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Achieving project success using Theory of Constraints beyond Critical Chain Project Management

PhD Research proposalMaryam Mirzaei

School of Management

Supervisors:Prof. Vicky Mabin

Dr. Jim Sheffield

Date: 28 Feb 2013

Overview Introduction Theory of Constraints (TOC) Critical Chain Project Management (CCPM) Moving beyond CCPM Research question Methodology

Introduction • Motivation

Project management as my research area Project management as my career path Critical chain project management as “the answer” Viewing my research as a project raised “new questions”

• Significance of the Study Project management is the most significant characteristic of the modern

organizations Scholars call for new approaches in project management Theory of constraints has provided breakthrough solution in many areas Project classification is an emerging knowledge base

TOC What it is , where it has emerged

how it deal with uncertainty ,

(Goldratt & Cox, 1984)

TOC

Manufacturing

Distribution

Throughput Accounting

Marketing

Strategic planning

CCPM Assumptions:Known tasks Known durationsKnown capacities (machine and human) Resource conflict (scarce resources)Structured network (precedence relations)

CCPM

CCPM Single Project Multi project

Prerequisite 1 - Identify the System and its Purpose

The Project(Leach, 1999; Steyn, 2001)

Collection of projects(Deac & Vrincut, 2010; Globerson, 2000; Lechler et al., 2005)

Prerequisite 2 - Determine the System’s Measures

Duration(Leach, 1999; Steyn, 2001)

Profit (Throughput)(Deac & Vrincut, 2010; Globerson, 2000; Lechler et al., 2005)

1. IDENTIFY the system's constraint

Longest chain of activity (Goldratt, 1997; Leach, 2004, p. 106)

Bottleneck resource (Budd & Cerveny, 2010; Cohen, Mandelbaum, & Shtub, 2004; Herroelen & Leus, 2001; Huang, Chen, Li, & Tsai, 2012; Leach, 2004 ;Newbold, 1998)

2. Decide how to EXPLOIT the system's constraint

Remove the individual buffer(Goldratt, 1997, p. chapter 13)

No Idle time for bottleneck resource (Budd & Cerveny, 2010; Cohen, Mandelbaum, & Shtub, 2004; Herroelen & Leus, 2001; Huang, Chen, Li, & Tsai, 2012; Leach, 2004 ;Newbold, 1998)

3. SUBORDINATE everything else to the above decision

Add feeding buffer(Cox et al., 2012, p. 76)

Add capacity buffer(Budd & Cerveny, 2010; Cohen, Mandelbaum, & Shtub, 2004; Herroelen & Leus, 2001; Huang, Chen, Li, & Tsai, 2012; Leach, 2004 ;Newbold, 1998)

4. ELEVATE the system's constraint (Leach, 1999; Steyn, 2001)

?

5. Repeat ? ?

CCPM ,

Endorsements of CCPM Direction for project management in the 21st century

(Newbold, 1998; Steyn, 2002; Vrincut, 2009)

Numerous successful applications(Bevilacqua, Ciarapica, & Giacchetta, 2009; Hwang, Chang, & Li, 2010; Leach, 1999; Newbold, 2008; Paseuth, 2003; Realization Technologies,

Inc, 2010; Smith, 2012; Srinivasan, Best, & Chandrasekaran, 2007; Stratton, 1998; Umble & Umble, 2000; Viljoen, 1997)

Simple and workable (Newbold, 1998; Steyn, 2002; Vrincut, 2009; Raz et al., 2003)

Stable schedule, Minimises work in progress (Herroelen, Leus, & Demeulemeester, 2002; PMI, 2008; Woeppel, 2005)

Addresses duration uncertainty well (Elton, 1998; Herroelen et al., 2002; Herroelen & Leus, 2001; Raz, Barnes, & Dvir, 2003)

Takes human factors into account(Goldratt, 1997; Huang et al., 2012; Leach, 1999; Newbold, 1998; Woeppel, 2006)

Criticisms on CCPM

Not applicable to all kind of projects(Mckay & Morton, 1998; Raz et al., 2003)

Not innovative (Trietsch, 2005)

Lack of mathematical analysis(Ashtiani, Jalali, Aryanezhad, & Makui, 2007; Jian-Bing, Hong, & Ji-Hai, 2008; Kuo, Chang, & Huang, 2009)

Creating a good baseline schedule is not easy(Raz et al., 2003)

Rejects data in later stages of the project(Dietrich & Lehtonen, 2005; Cohen et al., 2004)

Assumptions need to be clarified(Hill, Thomas, & Allen, 2000; Raz et al., 2003)

Success of a single project is measured in term of its duration

Success of a portfolio of projects is measured in term of its profit

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Project successSuccess factors Project managers expertise (Rubin & Seelig, 1967)

Top management support (Avots, 1969),

Ten key success factors (Slevin and Pinto, 1987)

Project team skills (Brown, 2001)

96 different variables (Shenhar and Dvir,1996)

Grouped success factors (Belassi & Tukel, 1996)

Senior management commitment/ organizational structure

and risk management (Lester, 1998)

Defining the project team (Abdel-Hamid, Sengupta, and Swett, 1999)

Documentation-based learning (Schindler & Eppler, 2003)

Quality of planning, goal changes, and plan-changes (Dvir and

Lechler, 2004)

More comprehensive success factors (Ika, 2009)

Necessary conditions versus sufficient conditions (Poon,

Young, Irandoost and Land, 2011)

Success criteria

Time/ Cost /Quality

Meeting the design goals/benefit to the development of the company/benefit to end user (Arye ,2000)

End-user satisfaction / customer-satisfaction (Hoegl and Gemuenden, 2001)

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Project success

Success and ways of achieving it will differ based on:

Project life cycle

Portfolio influence

Project type (classification)

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Research QuestionsHow can the application of TOC to project management move beyond CCPM?

• How are project constraints influenced by its characteristics?

• How are project constraints influenced by its portfolio?

• Why can certain available / proposed models or methods address certain types of constraints better?

CCPM and project typology

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Methodology

According to Yin how and why questions could be answered using case study

Case study as a research method allows in-depth analysis of an existing phenomenon

The nature of research is exploratory as there is no assumed hypothesis of what the constraints should be. And the research is the first of its type (looking for different types of constraint in different types of projects)

Research method: Case study

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Project management is action oriented Prescriptive research seeks to help people solve practical problems (Ahlemann et al., 2012; Denyer, Tranfield, & Aken, 2008; Easterby-Smith, Thorpe, Jackson, & Easterby-Smith, 2008).

“Prescriptive research is the heart of project management discipline” (Ahlemann et al., 2012)

Design Sciences Paradigm(Denyer et al., 2008; Ahlemann et al., 2013; Denyer et al., 2008; Simon, 1996)

technology-oriented counterpart to natural sciences Design of artifacts that serve human beings (tangible and intangible)

Methodology

Research approach: Abductive• Deduction– an analytic process based on the application of general rules toparticular cases with the inference of a result

• Induction– synthetic reasoning which infers the rule from the case and theResult

• Abduction– another form of synthetic inference but of the case from a ruleand a result

(Adapted from Dubois & Gadde, 2002; Kovacs & Spens, 2005)

Methodology

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Logic models Intermediate Objective map:A system level logic tree based on necessary condition relationships (Dettmer, 2007)

Data AnalysisCurrent reality tree:a logic-based tool for using cause-and-effect relationships to determine root problems that cause the undesirable effects of the system (Cox, 2003; Goldratt, 1994; Kim, Mabin, & Davies, 2008; Mabin, 1999; Scheinkopf, 1999)

Case investigation process Multiple sources of data

will be used including:

Documentation

Structured Interviews

Semi structure Interviews

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Project portfolios • Collective success of single

projects (Artto and Dietrich, 2007; Martinsuo and Lehtonen,

2007; Platje, Seidel, & Wadman, 1994)

• Alignment with organization strategy both deliberate and emergent (Boyd, Gupta, & Sussman, 2001; Meskendahl,

2010, 2010; Muller, Martinsuo, & Blomquist, 2008; Pearson, 1990; Pellegrinelli, 1997)

• Balanced along a range of dimensions (Archer & Ghasemzadeh, 1999; Cooper,

Edgett, & Kleinschmidt, 2001; Killen et al., 2008; Mikkola,2001)

• Profitability (Cooper et al., 2001; Chang, Kan, & Wang, 2010)

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Project classificationMatrix classifications: Two dimensions: End and Means (Pearson, 1990)

Three dimensions: Software–Hardware / strategic goal of the project / technological uncertainty (D Dvir et al., 1998)

Five dimensions:

1. Strategic goal of the project2. Market uncertainty3. Technological uncertainty4. System scope5. Pace (Shenhar, 2001; Shenhar et al., 2002)

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Pilot case study 1

NC: adopt Lean cosntruction policy

Goal: Maximum profit by construction of 174 three story housing units

CSF: minimix cost CSF: do not pay conpensation for delay

NC: minimise material cost

NC : minimise movement cost

NC: minimise labour cost NC: Minimize material misplace and abuse and forge claims

NC: follow a sound schedule

NC: keep good record of excuses to request extention

NC: maintain quality to avoid rework

NC: provide material in advance on time to the site to avoide delay

NC: assure more labours work on the site

NC: produce some of basic material such as blocks, and precast elements near the site NC : invest in material purchase before the peak demand start

NC: avoide direct labour and always employ subcontractors

NC: organize Professional procuement team

NC: use an advanced information management system

NC: pay subcontractors regualrly as per work done

NC: claim for material in site

NC: constantly look for more subcontractorsNC: facilitate overtime work for subcontractorsNC: constantly look for more subcontractors

NC: organize good supervision on site NC: collaborate supervision with donors

UDE1: it is expensive to transport required material

UDE2: Construction material are in high demand in that area

UDE3: Construction workers are in high demand

UDE4: Schedules are prepared and decided independent from construction actors,

UDE5: Schedules require to be changed very often

UDE6: existing audit may be very late to indicate any issue related to abuse and misplace

UDE7: The amount of work is overwhelmingly large that an individual project manager can not handle organizing everything

UDE8: It is very difficult to negotiate with new contractors, if we pay more we need to pay more to existing constractors in this project as well as other projects they are involved

UDE9: Subcontractors do not understand the profitability of their work until they get paid, and sometime they overclaim and realize their states when it is too late

UDE10: direct labour is very risky

UDE11: There are very few contractors who have experience to do such big projects

UDE12: New contractors are not likely to succeed

UDE13: Conmix do not have a management system for its construction unit and they use same system as distribution unit for track of material

UDE14: Office work in the site is very costly (due to high demand in the area)

UDE15: Conmix can not directly control number of labours

UDE16: External work is not possible to be performed in the bad weather condition

UDE17: Long term schedule cannot account for weather condition

UDE18: There are many political and ethnic conflicts in that area that stops the work for 1/3 days

UDE19: limited material can be stored in the site

E1: many large project starting in the area

UDE20: schedules are not effective

UDE21: There is a high cost of material

UDE22: It is hard to aquire enough labours

E2: conmix do not have a systematic approach that allow management of site in several level by several individuals

E4: the area is not prefered by employees

E5: any job done at the site will be paid irrespective of its place in the schedule

E6: measures happen only along with biddings to save quantity surveys time

AND

AND

AND

AND

E7: subcontractors alter schedules to get more work done

E8: Work will not be interupted for any worker with specialty

E9: Constrcution workers are usually multifunctional

UDE23: there is no local large quantity supplier of construction material

E10: Conmix own construction several material production and distribution unites in other cities

AND

DE1: Cost of transport is very high

E11: Some material will vanish gradually if it is supplied in large quantity (sand, cement

UDE24: Material shortage can interupt the work

E12: There is no large storage area nearby the site for collection of sand and metal

AND

AND

AND

E13: construction material are heavy and large in size

Root cause matches literature

Data Analysis

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Pilot case study 2

Data Analysis

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Research Quality

Internal Validity

Classification of data: Project profile

TOC’s tools to scrutinise logic diagrams (Dettmer, 2007)

External Validity

Generalizability : from single case to type of projects

Reliability of the results

Data base : Tables and diagrams

Multi-source data

Chain of evidence

Data Analysis

Schedule

Contributions • Opportunity for new TOC applications to emerge to

address projects that have not been addressed by CCPM

• Identification of 2-4 specific types of constraints that is common in a group of projects

• Contribution to classification models by describing the types of constraints that exist in a few different classes of projects

• Suitability of new models can be investigated as per project typology

Anticipated Issues/Limitations

Issues • Access to projects with required characteristics• Access to multiple interviews with project manager

Limitations • Possible number of cases • Predicted diversity of constraints • Generalisability • Whole picture of constraint/project typology

Questions

• Thanks!

Overview-Theoretical

Overview-Theoretical

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Methodology• Research approach:

Abductive

Kovacs & Spens, 2005

(Hallgren, 2012)

Assumption challenging research increases the chance to create interesting theories (Sandberg & Alvesson, 2011).

Five dimensions Matrix Dimension

Strategic goal of the project

Extension Strategic Problem solving

Utility Research

Market uncertainty

Derivative Platform Breakthrough

Technological uncertainty

Low Medium High Super high

System scope Assembly System Array

Pace Regular Fast/competitive

Blitz/Critical