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  • Scientia Iranica (2019) 26(1), 15{25

    Sharif University of TechnologyScientia Iranica

    Special Issue on: Socio-Cognitive Engineeringhttp://scientiairanica.sharif.edu

    Lean design management using a gami�ed system

    M. Khanzadia;�, M.M. Shahbazia, M. Arashpourb, and S. Ghoshc

    a. School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846, Iran.b. School of Property, Construction and Project Management, RMIT University, Melbourne, VIC 3000, Australia.c. The Haskell & Irene Lemon Construction Science Division, College of Architecture, University of Oklahoma, 830 Van Vleet

    Oval, Room 294GH, Norman, OK 73019-6141, USA.

    Received 18 March 2017; received in revised form 5 February 2018; accepted 16 April 2018

    KEYWORDSGami�cation;Last Planner®

    System;Design value stream;Design management;Pay for performance;Variabilitymanagement.

    Abstract. Design process, due to its information- and innovation-intensive nature,is highly susceptible to change and thus, waste. This attracted the attention of leandesign/construction professionals in the past few years. However, limited, if any, researcheshave addressed this issue from the human behavior perspective. This research proposesa method that exploits the potential of the Last Planner® System (LPS) in designmanagement. The main contribution of this paper is improving the applicability of the LPSto design processes by incorporating a gami�ed pay-for-performance system into the normalpractice of the LPS. It encourages motivating design engineers by granting them single-point, autonomous responsibility to perform their tasks. To this end, the proposed methodshifts the focus of design managers away from predicting the workow and chronologiesof design tasks to motivate design engineers to eliminate non-value-adding works/time.To bolster the concept and examine the method, it was put into practice by constructiondesign teams. Findings corroborate the e�ciency of the method in eliminating the non-value-adding works from design processes. The �ndings are of practical value to consulting�rms, especially design team managers who seek to maximize innovation, competency, andquality outcome.© 2019 Sharif University of Technology. All rights reserved.

    1. Introduction

    Design work inherently su�ers from the lack of tangibledeliverables and di�culty to evaluate/control againstprogress milestones [1]. Consequently, it is not uncom-mon that planning and controlling design processes arechaotic and involve improvising, miscommunication,lack of adequate documentation, unbalanced resourceallocation, and erratic decision making [2]. Theinternal and external interdependencies of a design

    *. Corresponding author. Fax: +98 21 77240398E-mail addresses: [email protected] (M. Khanzadi);shahbazi [email protected] (M.M. Shahbazi);[email protected] (M. Arashpour);[email protected] (S. Ghosh).

    doi: 10.24200/sci.2018.20325

    process tend to raise the level of uncertainties andvariations [3]. In lean principles, the main goal isto minimize the rate of non-value-adding (i.e., waste)work/time in the process value stream [4]. Hopp andSpearman [5] identi�ed two major sources of waste,namely workow and process time, based on which theattempts to address the subject could be categorizedinto two strategies.

    1.1. Strategies to manage wasteThe �rst strategy focuses on managing the waste ofprocess time/schedule. This strategy attempts topropose methods to predict a more precise schedule.For example, matrix based scheduling models suchas Dependency/Design Structure Matrix (DSM) [6]attempt to facilitate the formulation and implemen-tation of complex design scheduling. The DSM sug-

  • 16 M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25

    gests organizing complex schedules as matrix rowsand columns, then o�ers signals to easily identify thede�ciencies of schedule. For instance, if there is amark over the diagonal of the matrix, it indicatesthat a task gives input to an earlier task. This maybe due to poor ordering of tasks, or it reects aniteration (circuit) in the logic of the process. Someresearchers suggested using time bu�ers to increase the

    exibility of schedule [7]. A time bu�er is the di�erencebetween estimated/planned duration and the minimumduration the task should take based on optimum orbaseline productivity. Goldratt [8] developed criticalchain method based on bu�ering concept. He suggestedremoving all bu�ers within activities and placing themat the end and allowing activity delays to be absorbedby the pooled bu�er.

    The second strategy aims at minimizing the wasteof workow. In this context, the Last Planner®System (LPS) [9] has signi�cantly contributed to thelean construction literature [10]. The LPS improvesworkow by creating pull ow of resources and easesbottlenecks by �ltering out work packages that arenot ready for execution [9]. In the short-term plan,commitments are made in weekly meetings, from whichweekly work plans emerge.

    1.2. Current challenges in lean designmanagement

    Despite the reportedly successful application of theLPS in construction [11,12], there is a great deal ofdebate on the applicability of this method to designprocesses. There is a fairly common agreement inthe literature that certain characteristics of the designprocess make it fundamentally di�erent from the con-struction process, thus the same management approachmay not work for both [13,14]. This attracted theattention of design management academics and practi-tioners to modify the LPS, making it more adaptable todesign processes [11,15,16]. Fundli and Drevland [17]incorporated collaborative design management into

    LPS, applied it to a design case study, and reportedpositive �ndings. Rosas [18] integrated the DSM andLPS into building design in order to reduce the rate ofuncertainties.

    Despite the increasing commentary on its meritsand shortcomings, little work has surveyed the LPSfrom human behavior perspective. A barrier to anacceptable e�ectiveness of implementing lean methodslies in the fact that behaviorism is deeply ingrainedin such practices [19]. In fact, to achieve success,the participative approaches in construction (e.g., LPS,Collaborative Design Management, and Integrated De-sign Management) are inevitable to consider the e�ectsof human behavior [20,21].

    1.3. Common behavioral issuesAmong the roots of behavioral issues causing wasteaddressed in the literature, this research focuses ontwo major ones: over-estimation and under-estimation(Figure 1).

    1.3.1. Overestimation: Waste of timeWhen a more-than-needed time is assigned to a task,the extra time will not show up as \free time" onthe individual's activity reports, but the designer willconsume all the allotted time, resulting in loss ofproductivity. This is due to the fact that individualsare inclined to save their vital energy rather thanputting their best e�ort on work, unless they areexposed to a certain amount of stress from the lossof pro�t for a performed activity [22]. Parkinson'sLaw [23] and Student Syndrome [24] explain this as:\work expands to �ll the time available for completion"and \individuals tend to waste time and wait untilactivities get really urgent before they work on them."A simple approach to allotting less time may notwork as there are often small reasons relating toclari�cations/coordination that provide the \reason" toa design engineer for taking more time for completinga task [25].

    Figure 1. Obstacles to the ow of tasks: (a) Propositions of the Last Planner® System to eliminate the obstacles and (b)behavioral barriers in highly variable conditions.

  • M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25 17

    1.3.2. Underestimation: Cutting corners, erroneousoutcome, and rework

    On the other hand, at the task level, the studies byBuehler et al. [26] and Roy et al. [27] support the factthat when individuals underestimate the time neededto do a job, soon they run out of time, the projectruns late, and management makes their team workfaster [28]. In this situation, what we SHOULD do ismuch greater than what we CAN do, and managerstend to cut corners, which is by not checking one'swork to the degree of details necessary to �nd mostof the error. This approach increases the probabilityof errors occurring, decreases the chance of detectingerrors, increases the number of work defects throughthe selective use of information, and does not easilydiscover the associated quality problems until late ina project, resulting in reworks, quality deviations, andproductivity losses [29,30].

    2. Proposed method: Gami�ed Last PlannerPay-for-Performance (GL3P)

    Elaborating on the behavioral barriers and drivers,this research argues that in uncertain environments(e.g., design processes), activities would be vulnerableto over-/under-estimation, leading to behavioral issuessuch as Parkinson's law, student syndrome, erroneousoutcome under schedule pressure, and role ambiguities,especially in the case of complex, time-bound deliver-ables. To address these issues, this paper proposes agami�ed pay-for-performance system with three mainpropositions:

    1. Incorporated LPS to manage workow variabilities;

    2. Applied game mechanics in order to encouragedesign engineers to keep away from Parkinson's Lawand Student Syndrome; and

    3. Integrated pay-for-performance concept with gamemechanics to bring more reality into the game.

    A piece of software was developed based on thesepropositions to automate and better manage the im-plementation process.

    This research is a part of a larger study conductedby the same research team on behavioral issues inparticipative construction processes. The aim is todevelop a comprehensive framework to manage thehuman behavior embodying lean principles.

    2.1. Last Planner® basicsThe major contribution of the LPS to the lean con-struction is to minimize the waste in workow by trans-forming what SHOULD be done into what CAN bedone, forming an inventory of ready works [9]. It actson the following four project planning levels: masterplan, phase schedule, look-ahead planning, and weekly

    work plans. The master plan produces the initialproject budget and schedule, and provides a coordi-nating map that \pushes" completions and deliveriesonto the project. The phase schedule produces moredetailed and manageable plans with higher complexitylevel. The look-ahead planning focuses on controllingthe ow of work through the production system bydetailing and adjusting budgets and schedules to \pull"resources into play. Weekly work plan determines theactivities and scheduled work that will be done on-siteaccording to the status of resources and prerequisites.

    Despite the reportedly success of the LPS inreducing the waste in construction workow [31], lit-tle research, if any, has addressed the subject fromthe socio-cognitive perspective, i.e., the connectionbetween the operational elements (planning/managingtasks/resources and utilizing control functions) and thebehavioral/social elements. The socio-cognitive issuecomes to the fore in design workow due to the highercomplexity and unique characteristics of design processthat make it fundamentally di�erent from the buildingprocess [15]. Hamzeh et al. [16] highlight the followingfactors that make design more complex and distinctfrom building:

    Greater uncertainty, thus lower predictability offuture tasks;

    The impact of increasing execution speed of designtasks on removing constraints and making tasksready for execution;

    Interdependencies between design tasks, which in-crease the level of complexity;

    In design, more work is done by individual special-ists than in construction. Therefore, the ability toassess capacity when responding to requests requiresindividual work plans at the commitment level.They conclude that (1) the level of interdependencein design is much higher than that in construc-tion; (2) design tasks are subject to higher levelof complexity than building tasks are, due to thehigher interdependencies; and (3) the consequencesof human behavior are more signi�cant in designthan in construction.

    This paper takes advantages of game mechanicsapplied to the LPS in order to facilitate design man-agement from the behavioral perspective.

    2.2. Gami�cation and game mechanicsGami�cation is commonly de�ned as the use of gameelements in non-game contexts [32]. Game, in classiccontext, is \a rule-based formal system with a variableand quanti�able outcome, where di�erent outcomes areassigned di�erent values, the player exerts e�ort in or-der to inuence the outcome, the player feels attachedto the outcome, and the consequences of the activity

  • 18 M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25

    are optional and negotiable" [33]. The conceptual aimof gami�cation is to make activities enjoyable by addinginherently enjoyable game elements. For this, gamemechanics can be layered on top of serious works anddrive engagement, proactivity, and loyalty [34].

    Gami�cation has been increasingly used as a pro-cess of enhancing services with motivational a�ordancein order to invoke gameful experiences and furtheroutcomes [35]. Industry professionals have taken noticeof this trend and have attempted to apply motivationalpotential of games to various non-gaming contexts tofoster user engagement by rewarding and directingemployee attention to particular focal conducts [36,37].

    The proposed method takes advantage of gameelements (i.e., points, levels, scoreboard), encour-aging designers to avoid engaging in non-value-adding works/times. The point allotted to a taskrepresents the value the task contributes to theproject/organization. At the end of each month, thetotal points gained by a player are taken as the basisfor payments. This is in congruence with pay-for-performance (P4P) concept, which involves provid-ing rewards through carefully designed compensationsystems that base payment on the measured perfor-mance [38].

    2.3. Pay-for-performancePay-for-performance is payments to individuals accord-ingto their performance. In this payment system, anindividual risks not receiving (either the whole or apart of) the payment unless the same or a higherlevel of performance is achieved by reaching the targetsassigned [39]. To develop a fair payment system, anelaborate performance metric is needed.

    2.3.1. Performance metricThe main driver in ruling performance is the rate thetask exceeds its due date. To put emphasis on this, thedelayed tasks are penalized as shown in Eq. (1):

    PFi = min�

    1;max�

    0; PPFj�DOi �DUiDUi �DAi

    ���;

    i = 1; 2; � � � ; n; j = 1; 2; � � � ;m; (1)where PFi is the penalty factor for task i; PPFj is thepenalty factor for project j; DOi, DUi, and DAi arethe dates when the task i has been assigned, has beendone, and should have been done, respectively; n isthe number of tasks; and m is the number of projects.The point assigned to task i, Pi, is then modi�ed usingEq. (2):

    P �i = Pi(1� PFi): (2)At the end of each month, the total point gained byemployee k, TPk, is calculated using Eq. (3), based

    on which a scoreboard is created (Figure 2). Teammembers are able to monitor their position in theboard. This motivates them to adjust their position byworking harder and taking corrective actions for thenext week. This is in accordance with the reinforce-ment immediacy concept, that is, the shorter the delaybetween the action and the reinforcement, the more ef-fective the reinforcement will be, because the contiguityor connection between the two is strengthened:

    TPk =nXi=1

    P �i : (3)

    The scoreboard will be taken as the basis for calculatingvariable pay, V Pk, using Eq. (4):

    V Pk = V PB�TPk�� lXk=1

    TPk��1

    ; k = 1; 2; :::; l;(4)

    where V PB is the Variable Pay Budget (e.g., for adivision) and l is the number of employees.

    3. Design and implementation

    A client-server desktop application was implementedto examine the applicability of the proposed method indesign management.

    3.1. Task life-cycleEach task can end with one of the three states: DONE,APPROVED, or CANCELED; otherwise, it would beIN-PROGRESS. These states can be updated by theassignee or by the manager in weekly meetings. As-signees do not receive points unless they shift the statusto DONE and then APPROVED. The unaccomplishedtasks (i.e., IN-PROGRESS) are questioned for reasonsand the possible obstacles are discussed in the meetingslike a brain-storming session. To address the obstacles,new tasks may emerge from the brain-storming; thetasks are then re�ned, prioritized, and fed into the life-cycle. If a task is determined as not doable, it will beCANCELED. Figure 3 shows the task life-cycle duringa meeting.

    3.2. Noti�cation systemNotifying parties in a timely, sustainable manner wasa focus in designing and implementing the program.In this sense, an elaborate noti�cation service wasdeemed crucial. PostgreSQL [40], for its asynchronousLISTEN/NOTIFY feature, was favored for this pur-pose. The messaging mechanism is used along withtriggers to issue noti�cations to other clients. In thismechanism (Figure 4), all clients listen for updatesfrom the projects they are a member of. Once atask is updated, a message is broadcasted to the otherparties of the same project, displaying a popup window(Figure 5).

  • M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25 19

    Figure 2. Monthly scoreboard of the team members' performance.

    Figure 3. Flowchart of creating/updating tasks in weeklymeetings.

    Furthermore, PostgreSQL facilitates developmentof triggers and functions in high-level programminglanguages (e.g., Python [41]). This feature allowedhighly complex logic blocks to be easily developed andmaintained. For example, when an urgent task is

    Figure 4. Noti�cation broadcast mechanism.

    created, using python triggers, the database sends anemail and/or text message to the o�ine assignees. Todo so, a client (Delphi application) creates a task inthe database (PostgreSQL) and the database checksthe assignee's situation (online/o�ine); if the assigneeis not connected to the server, PostgreSQL triggersthe functions \send email" and \send sms" written inplpython (i.e., Python in PostgreSQL) (Figure 6).

    3.3. Roles and permissionsTo support the matrix organization structure [42], therelationship between project and members is taken asmany-to-many, that is, individuals may play di�erent

  • 20 M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25

    Figure 5. Noti�cation popup window.

    Figure 6. The application of triggers in routing noti�cation messages.

    roles in di�erent projects (Figure 7). The commonroles and permissions that are supported by the soft-ware are listed in (but not limited to) Table 1 andFigure 7.

    - Doer: Doers are those who perform the tasks. Theycan create tasks for themselves, but are not allowedto assign tasks to the other parties. They can alsocomment and attach �les to the assignments;

    - Coordinator: Coordinators have doers' authorities,plus they can assign tasks to the other members;

    - Supervisor: They inherit all the authorities fromthe coordinators, plus they can approve the tasksaccomplished by the assignees;

    - Leader: Project leaders have all the authorities theyneed to manage the project. They can add/removemembers to/from the project, and grant them thenecessary permissions. They can also edit/removethe others' tasks.

    It should be noted that these roles are not rigid andunchangeable. For instance, the project leader candelegate some roles to the supervisor. On the other

  • M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25 21

    Figure 7. The role of each member in each project.

    Table 1. Original role authorities in GL3P.

    Leader Supervisor Coordinator Doer

    Add � � � �Assign � � �Attach � � � �

    Comment � � � �Approve � �

    Rate �Lead �

    hand, the project members are not limited to onlyone organization. It is possible to have participantsfrom the other organizations and individuals (e.g.,contractors, owner, shareholders, stakeholders, etc.).

    4. Case study

    The proposed method was examined and validated bydesign teams in 17 civil engineering projects, espe-cially marine structures and o�shore engineering, fora period of approximately four months. Among theparticipants, 33% were older than 35 years old, 50%were between 30 and 35, and the rest were youngerthan 30. In terms of academic quali�cations, 33% ofthe participants had Master's degree or above and 67%

    had Bachelor's degree. 17% of the participants hadmore than 10, 67% between 5 and 10, and the rest lessthan 5 years of experience. The process entailed thefollowing two stages:

    Stage 1: Before gami�cationAt the �rst stage, the authors studied and gathereddata from the current task accomplishment process.To do so, the team members were given task sheetsto document what they did on a daily basis. Themanager was then asked to assign points to the tasks herecognized as accomplished properly. The points werejudged based on the reasonable time needed for doingthe task.

    Stage 2: After gami�cationThe objective of this stage was to examine the impactof the proposed method on increasing the rate of VA. Atthis stage, meetings were conducted on a weekly basis.In the meetings, the tasks were evaluated, passing theevaluation process, and weekly work plans emerged forthe upcoming week.

    4.1. Results and discussionThe value-added time (i.e., the sum of points as-signed to the approved activities) was measured andcompared with the total presence time as shown inFigure 8.

  • 22 M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25

    Figure 8. Comparing the Value-Adding (VA) times and total presence times between Stage 1 and Stage 2.

    Figure 9. Comparing the rates of VA time between Stage 1 and Stage 2.

    It should be emphasized that contrary to taskdurations, a point, once assigned to a task, cannotbe mutated by elongating/shortening the time spent.This minimizes the negative impacts of under-/over-estimations. The GL3P encourages the assigneesto accomplish the tasks at the minimum duration,then proceed to the next in the list. This providesteam members with the opportunity to shift up theirposition on the board, achieving more satisfying pay-ments.

    Using Figure 8, the rate of VA time can be drawnas shown in Figure 9.

    To ensure a statistically rigorous comparison be-tween Stage 1 and Stage 2, paired two-sample t-testswere conducted at the con�dence level of 95% (� =0:05). Doing so, the following null hypothesis wastested:

    Hypothesis: Utilizing GL3P in design managementmakes no signi�cant di�erence between the rate of VAin Stage 1 and that in Stage 2.

    The results of statistical analysis (p- and t-value)are given in Table 2, from which a signi�cant decrease(46%) in the rate of non-value-adding time can beconcluded. The p < 0:05 is the evidence for rejectingthe null hypothesis.

    5. Conclusions

    Focusing on behavioral barriers bring about waste indesign processes. This research aimed at contributinga step forward in eliminating waste from the designprocesses using a gami�ed system, GL3P, o�ering thefollowing propositions:

  • M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25 23

    Table 2. Results of two-sample t-test.

    Presence Approved (%) VAStage 1 Stage 2 Stage 1 Stage 2 Stage 1 Stage 2

    Sum 1395 1472 { { 327 900Mean 174 184 69.3 91.3 40.9 112.5SD 22.5 26.2 10.9 6.8 12.1 20.2t {0.8 {4.8 {8.6p 0.564 0.001 0.000

    1. Taking advantage of the LPS concept, especially theweekly meetings;

    2. Incorporating game mechanics into the tasks emerg-ing from the weekly meetings, i.e., weekly workplans;

    3. Associating the payments with gami�ed system us-ing the pay-for-performance concept.

    To facilitate the implementation and measurement, adesktop application was developed.

    The proposed method is novel to the lean de-sign management literature for integrating the LPS,gami�cation, and pay for performance concepts, basedon which a computer program, GL3P, is developedand put into practice. GL3P encourages man-agers/organizations to shift the basis of payment andfocus of design management from \presence time" to\value-adding time". The method was examined bydesign teams and the results corroborated its meaning-ful impact on enhancing the performance of the designteams.

    The contribution of this research should be con-sidered in light of several limitations, each of whichcan signal possible directions for future research: �rst,it is not easy to implement changes in companies. Infact, many people feel controlled when the evaluationstage is carried out. Setting goals, assigning tasks, anddetermining the value after the fact, while accountingfor situational factors, require managers to understandthe full context of employees' performance and createawareness about the principles of lean. Second, touch-ing the engineers' payments would raise opponents,of which the managers are often afraid. Lessonslearned from empirical applications suggest relying onnon-controlling and informational language, displayingpatience to accept the opponents' expressions, andgiving them time to adjust themselves to the newsystem. Nevertheless, these human-nature barrierstend to vanish when improvements start to appear.

    This research contributes to the body of knowl-edge in construction design management by providingdesign managers with the means to automate designtasks management and designer's performance moni-toring using a gami�ed system.

    Acknowledgement

    The authors would like to thank Professor Ron Wake-�eld at RMIT University for his kind support.

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  • M. Khanzadi et al./Scientia Iranica, Special Issue on: Socio-Cognitive Engineering 26 (2019) 15{25 25

    Biographies

    Mostafa Khanzadi is Associate Professor of Con-struction Engineering and Management in the De-partment of Civil Engineering at Iran University ofScience and Technology. His research interests includeperformance management, decision support systems,and strategic project management.

    Mohammad Mahdi Shahbazi is PhD candidate inConstruction Engineering and Management at IranUniversity of Science and Technology. For his thesis,he has been working on incorporating gami�cationconcepts into lean construction principles aiming atimproving the performance of construction/design en-gineers through mitigating the e�ects of behavioralissues and motivating them to perform better. In thissense, he has been contributing to the development andimplementation of the following gami�ed lean systems:

    Tetron, a gami�ed design management system basedon task repositories; Harmonix, a gami�ed task man-agement system for construction sites; and DocMe, agami�ed lean document/knowledge management sys-tem in which the construction engineers are motivatedto share their knowledge.

    Mehrdad Arashpour is Lecturer and Researcherin the School of Property, Construction and ProjectManagement. His research focuses on process opti-mization and automation, productivity improvement,civil engineering design, uncertainty management, andoperations research.

    Somik Ghosh is Assistant Professor in the Haskell& Irene Lemon Construction Science Division. His re-search interests are lean construction, multidisciplinarycollaboration, occupational safety, and resilience engi-neering.


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