be)managed and measured.

Individual processes or groups of processes can beconsidered mature if they meet certain thresholds


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Problem #3.

Project management maturity models

reflect a limited history... emphasizing

highly defined process control.


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PM models: the first generation

Construction Project Management Maturity Model

Project Management Process Maturity Model

Evolutionary Software Project Management Maturity Model

Strategic Project Management Maturity Model

OPM3

Prince 2 Maturity Model

Portfolio, Programme and Project Management Maturity Model

The Project Management Maturity Model (ProMMM)


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How do they measure maturity?

Construction Project Management Maturity Model 5 levels: Initial, Repeatable, Completely organized,Quantitatively managed, Optimizing

Project management Process Maturity (PM)2

Model

5 levels: Ad-hoc, Initial Project Planning, Systematic

Project Planning & Control, Integrated Multi-Project

Planning and Control, Continuous improvement


5 levels: Common language, Common Processes,

Singular Methodology, Benchmarking, Continuous

Improvement

OPM3

Multidimensional: project, program, and portfolio

upwards along the levels of standardization,

measurement, control and continuous improvement

P3M35 levels: Awareness, Repeatable, Defined, Managed,

Optimised

Prince 2 3 levels: Initial, Repeatable, Defined

Project Management Maturity Model

5 step ladder: Initial, Structured Process and

Standards, Organizational Standards and

Institutionalized Process, Managed Process,

Optimizing Process

ProMMM 4 levels: Nave, Novice, Normalised, Natural


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But what are they measuring?

Management

Organization

Process management

Process, Tool development

Awareness

Business Case & Benefits

Project specifications

Formality

PM Office

Risks and Management

Training

Communications

Quality management

Data management

Continuous improvement

PM process analysis


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Other models...

Data Warehousing Maturity Model

Design Safety Capability Maturity Model

Developmental Maturity Model

e-Learning Maturity Model

Knowledge Management Maturity Model

Model-drive Development Maturity Model

Computer Education Maturity model

Evolutionary Software Project management

Maturity model

Value-based business-IT Alignment Maturity

Model

Process and Enterprise Maturity Model

Moisture-modified Maturity Model

Requirements Engineering Maturity Model

Framework

Maturity Model for Criminal Organization

Maturity model for email communications

Malcolm Baldridge National Quality Award

Capability Maturity Model

People Capability Maturity Model

Standard Testing Maturity Model

Ascospore Maturity Model

Corrective Maintenance Maturity Model

Information Systems Action-Research Maturity

Model


Leadership Maturity Model

Online Course Design Maturity model

ProscisChange Management Maturity Model

Engineering Education Capability Maturity model

Software Maintenance Maturity Model

Innovation Maturity Model


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Letscompare

Management

Organization

Process management

Process, Tool development

Awareness


Project specifications

Formality

PM Office

Risks and Management

Training

Communications

Quality management

Data management

Continuous improvement

PM process analysis

Culture

CustomerOrganizational & management policies

Leaders, champions (individual roles)

Interface with host organization

Quality

Resources


Problems, Variations, Defects

Training

Organizational , Environment

Continuous Improvement

Project characteristics

Chaotic references

Risk Management


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Problem #4.

Project management maturity

is determined by

what the model says is important.


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Problems ...

1. Not all projects have defined

processes...making process control difficult.

2. There is no universal definition of project

management maturity.

3. Project management maturity is determined

by what the model says is important.

4. Project management maturity models reflecta limited history emphasizing highly defined

projects.


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Other considerations

Project types and environments have multiplied andincreased in complexity

Is it reasonable to apply the process control metricsused in a manufacturing setting to (for example)wicked projects?

Do all industries, organizations have the sameexpectation for maturity?

Projects lacking definition may be managed using unique,unpredictable, unrepeatable processes to achieve projectgoals


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Core research question:

What non-process factors couldcontribute to a mature PM capability?

A professional doctoral study from the University of Technology, Sydney(S.Boydell and S.Sankaran, supervisors)


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A multimethod study in 3 parts...

1. Content analysis of 2 maturity model collections

leading to conceptual framework

2. Pilot case study leading to final case study

design

3. Case study at multiple universities leading to

final conceptual model and conclusions


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Considerations...

Item

Justify non-process factors

Determine project type

Find suitable organization /

environment

Demonstrate their existing

reliability

Solutions Non-PM maturity models

helped with this

Goals & Methods matrix(Turner & Cochrane, 1993)

E-Learning projects

Higher education

Candidates prior research


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References

Andersen, E.S. & Jessen, S.A. 2003, 'Project maturity in organisations',International Journal of Project Management, vol. 21, no. 6,pp. 457-61.

Cooke-Davies, T.J. 2004a, 'Measurement of organizational maturity', in D.P.Slevin, D.I. Cleland & J.K. Pinto (eds), Innovations -- Project ManagementResearch 2004, Project Management Institute, London, U.K., pp. 523-42.

Cooke-Davies, T.J. 2004b, 'Project management maturity models', in J.K. Pinto& P.W.G. Morris (eds), The Wiley Guide to Managing Projects, 1st edn, Wiley& Sons, Inc., Hoboken, N.J., pp. 1234-55.

Crosby, P.B. 1979, Quality is Free: The Art of Making Quality Certain, 1st edn,McGraw-Hill Book Company, New York City.

Goldratt, E.M. 1986, The Goal: A Process of Ongoing Improvement, 3rd edn,North River Press, New York, NY.

Hameri, A.-P. & Heikkila, J. 2002, 'Improving efficiency: time-critical interfacingof project tasks', International Journal of Project Management, vol. 20, pp. 143-53.


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References (2)

Humphrey, W.S. 1989, Managing the Software Process, Addison-Wesley

Publishing Company, Reading, MA.

Ibbs, C.W., Reginato, J.M. & Kwak, Y.H. 2004, 'Developing project

management capability: benchmarking, maturity, modeling, gap analyses, and

ROI studies', in J.K. Pinto & P.W.G. Morris (eds), The Wiley Guide to

Managing Projects, 1st edn, Wiley & Sons, Inc., Hoboken, N.J., pp. 1214-33.

Kerzner, H. 2004, Project Management Best Practices: Achieving Global

Excellence, 1st edn, John Wiley & Sons, Hoboken, N.J.

Kwak, Y.H., Watson, R.J. & Anbari, F.T. 2008, 'Comprehensive framework for

estimating the deployment cost of integrated business transformation projects',

International Journal of Managing Projects in Business, vol. 1, no. 1,pp. 131-9

Mavrotas, G., Caloghirou, Y. & Koune, J. 2005, 'A model on cash flow

forecasting and early warning for multi-project programmes: application to the

operational programme for the information society in Greece', International

Journal of Project Management, vol. 23, pp. 121-33.


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References (3)

Nobelius, D. & Trygg, L. 2002, 'Stop chasing the front-end process

management of the early phases in product development projects',

International Journal of Project Management, vol. 20, pp. 331-40.

Sanchez, A.M. & Perez, M.P. 2004, 'Early warning signals for R&D projects: an

empirical study', Project Management Journal, vol. 35, no. 1,pp. 11-24.

Saures, I. 1998, 'A real world look at achieving project management maturity',

paper presented to the Project Management Institute 29th Annual

Seminars/Symposium, Long Beach, CA, October 9-15.

Shewhart, W.A. 1931, Economic Control: Quality of Manufactured Products,

Van Nostrand Co., Inc., New York, NY.

Shewhart, W.A. & Deming, W. 1939, Statistical Method from the Viewpoint of

Quality Control, The Graduate School: The Department of Agriculture,

Washington.


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Step 1:

Content analysis of maturity modelcollections


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Construction Project Management Maturity Model5 levels: Initial, Repeatable, Completely organized,

Quantitatively managed, Optimizing

Project management Process Maturity (PM)2

Model

5 levels: Ad-hoc, Initial Project Planning, Systematic

Project Planning & Control, Integrated Multi-Project

Planning and Control, Continuous improvement


5 levels: Common language, Common Processes,

Singular Methodology, Benchmarking, Continuous

Improvement

OPM3

Multidimensional: project, program, and portfolio

upwards along the levels of standardization,

measurement, control and continuous improvement

P3M35 levels: Awareness, Repeatable, Defined, Managed,

Optimised

Prince 2 3 levels: Initial, Repeatable, Defined

Project Management Maturity Model

5 step ladder: Initial, Structured Process and

Standards, Organizational Standards and

Institutionalized Process, Managed Process,

Optimizing Process

ProMMM 4 levels: Nave, Novice, Normalised, Natural


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Data Warehousing Maturity Model

Design Safety Capability Maturity Model

Developmental Maturity Model

e-Learning Maturity Model


Model-drive Development Maturity Model

Computer Education Maturity model

Evolutionary Software Project management

Maturity model

Value-based business-IT Alignment Maturity

Model

Process and Enterprise Maturity Model

Moisture-modified Maturity Model

Requirements Engineering Maturity Model

Framework

Maturity Model for Criminal Organization

Maturity model for email communications

Malcolm Baldridge National Quality Award

Capability Maturity Model

People Capability Maturity Model

Standard Testing Maturity Model

Ascospore Maturity Model

Corrective Maintenance Maturity Model

Information Systems Action-Research Maturity

Model


Leadership Maturity Model

Online Course Design Maturity model

ProscisChange Management Maturity Model

Engineering Education Capability Maturity model

Software Maintenance Maturity Model

Innovation Maturity Model


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PM Maturity Models Results

Term Sources # of References

Management 23 42

Organization 17 28

Process management 15 23

Process, Tool development 13 22

Awareness 11 20

Business Case & Benefits 14 19

Project specifications 6 17

Formality 8 15

PM Office 5 15

Risks and Management 5 14

Training 13 14

Communications 6 11

Quality management 7 11

Data management 9 10


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Non PM Maturity Results

Item Sources # of references

Culture 17 62

Customer 11 61

Organizational & management policies 19 52

Leaders, champions (individual roles)

19

38

Interface with host organization 19 36

Specific processes 16 34

Quality 18 32

Resources 14 30

Business Case & Benefits 9 26

Problems, Variations, Defects 9 25

Training 9 25

Organizational, Environment 17 24

Continuous Improvement 13 22

Project characteristics 13 21

Chaotic references 7 20

Risk Management 7 20

Change management 10 19Project Planning 13 19


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Step 1:

Content analysis of maturity model collections

This told me that non-process factorswere in consideration outside of PM.


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Step 2:

Pilot case study with suitable project typeand host organization


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Goals & Methods matrix(Turner & Cochrane 93)

Type

Description

1Goals and methods well-defined.

Eg: Large engineering or construction projects

2

Goals well defined, methods are not.Eg Product development projects,

3Goals are not well defined, but methods are.

Eg Software-development projects

4

Neither goals nor methods are clear.

Eg organizational-development projects,


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Project types & Maturity

Type

Description

Maturity Implications

1Goals and methods

are well-defined

Possible to apply process

based approaches

2

Goals well defined,

methods are not

Cannot apply conventional

approaches as repeatableprocesses do not exist

3

Goals are not well defined,

but methods are


approaches as repeatable

processes do not exist

4

Neither goals nor methodsare well-defined.


approaches as repeatable

processes do not exist


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Agricultural Sciences

Contracting, Procurement

Construction

Design Safety

Developmental Pregnancy

Earned Value Management

Infrastructure Maturity Tool

Agile Process (SW)

Building Security

Business-IT alignment

Cloud Computing

Community Management

Computing EducationCorrective Maintenance

Criminal Organizations

Data Warehousing Process

eGovernment

e-Healthe-Learning (learning)

eMail Communication

Engineering Education

Enterprise ArchitectureGovernment Interoperability

Change management

IS - Action Research PM

Knowledge Management

Leadership

Open Source

Yes

Yes

No

No

IBM Data Governance

Information Processing

Internet

IT Architecture

Marketing operations

Networking

Online Course Design

Open Source

Service-oriented ArchitectureSoftware maintenance

Testing Process

Usability

InnovationNew product development

4(air)

2(Water)

1(Earth)

3 (Fire)


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Reliable e-Learning project management

Satisfies project outcomes as defined by the project team (Williams,2006a). Generates data that illustrate support of institutional plans (Pitts and

Siedlaczek, 2006, Jones, 2004). Produces pedagogically-sound, media-rich online courses that do

not overlap existing ones (Malinski and MacRae, 2006, Chiazzese

and Seta, 2006). Moves the institution forward by providing knowledge, processes

and skills that have been integrated into normal institutional practice(Williams, 2006b, Wallace, 2006).

Demonstrates a sustainability of management elements and an

adaptability to new initiatives (Jones, 2004). Illustrates a high level of e-readiness (Pasian and Woodill, 2006)defined as the ability of HEIs and the capacity of the institutionalstakeholders to benefit from educational technology (or e-Learning).


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Research Centre forInnovations in Health Carewww.kenniscentrumivz.hu.nl

Conceptual Framework


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Step 3:

Multiple case study at universitiesexamining their eLearning projectmanagement capability


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Summary: data collection methods


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Initial version of CF


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Academic freedom

Creativity

Culture

Expertise

Funding

Intellectual Property

Instructional Designer

Interface with organizationProblem resolution

Leadership

Release time

Teamwork

Union / Labour relations

Customer

involvement

Definedprocesses

Dynamic non-events

Adaptablevariants

eLearning PM

capability

Agendas

Skills, Perspectives, Experience

Reactions

Knowledge

Trust

Attitude

Loyalty

Acceptance

Motivation

Commitment

Momentum

Morale

PM-Initiation

PM-Planning

PM-Execution

DesignDevelopment

Delivery

Evaluation

Analysis/Closure

Inst i tut ion School Program Faculty

Student

ALPHA


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Academic freedom,

Advisory Committee

Creativity

Culture

Expertise

Interface with organization

Leadership

PedagogyIT intersection

Problem resolutionProject manager

Relationship-building

SMEs/Faculty

Resources

Teamwork

Tools

Training

Union / Labour relations

Values

Customer

involvement

Definedprocesses

Dynamic non-events

Adaptablevariants

eLearning PM

capability

Agendas


Reactions

Knowledge

Trust, Attitude, Loyalty, Acceptance, Commitment, Credibility,

Momentum, Morale, Motivation, Negotiation, Nuture

Analysis

Approvals

Change Management

Communications

Needs assessment

Planning

Design

Development

Delivery

Evaluation

Closure


Student

BETA


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Academic freedom,

Advisory CommitteeCreativity

Culture

Expertise

Funding

Intellectual property

Interface with organization

Leadership

PedagogyIT intersection

Problem resolution

Project manager

Relationship-building

SMEs/Faculty

Release time

Resources

Teamwork

Tools

TrainingUnion / Labour relations

Values

Customer

involvement

Definedprocesses

Dynamic non-events

Adaptablevariants

eLearning PM

capability

Agendas


Reactions

Knowledge

Trust, Attitude, Loyalty, Acceptance, Commitment, Credibility,

Momentum, Morale, Motivation, Negotiation, Nuture

Analysis

Approvals

Change Management

Communications

Needs assessment

Planning

Design

Development

Delivery

Evaluation

Closure


Student

COMBINED


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Original nodes Alpha variations Beta variations

Customer involvement:Agend as, Experience,

Kno wledge, Perspectives,

Reactions, Skil ls

-No variation- -No variation-

Defined processes:

Design, Development,Delivery, Evaluation,

Closure

PM-Initiation

PM-PlanningPM-Execution

PM-Closure

Analysis, Approvals, Change

management, Communications &Reporting, Needs assessment,

Planning

Dynamic non-events:Acc eptance, Att i tud e,

Commitment,

Loy alty, Motivation, Trust

Momentum , MoraleCredibility, Morale, Negotiation,

Nurture

Adaptable Variants:Academ ic freedom, Culture,

Expert ise, Interface w ith

organization,

Problem resolut ion,

Leadership,

Teamwork (various roles)

Creativity, Funding,

Intellectual property,

Instructional designer,

(Interface with organization),

(Problem resolution), Release

time, Union / Labour relations

Advisory Committee, Creativity,

PedagogyIT interaction, Project

manager, Relationship-building,

SMEs/Faculty, Resources, Tools,

Training, Union / Labour relations,

Values

Summary of Changes


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Core research question:

What non-process factors couldcontribute to a mature PM capability?


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Academic freedom

Culture

Expertise

Interface-organization

Leadership

Problem resolution

Teamwork

C u s t o m e r i n v o l v e m e n t

De

fined

proce

sses

H u m a n F a c t o r s

A

daptablevariants

eLearning

PM

capability

Agendas, Experience, Knowledge, Perspectives, Reactions, Skills

Acceptance, Attitude, Commitment, Loyalty, Motivation, Trust

AssessDesign

Develop

Implement

Evaluation,

Closure

Final version


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Managing undefined projects...

Involve the customer

Foster a culture of adaptability

Be mindful of the human factors

Provide/support defined processes where

appropriate


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Potential new research areas...

Schools of PM maturity models (using similar

content analysis approach)

More project/organization specific analysis

Different industry analysis (eg, mega

construction)

Emphasis on human factors


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Outputs & implications of this research

Special issues: JPPPM (Vol 2, #2) and IJMPB

(April14) Multiple presentations and book chapters Dutch National Research Group IPMA World Congress program (Rotterdam,

Sept 30Oct 2) Likely new journal Wonderful collaboration! Pasian & Williams


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Important web sites

www.ipma2014.com

www.dutchnationalresearchgroup.nl

www.gowerpublishing.com

(Designs, methods & practices for research of PM Dec 14)


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Thank you very muchfor your time and attention.

[email protected]+31 (0)6 34 82 77 19

Linkedin@dnrginpm

@beverlypasianFacebook


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Future Directions in Maturity

Measurement Current approaches vary in WHAT is

measured, not HOW

Developing new insights requires the

consideration of new research philosophies andmethods

Project management maturity in the age of big

dataN Williams, NP Ferdinand, R Croft

International Journal of Managing Projects in

Business 7 (2), 311-317
http://scholar.google.co.uk/citations?view_op=view_citation&hl=en&user=jKIcs6wAAAAJ&citation_for_view=jKIcs6wAAAAJ:Tyk-4Ss8FVUChttp://scholar.google.co.uk/citations?view_op=view_citation&hl=en&user=jKIcs6wAAAAJ&citation_for_view=jKIcs6wAAAAJ:Tyk-4Ss8FVUChttp://scholar.google.co.uk/citations?view_op=view_citation&hl=en&user=jKIcs6wAAAAJ&citation_for_view=jKIcs6wAAAAJ:Tyk-4Ss8FVUChttp://scholar.google.co.uk/citations?view_op=view_citation&hl=en&user=jKIcs6wAAAAJ&citation_for_view=jKIcs6wAAAAJ:Tyk-4Ss8FVUC


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From Data to Big Data

Big data, defined by three main characteristics :volume, velocity and variety(Frankel and Reid2008). Volume refers to the scale or amount of data

(Zikopoulos and Eaton 2011). Velocity refers to the rate at which data may

enter the organization (Sagiroglu and Sinanc2013).

Variety refers to the heterogeneous nature ofbig data (Chen et al. 2012).


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Current Research Paradigms

Qualitative Detailed knowledge of a given setting through

unstructured or semi structured data collectionfrom a small number of sources (Denzin and

Lincoln 2011). Quantitative Insights from analysis of associations between

observed or latent variables (Groves 2011)


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Big Data and Evaluation

Integrating a range of data linked to humaninteractions in natural settings (Dong andSrivastava 2013).

These trends can have significant effects on data

collection enabling Real time perspective as data can be collected

and analysed automatically Census approach as all interactions can be

collected Geographical expansion beyond the boundaries

of the enterprise


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Possible Approaches

Social Network Analysis Text Analysis


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Social Network Analysis

Social Network Analysis enables researchers toexamine relationships between entities(Borgatti etal. 2009)

Enable the understanding the underlying social

processes in organisations. Can be used to understand the degree to which

PM is aligned with, and integrated intoorganizational activities

Support the designs of interventions improveproject performance.


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Text Analysis

While manual content analysis has been appliedto understand project processes in organizations(Pasian 2011)

Text-mining techniques enable the rapid review

and summarization of large volumes unstructuredtext, including documents and emails(Sukanyaand Biruntha 2012).

Enables assessors to develop an understanding of

the organization based on the actualorganizational discourse on project management.


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Integrating SNA and Text Mining

SNA and Text Mining combined can assessMaturity areas that are difficult to evaluate byconventional means Organizational support for PM

Receptivity of PM. Text mining can identify the degree to which PM is

embedded within the organization. Social network analysis can identify the extent to

which all stakeholders engage with projectmanagement


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Challenges

Data collection based on documents andrelationships can be intrusive

May reveal information that may not have beenintended by the writer or creator(Wu et al. 2012).

Aggregation of different types of data magnifiesthis issue as data (Pospiech and Felden 2012)


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Future Maturity Models

Holistic and Adaptive Maturity Models.

Holistic maturity models :all of an organizationsproject management related interactions andcontent, not just structured content, can beaccessed to assess its development.

Possible to design interventions or developmentinitiatives that can be closer matched to thereality of the organizations context

Adaptive maturity models: autonomous or

ambient data collection and real time analysisapproaches Provide insights using visual displays to enable

stakeholders to identify project management

issues in near real time.


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My Contact Information

[email protected] [email protected] @org_pm uk.linkedin.com/in/drnigelwilliams/

OPM- Organizational Project ManagementLinkedin Group

2014 Conference/LiveStream @FestIMCon2014
mailto:[email protected]://uk.linkedin.com/in/drnigelwilliams/http://uk.linkedin.com/in/drnigelwilliams/http://uk.linkedin.com/in/drnigelwilliams/http://uk.linkedin.com/in/drnigelwilliams/mailto:[email protected]


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References

Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009).Network analysis in the social sciences. science, 323(5916), 892-895.

Boyd, D., & Crawford, K. (2011). Six provocations for big data. Bryman, A. (2012). Social research methods: Oxford university

press. Chen, H., Chiang, R. H., & Storey, V. C. (2012). BusinessIntelligence and Analytics: From Big Data to Big Impact. MISQuarterly, 36(4), 1165-1188.

Dong, X. L., & Srivastava, D. Big data integration. In DataEngineering (ICDE), 2013 IEEE 29th International Conference on,

2013(pp. 1245-1248): IEEE Frankel, F., & Reid, R. (2008). Big data: Distilling meaning from

data. Nature, 455(7209), 30-30. Gupta, V., & Lehal, G. S. (2009). A survey of text mining techniques

and applications. Journal of Emerging Technologies in Web

Intelligence, 1(1), 60-76.


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Research Centre forI ti i H lth C

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Contemporary Issues in PM Maturity

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