The iterative cycles used in agile software development create a series of deadlines for project teams. We investigate the optimal iteration length under behavioral conditions for agile software projects. Based on system dynamics simulation, we argue that both very long (as in sequential development) and very short (monthly) iterative cycles create huge and disruptive fluctuations in schedule pressure experienced by the team. These lead to poor performance in terms of quality, as well as costs and time compared with optimal iterative cycles of two to three months. The monthly cycles used in many agile practices might be too short to ensure optimal performance.
Abdel-HamidT. K.SenguptaK.SwettC. (1999). The impact of goals on software project management: An experimental investigation. MIS Quarterly, 23(4), 531–555.
5.
ÅgerfalkP. J.FitzgeraldB.SlaughterS. A. (2009). Flexible and distributed information systems development: State of the art and research challenges. Information Systems Research, 20(3), 317–328.
6.
AgrawalM.ChariK. (2007). Software effort, quality, and cycle time: A study of CMM level 5 projects. IEEE Transactions on Software Engineering, 33(3), 145–156.
7.
AkkermansH.van OorschotK. E. (2016). Pilot error? Managerial decision biases as explanation for disruptions in aircraft development. Project Management Journal, 47(2), 79–102.
8.
AmabileT. M. (1988). A model of creativity and innovation in organizations. In StawB. M.CummingsL. L. (Eds.), Research in organizational behavior (Vol. 10, pp. 123–167). Greenwich, CT: JAI Press.
9.
AmabileT. M.HadleyC. N.KramerS. J. (2002). Creativity under the gun. Harvard Business Review, 80(8), 52–63.
10.
AnconaD.OkhuysenA.PerlowL. (2001). Taking time to integrate temporal research. Academy of Management Review, 26(4), 512–529.
AustinR. D. (2001). The effects of time pressure on quality in software development: An agency model. Information Systems Research, 12(2), 195–207.
13.
AustinR. D.DevinL. (2009). Weighing the benefits and costs of flexibility in making software: Toward a contingency theory of the determinants of development process design. Information Systems Research, 20(3), 462–477.
14.
BaerM.OldhamG. R. (2006). The curvilinear relation between experienced creative time pressure and creativity: Moderating effects of openness to experience and support for creativity. The Journal of Applied Psychology, 91(4), 963–970.
15.
BjarnasonE.WnukK.RegnellB. (2012). Are you biting off more than you can chew? A case study on causes and effects of overscoping in large-scale software engineering. Information and Software Technology, 54(10), 1107–1124.
16.
BoehmB. W. (1981). Software engineering economics. Englewood Cliffs, NJ: Prentice-Hall.
17.
BoehmB. W.TurnerR. (2005). Management challenges to implementing agile processes in traditional development organizations. IEEE Software, 22(5), 30–39.
18.
BohW. F.SlaughterS. A.EspinosaJ. A. (2007). Learning from experience in software development: A multilevel analysis. Management Science, 53(8), 1315–1331.
19.
BuehlerR. D.GriffinD.RossM. (1994). Exploring the “planning fallacy:” Why people underestimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366–381.
20.
BuehlerR.GriffinD.RossM. (2002). Inside the planning fallacy: The causes and consequences of optimistic time predictions. In GilovichT.GriffinD.KahnemanD. (Eds.), Heuristics and biases: The psychology of intuitive judgment. Cambridge, UK: Cambridge University Press.
21.
CaoL.RameshB.Abdel-HamidT. (2010). Modeling dynamics in agile software development. ACM Transactions on Management Information Systems, 1(1), 1–26.
22.
ConboyK. (2009). Agility from first principles: Reconstructing the concept of agility in information systems development. Information Systems Research, 20(3), 329–354.
23.
ConfortoE. C.SalumF.AmaralD. C.Da SilvaS. L.de AlmeidaL. F. M. (2014). Can agile project management be adopted by industries other than software development?Project Management Journal, 45(3), 21–34.
24.
CooperR. G. (1994). Perspective third-generation new product processes. Journal of Product Innovation Management, 11(1), 3–14.
25.
CooperR. G. (2008). Perspective: The Stage-Gate® idea-to-launch process—Update, what’s new, and NexGen systems. Journal of Product Innovation Management, 25(3), 213–232.
26.
CroninM.GonzalezC.StermanJ. (2009). Why don’t well-educated adults understand accumulation?Organizational Behavior and Human Decision Processes, 108(1), 116–130.
27.
DavisJ. P.EisenhardtK. M.BingmanC. B. (2007). Developing theory through simulation methods. Academy of Management Review, 32(2), 480–499.
28.
DawsonR. J.DawsonC. W. (1998). Practical proposals for managing uncertainty and risk in project planning. International Journal of Project Management, 16(5), 299–310.
29.
DingsøyrT.NerurS.BalijepallyV.MoeN. (2012). A decade of agile methodologies: Towards explaining agile software development. The Journal of Systems and Software, 85(6), 1213–1221.
30.
DruryM.ConboyK.PowerK. (2012). Obstacles to decision making in agile software development teams. Journal of Systems and Software, 85(6), 1239–1254.
31.
DuttaA. (2001). Business planning for network services: A systems thinking approach. Information Systems Research, 12(3), 260–283.
32.
DybåT.DingsøyrT. (2008). Empirical studies of agile software development: A systematic review. Information and Software Technology, 50(9–10), 833–859.
33.
EisenhardtK. M.TabriziB. N. (1995). Accelerating adaptive processes: Product innovation in the global computer industry. Administrative Science Quarterly, 40, 84–110.
34.
EllisA. P. J. (2006). System breakdown: The role of mental models and transactive memory in the relationship between acute stress and team performance. Academy of Management Journal, 49(3), 576–589.
35.
EricksenJ.DyerL. (2004). Right from the start: Exploring the effects of early team events on subsequent project team development and performance. Administrative Science Quarterly, 49(3), 438–471.
36.
FitzgeraldB.HartnettG.ConboyK. (2006). Customising agile methods to software practices. European Journal of Information Systems, 15(2), 197–210.
37.
FordD. N.StermanJ. D. (1998). Dynamic modeling of product development processes. System Dynamics Review, 14(1), 31–68.
38.
FowlerM.HighsmithJ. (2001). The agile manifesto. Software Development, 9, 28–32.
39.
FruhlingA.de VreedeG. J. (2006). Field experiences with eXtreme programming: Developing an emergency response system. Journal of Management Information Systems, 22(4), 39–68.
40.
GardnerH. K. (2012). Performance pressure as a double-edged sword: Enhancing team motivation but undermining the use of team knowledge. Administrative Science Quarterly, 57(1), 1–46.
41.
GeversJ. M. P.van EerdeW.RutteC. G. (2001). Time pressure, potency, and progress in project groups. European Journal of Work and Organizational Psychology, 10(2), 205–221.
42.
GlaielF.MoultonA.MadnickS. (2013, July21–25). Agile project dynamics: A system dynamics investigation of agile software development methods. In Proceeding of 31st International Conference of the System Dynamics Society, Cambridge, MA.
43.
GlickmanS.KopchoJ. (1995). Bellcore’s experiences using Abdel-Hamid’s systems dynamics model. COCOMO Conference, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA.
44.
GoldrattE. (1997). Critical chain. Great Barrington, MA: The North River Press.
45.
HarrisM. L.CollinsR. W.HevnerA. R. (2009). Control of flexible software development under uncertainty. Information Systems Research, 20(3), 400–419.
46.
HomerJ. (2014). Levels of evidence in system dynamics modeling. System Dynamics Review, 30(1–2), 75–80.
47.
IansitiM.MacCormackA. (1997). Developing products on internet time. Harvard Business Review, 75(5), 108–117.
48.
KarauS. J.KellyJ. R. (1992). The effects of time scarcity and time abundance on group performance quality and interaction process. Journal of Experimental Social Psychology, 28(6), 542–571.
49.
KellyJ.KarauS. (1999). Group decision making: The effects of initial preferences and time pressure. Personality and Social Psychology Bulletin, 25(11), 1342–1354.
50.
KesslerE. H.BierlyP. E. (2002). Is faster really better? An empirical test of the implications of innovation speed. IEEE Transactions on Engineering Management, 49(1), 2–12.
51.
LarmanC. (2006). Agile and iterative development: A manager’s guide. In CockburnA.HighsmithJ. (Eds.), Agile software development series. Boston, MA: Addison-Wesley Publishing Company.
52.
LathamG. P.SeijtsG. H. (1999). The effects of proximal and distal goals on performance on a moderately complex task. Journal of Organizational Behavior, 20(4), 421–429.
53.
LeeG.XiaW. (2010). Toward agile: An integrated analysis of quantitative and qualitative field data on software development agility. MIS Quarterly, 34(1), 87–114.
54.
LindstromL.JeffriesR. (2004). Extreme programming and agile software development methodologies. Information Systems Management, 21(3), 41–60.
55.
LyneisJ. M.FordD. N. (2007). System dynamics applied to project management: A survey, assessment, and directions for future research. System Dynamics Review, 23(2–3), 157–189.
56.
MarksM.MathieuJ.ZaccaroS. (2001). A temporally based framework and taxonomy of team processes. Academy of Management Review, 26(3), 356–376.
57.
MarupingL. M.VenkateshV.AgarwalR. (2009). A control theory perspective on agile methodology use and changing user requirements. Information Systems Research, 20(3), 377–399.
58.
MarupingL. M.VenkateshV.ThatcherS. M. B.PatelP. C. (2015). Folding under pressure or rising to the occasion? Perceived time pressure and the moderating role of team temporal leadership. Academy of Management Journal, 58(5), 1313–1333.
59.
McDermottC. (1999). Managing radical product development in large manufacturing firms: A longitudinal study. Journal of Operations Management, 17(6), 631–644.
60.
MiddletonP.JoyceD. (2012). Lean software management: BBC worldwide case study. IEEE Transactions on Engineering Management, 59(1), 20–32.
61.
Molokken-ØstvoldK.JørgensenM. (2005). A comparison of software project overruns—Flexible versus sequential development models. IEEE Transactions on Software Engineering, 31(9), 754–766.
62.
MooreJ. E. (2000). One road to turnover: An examination of work exhaustion in technology professionals. MIS Quarterly, 24(1), 141–168.
63.
NanN.HarterD. E. (2009). Impact of budget and schedule pressure on software development cycle time and effort. IEEE Transactions on Software Engineering, 35(5), 624–637.
64.
OhlyS.SonnentagS.PluntkeF. (2007). Routinization, work characteristics and their relationships with creative and proactive behaviors. Journal of Organizational Behavior, 27(3), 257–279.
65.
OlivaR.StermanJ. D. (2001). Cutting corners and working overtime: Quality erosion in the service industry. Management Science, 47(7), 894–914.
66.
PearsallM.EllisA.SteinJ. (2009). Coping with challenge and hindrance stressors in teams: Behavioral, cognitive, and affective outcomes. Organizational Behavior and Human Decision Processes, 109(1), 18–28.
67.
PerlowL. A. (1999). The time famine: Toward a sociology of work time. Administrative Science Quarterly, 44, 57–81.
68.
PetersenK.WohlinC. (2010). The effect of moving from a plan-driven to an incremental software development approach with agile practices. Empirical Software Engineering, 15(6), 654–693.
69.
PlyJ. K.MooreJ. E.WilliamsC. K.ThatcherJ. B. (2012). IS employee attitudes and perceptions at varying levels of software process maturity. MIS Quarterly, 36(2), 601–624.
70.
PortD.BuiT. (2009). Simulating mixed agile and plan-based requirements prioritization strategies: Proof-of-concept and practical implications. European Journal of Information Systems, 18(4), 317–331.
71.
PowellF. D. (1987). Study of a software development process dynamic model (Technical Report MTR 10314). Bedford, MA: Mitre Corporation.
72.
RahmandadH.StermanJ. D. (2012). Reporting guidelines for simulation-based research in social sciences. System Dynamics Review, 28(4), 396–411.
73.
RameshB.MohanK.CaoL. (2012). Ambidexterity in agile distributed development: An empirical investigation. Information Systems Research, 24(2), 323–339.
74.
RepenningN. P.GoncalvesP.BlackL. J. (2001). Systems dynamics—Past the tipping point: The persistence of firefighting in product development. California Management Review, 43(4), 44–63.
75.
RepenningN. P.StermanJ. D. (2002). Capability traps and self-confirming attribution errors in the dynamics of process improvements. Administrative Science Quarterly, 47, 265–295.
76.
RossoB. D. (2014). Creativity and constraints: Exploring the role of constraints in the creative processes of research and development teams. Organization Studies, 35(4), 551–585.
77.
SarkerS.SarkerS. (2009). Exploring agility in distributed information systems development teams: An interpretive study in an offshoring context. Information Systems Research, 20(3), 440–461.
78.
SchatzB.AbdelshafiI. (2005). Primavera gets agile: A successful transition to agile development. IEEE Software, 22(3), 36–42.
79.
SchaufeliW.BakkerA.Van RhenenW. (2009). How changes in job demands and resources predict burnout, work engagement, and sickness absenteeism. Journal of Organizational Behavior, 30(7), 893–917.
80.
SeersA.WoodruffS. (1997). Temporal pacing in task forces: Group development or deadline pressure. Journal of Management, 23(2), 169–187.
81.
SenguptaK.Abdel-HamidT. K. (1993). Alternative conceptions of feedback in dynamic decision environments: An experimental investigation. Management Science, 39(4), 411–428.
82.
SenguptaK.Abdel-HamidT. K. (1996). The impact of unreliable information on the management of software projects: A dynamic decision perspective. IEEE Transactions on Systems, Man, and Cybernetics, 26(2), 177–189.
83.
SenguptaK.Abdel-HamidT. K.Van WassenhoveL. (2008). The experience trap. Harvard Business Review, 86(2), 94–102.
84.
SeshadriS.ShapiraZ. (2001). Managerial allocation of time and effort: The effects of interruptions. Management Science, 47(5), 647–662.
85.
StermanJ. D. (2000). Business dynamics—Systems thinking and modeling for a complex world. Boston, MA: Irwin McGraw-Hill.
86.
TatikondaM. V.RosenthalS. R. (2000). Successful execution of product development projects: Balancing firmness and flexibility in the innovation process. Journal of Operations Management, 18(4), 401–425.
87.
ThalerR. H. (1999). Mental accounting matters. Journal of Behavioral Decision Making, 12(3), 183–206.
88.
ThomkeS. H. (1998). Managing experimentation in the design of new products. Management Science, 44(6), 743–762.
89.
van OorschotK. E.BertrandJ. W. M.RutteC. G. (2005). Field studies into the dynamics of product development tasks. International Journal of Operations and Production Management, 25(8), 720–739.
90.
van OorschotK. E.SenguptaK.AkkermansH.Van WassenhoveL. (2010). Get fat fast: Surviving stage-gates in NPD. Journal of Product Innovation Management, 27(6), 828–839.
91.
VigdenR.WangX. (2009). Coevolving systems and the organization of agile software development. Information Systems Research, 20(3), 355–376.
92.
WickensC. D. (1984). Processing resources in attention. In ParasuramanR.DaviesD. R. (Eds.), Varieties of attention. Orlando, FL: Academic Press.
93.
WiersmaE. (2007). Conditions that shape the learning curve: Factors that increase the ability and opportunity to learn. Management Science, 53(12), 1903–1915.
94.
WuY.RamachandranK.KrishnanV. (2014). Managing cost salience and procrastination in projects: Compensation and team composition. Production and Operations Management, 23(8), 1299–1311.
95.
ZelkowitzM.WallaceD.BinkleyD. (2003). Experimental validation of new software technology. In JuristoN.MorenoA. (Eds.), Lecture notes on empirical software engineering (pp. 229–263). Singapore: World Scientific Publishing.
96.
Zellmer-BruhnM. E. (2003). Interruptive events and team knowledge acquisition. Management Science, 49(4), 514–528.
