Successes and failures in software development project management: a systematic literature review

Abstract

Project management is a social construction and must be analyzed from the objective and subjective world. The high failure rate of software development projects, even with the evidence of a thorough knowledge of the factors, require a change of paradigm. Planning, execution and control is only efective in conditions of predictability and certainty and this sequence must give way to experimentation and collaborative learning and a co-creation that allows to make perception and mental models evident. This requires a framework that allows co-creating the content to be adequately represented in the decision-making process. Scripts conform a structure that makes thought visible, allows structuring the subjective and transforming it with a common objective. The nature of risks changes and understanding human behavior is key. Through communication, cognitive processes are put into perspective, modifying individual intelligences and institutionalizing the capabilities needed to achieve success. The black box is opened and project managers must pull back the veil of security based on a risk analysis resulting from lessons learned. They must modify their own mental models and dare to innovate and create successful projects with the knowledge of existing capabilities and co-creating those necessary for action

Keywords

• eol>Knowledge Management
• Co-creation
• Project Management
• Software Development

1. Introduction

Project Management Institute [1] defines project as a temporary efort that is undertaken to create unique results. Project management is the framework, functions and processes that guide the activities [2]. Software is an intangible product [3] and, from a management perspective, involves planning, monitoring and control, processes and actions that occur as the software evolves [4]. Avoiding failure involves understanding the crucial factors that lead to good project management and developing a common sense approach [4]. The traditional approach focuses on planning, execution and control which is inefective due to the instability and unpredictability of system changes [5]. Project management is a social construct that if looked inwardly pretending to deliver on time, within budget and scope, would not be contemplating the delivery of successful projects due to the adaptation deficit to the operational and social context [6]. It should be seen as a temporary organization that is motivated by the need to perform specific actions to achieve immediate goals [ 7]. It is made up of a group of individuals who temporarily enact a common cause, with expectations it become into action and learning, the great challenge being the preservation of this after the project [8].

Success and failure factors are some of the best indicators of lessons learned, adapted and used by the software industry as a method to help managers determine what information is most relevant to achieve their goals [9] and they represent the probability of increasing or decreasing the result [3]. Criteria are the variables that allow to evaluate and compare projects distinguishing between hard (cost, time, scope/quality) and soft (customer satisfaction) [3]. Three theoretical perspectives are evident when analyzing success and failure in management: rationalist, process and narrative [10].

A rationalist that although it contributes to a better understanding of the nature and management of projects focuses on the failure of the previously specified compliance and the social and narrative construction that as a complement to the previous ones focuses on subjectivity [10]. Its objective is to help managers in practice, it is expected that paying attention to the factors will increase the probability of avoiding failure [10]. McConnell [11, 12] evaluates the practices frequently chosen in the management of software development projects leading to results so predictable and bad that they deserve to be called Classic Mistakes. Nelson [13] takes up this concept and through a retrospective analysis of lessons learned identifies best practices. In the same way, the research industry, represented by the Standish Group, has published since 1994 the Chaos Report [14]. These studies reveal percentages of successful projects and frequent failure factors in software development projects. They are references used in both academic and professional environments. Authors such as [15, 16, 17, 18] take the results as a starting point in their research, even taking into account objections from authors such as [19, 20, 21] who question their results by showing biases and methodological issues. This perspective is criticized for providing a simple and linear cause-efect model causing a lack of understanding of complex and ambiguous phenomena [10], however, they provide the “what” in many research projects.

The process perspective avoids the black box by understanding that projects are shaped by emergent, dynamic, political and social relationships [10]. It suggests adjusting procedures when they become flawed. The Guide [ 1] accounts for the complicated and describes processes by identifying at the beginning of the project the objectives, required investment, financial and qualitative criteria for success. Progress through the life cycle allows the results to be compared with the specified objectives and criteria, providing the basis for measuring success [ 1]. This traditional project management perspective predefines the way of doing things and provides tools to resolve conflicts. It identifies the “how” and “when”. However, it provides a somewhat biased view from the praxis because it focuses on what should be and often leaves aside what is [22].

There is a very pragmatic desire by project teams to understand the lived experience in order to deal with complexity and uncertainty [23]. Researchers and research subjects will cooperate in interpretation [24, 25]. Verbalization, as the process of data collection, allows important aspects of praxis such as social responsibility, judgment, emotions, the functioning of dominant discourses, the potential relationship between knowledge and practical wisdom to be addressed together. It ofers more coherent theoretical concepts of the complexity related to communication processes, power relations and the ambiguity of performance criteria over time. It evidences the practice of project management as a collaborative learning process.

By adding the discursive layer, the subjective is emphasized, providing a constructive and social narrative perspective on failure. The discursive interpretive and political nature of project evaluation is centered among the daily interactions constructing reality [10]. Through this perspective, a deeper understanding of how meaning-making and interpretive processes in diferent social and political contexts contribute to the success and failure of projects is built by adding the why to the research.

All these perspectives imply a productive management paradigm based on planning, execution and control. The “what” is identified, the “how” is analyzed, the “when” is analyzed, and the “why” is constructed, reflecting the conclusions in lessons learned. However, constructing a postmortem reality can be valid for complicated projects with predictable outcomes. Proper planning and risk analysis based on past experience may contribute to success, but may be evidence of a high failure rate. This clear limitation could be justified in the unique and changing reality of software development projects where the social process, value creation and the importance of understanding lived experiences form in itself complex systems understood as the inability to predict behavior [26]. Most complex projects consist of ambiguity and uncertainty, interdependence, nonlinearity, unique local conditions, autonomy, emergent behaviors, and unfixed boundaries [ 27]. All interrelated parts can change and evolve with respect to the objectives leaving success associated with the complexity paradigm [28]. Managers applying models based on the execution of practical guidelines should verify the stability conditions of the production systems because they could be inappropriate preventing the management model from detecting an error in the production systems [28].

Knowledge is a dynamic process of personal justification of beliefs towards truth [ 29]. If it is explicit, it has a universal character, supporting the ability to act in diferent contexts, it is accessible through consciousness [30]. The tacit is related to the senses, skills, intuition, unarticulated mental models and is rooted in action, routines, ideals, values and emotions [31]. Thus, the diferent knowledge interacts with each other within the spiral of creation [ 29]. This interaction motivates action, requiring the integration of knowledge management into management so that positive feedback occurs during the project and not after its completion [32].

The Standish Group [14, 33], McConnell [11, 12] and literature reviews [34] based on the identification and grouping of factors in several dimensional axes, form the starting point. But projects are crossed by the ambiguity of human relationships, the dynamics of the environment that influences in a complex way and the limitation in the availability of resources [ 35]. There is a need to broaden the understanding of complexity as a subjective notion, reflecting the lived experiences of the people involved [36]. To create knowledge, skills shared with others need to be internalized, reformulated, enriched, and translated to fit the new identity [ 37]. Perception, intuition and hunches as a subjective part have to be incorporated into the hierarchy and as a fundamental link in predicting the possible outcome in the inter-exchange of ideas about the problem at hand. The key to achieve the institutionalization of knowledge is to change the project management paradigm and couple it to the knowledge management system. Creating new knowledge literally means recreating the organization [37] or creating it in the case of temporary organizations. Opening the black box [38] and showing success or failure as an antagonistic construction process of interrelated factors is the complex path to follow, putting the narrative at the center of the scene.

2. Method

Evidence-based software engineering [39] provides the means by which research can be integrated with practical experience and human values in the decision making process [21]. Systematic literature review (SLR) not only succeeds in identifying all existing evidence on a question, but also provides software engineering solutions [39]. If during the examination of a domain, it is discovered that the problem is broader then systematic mapping is the most appropriate by broadening the search to a not so narrow focus [40]. Systematic mapping is proposed to identify evidence of factors conditioning success and failure in a domain at a high level of granularity [40]. The proposed procedure includes tasks associated with planning (generation of research questions, definition of the search string, period, specification of the engines, inclusion, exclusion, quality, data extraction and accounting strategies), execution (search, selection according to established criteria and extraction of data in templates) and presentation of results once a significant sample has been obtained.

In order to determine the factors that condition success and failure in software development projects and to identify emerging elements that allow institutionalizing knowledge for decision making, the following questions are proposed: • Q1. What criteria do the authors identify as indicators of success and failure in software development projects and what factors condition them? • Q2. What diferences or similarities exist between the success and failure criteria and factors identified in the literature in the last four years (2017-2020) and those specified by McConnell (1996-2008) or the Chaos Report published annually (1994-2015) by Standish Group? • Q3. What are the emerging elements that emerge from relevant research for the approach of a software development project management framework?

It specifies the search strings, the engines to be used in a period between January 2017 and June 2020.

• Search string: "Success factors in software development projects". "Failure factors in software development projects". "Factores de fracaso en proyectos de desarrollo de software". "Factores de éxito en proyectos de desarrollo de software".

Success+factors+failure+project+software Exito+fracaso+factores+proyecto+software Success+failure+Projects+management+software+development

Exito+fracaso+proyecto+administración+software+desarrollo • Search engines: ACM Digital Library, Emeral, GoogleScholar, IEEE Xplore, IGI-Global, Redalyc, Scielo, ScienceDirect and Taylor&Francis. The following inclusion, exclusion and quality criteria are specified: • Inclusion: Primary and secondary studies written in Spanish or English, reported in national or international congresses and scientific journals available in any of the speciifed sources and that include any key words Success+failure+project+software/SI in the abstract or in the text, in the specified search period 2017-2020. • Exclusion: Repeated articles, studies that do not meet the inclusion criteria or not having access to the entire content. • Quality: Objectives clearly defined and aimed at achieving them and variables clearly measured.

In order to data extraction and accounting strategies, a template is prepared for the extraction of general data, context of the studies (circumstance of software development), purpose (objectives that the researchers intend to achieve), contribution (contribution made) and relevant characteristics (criteria and success and failure factors grouped by dimensions or axes on which they have an impact).

3. Systematic Literature Review

In accordance with the process formalized in the planning, the selection of articles and continuous iteration is carried out until a significant sample of 179 (147 primary and 32 secondary) is obtained. The sample of secondary studies is maintained as background and validation of the data collected. Hereafter, the results are expressed by indicating characteristic (X1, X2), where X1 is the number corresponding to primary studies and X2 is the number corresponding to secondary studies.

The following articles were found in GoogleScholar ( 40,13 ), ScienceDirect ( 38,7 ), IEEEXplore ( 30,7 ), Taylor&Francis ( 11,0 ), Emeral ( 3,2 ), IGI-Global ( 8,1 ), ACM Digital Library ( 5,1 ), Scielo ( 4,1 ) and Redalyc ( 2,0 ). The distribution by year is uniform 2017 ( 45,14 ), 2018 (34.4), 2019 ( 47,10 ) and up to June 2020 ( 11,4 ). The strategies used by the authors are mainly mixed ( 76,15 ), qualitative ( 38,17 ) and quantitative ( 0,38 ).

Many of the studies are developed in the context of a specific methodology, others base their research on any methodological context, extending their conclusions. From the sample were obtained in agile contexts ( 24,1 ) identifying as characteristics the free flow of communication, organic structure [41], continuous progress and interaction [42], coordination with direct influence on productivity [43], use of tacit knowledge avoiding heavy documentation [44], savings and elimination of bureaucracy [45]. In traditional contexts ( 1,0 ) identifying the plan-based approach, clearly specified requirements, satisfaction or not of the final product [ 46]. Most of the articles are not developed in a specific context, also contemplating hybrid contexts, indistinct ( 80,17 ). Open-source development (1.0) with its collaborative nature, available source code [47] low cost of construction and deployment and global software context ( 5,3 ) with lower cost of skilled resources, fast delivery with its challenges in communication, coordination, control by geographical, socio-cultural, temporal and organizational distances [48], technological and process [49] and trust as a critical factor [50] starts to emerge among the researches. Project portfolios ( 6,1 ) with their individual characteristics of interdependencies and massive consequences of failure [51] as well as their complex, unique, temporal and uncertain components [52] require alignment and eficiency [ 53] with small, focused and less dispersed teams [16] recognizing agile capabilities as emerging strategies in uncertain environments [54]. Complex contexts ( 3,5 ) are dificult to understand, foresee and keep under control behavior [ 55] however, there is great dificulty in distinguishing complex from complicated projects [ 56], the authors identify interacting components of uncertainty, ambiguity and interdependence [57]. Developments in process improvement contexts (4.1) contemplate developments including a series of tasks such as process scoping, evaluation, design, realization and continuous improvement [58], seek to contribute and increase the performance and usefulness of processes [59] emerging through agility new models that contemplate continuous learning [58]. Large-scale developments ( 9,3 ) are characteristic of a high cost and the intervention of many people with a long duration, this implies a high collective efort made by multiple developers [ 50]. Not many studies were identified in the context of SMEs (1.0) even though they continue to be the driving force of the economy of many countries. Among the characteristics observed, they identify the need to focus on requirements, customer expectations, progressive planning, monitoring, control through a clear definition of scope and the use of management methodologies [ 60]. App development ( 1,0 ) is mentioned for a particular characteristic of interaction with users which allows them to implement changes that are then rewarded [61]. The public sector is a particular context (4.1) due to its complexity and the need for eficient and efective management [ 62]. And the academic environment ( 8,0 ) corresponds to a controlled environment [63] with students using scrum methodology or [64] with survey identifying best practices and management support are important for the success of the project.

Among the diferent purposes it was identified: • Report an experience ( 80,0 );[65] show how is the agile process in the current software industry. • Synthesize the available evidence ( 0, 22 ) as [66] that review the literature of the last 25 years identifying 142 success factors in technology projects triangulating with a survey to determine the impact that each one has on the success of the project. • Propose ( 28, 9 ) such as [67] suggesting a new parameter favoring a holistic approach to measure projects in contrast to the traditional view or [68] proposing a hybrid approach. • Validate ( 30,1 ) giving firmness to a statement as [ 69] that identify emotional intelligence as the main contributor to the challenges of management under agile methodologies. • Evaluate ( 5,0 ) as [70] that determine the correlation between quality, time and cost and give an opinion (4.0).

The main contribution is to the knowledge of factors conditioning success and failure and their possible correlations and is justified by the specified search string. Knowledge of determinants ( 109,23 ) [71, 72, 73], some frameworks ( 18,6 ) [74], metrics ( 3,0 ) [67, 75], models ( 9,1 ) [41, 49], methods ( 4,0 ) and tools ( 4,2 ) [76, 77].

There are several looks at defining success and failure criteria, most agree cost, time and quality as hard and stakeholder expectations as soft [3, 17] considering the subjective way of evaluating the project from the narrative [78] leaving perception in evidence [79]. Stakeholder theory contemplates a holistic approach [79] and conditions the starting point for embedding learning in the system. Performance looks at project performance [80] and within the hierarchy. A failed project does not necessarily indicate poor performance of its managers [81]. Economic profitability identifies that it may be promising during start-up and not be accepted in the market [3][3]. The criteria mentioned by the researchers cost ( 73,20 ), scope ( 66,14 ), time ( 73,91 ) continue to be the hard criteria for evaluating projects. To the same extent customer/user acceptance ( 70,11 ) as soft criteria. Performance ( 40,7 ) emerges as a criterion that seeks to establish both objective and subjective concepts when evaluating projects, with the economic and commercial proposal ( 3,1 ) being the least considered.

There is no agreement among researchers on the important and relevant dimensions when grouping factors that condition success and. The authors propose organization, environment, processes and people [74], teams and customers [9], technique [46], users and stakeholders considering communication at all levels as predictors of success [66], external environment [80] and financial [82].

It was decided to group the sample into 9 dimensions with their associated factors: • Organization ( 102,20 ): clear role definition ( 13,2 ), conflict resolution ( 27,4 ), coordination ( 37,7 ), change management/flexibility ( 45,12 ), open/mature communication ( 40,11 ), rewards ( 15,2 ), recognition ( 11,2 ), transparency ( 12,2 ), structural, organizational policies, alignment (12.2), ability to learn ( 30,7 ), ability to translate learning/give meaning ( 24,4 ), knowledge management ( 3,0 ), and good working environment ( 25,3 ). • Team ( 93,14 ): good relationship ( 11,1 ), trust ( 34,3 ), compatibility ( 4,1 ), adequate expertise ( 41,6 ), good communication ( 40,3 ), cooperation ( 38,6 ), commitment ( 24,2 ), shared vision, shared experiences, exchange ( 20,1 ), autonomy/empowerment ( 16,0 ) and motivation ( 33,6 ). • Processes ( 78,20 ): planning ( 45,11 ), estimation ( 9,3 ), risk assessment ( 24,10 ), communication ( 25,6 ), follow-up ( 14,2 ), monitoring and control ( 25,9 ), documentation ( 11,7 ), choice of processes, development and training ( 34,8 ). • Technical ( 37,10 ): use of techniques and tools ( 9,1 ), incomplete/ambiguous requirements ( 20,7 ), experience and knowledge in the use of tools ( 7,3 ). • Personal ( 77, 20 ): management intelligence/management skills (52.10), social skills (4.4), emotional intelligence/self-control ( 11,5 ), business skills ( 12,2 ), political skills ( 3,1 ), decision making and leadership ( 16,7 ), technical knowledge ( 17,1 ), soft and cognitive skills ( 38,6 ). • Political/legal ( 39,13 ): lack of management commitment and support ( 33,12 ), lack of coordination with governments ( 7,4 ), underestimation of changing requirements ( 4,3 ), lack of communication with project management ( 2,0 ). • Financial ( 14,7 ): lack of money/financial/resources ( 16,7 ). • Third parties ( 67,12 ): perception of product quality ( 41,7 ), participation ( 29,5 ), collaboration ( 10,0 ), communication ( 10,1 ), trust ( 18,1 ), flexibility ( 2,0 ) and commitment ( 17,3 ). • Internal/external environments (48.14): complexity (37.14), uncertainty (26.7), ambiguity (11.5), independence/nonlinearity (8.2).

4. Result

Q1: What criteria do the authors identify as indicators of success and failure in software development projects and what factors condition them? A combination of hard and soft concepts is observed in equal proportion, giving rise to the performance criterion. The factors associated with the organizational dimension and the team are evidenced over the processes, emerging the personal dimension.

Q2: What diferences or similarities exist between the success and failure criteria and factors identified in the literature over the past four years (2017-2020) and those specified by McConnell (1996-2008) or the Chaos Report published annually (1994-2015) by Standish Group? Standish Group specifies user involvement, resource, planning and management support [ 14], includes emotional maturity and qualified resources as relevant [33][ 33]. These are still present in the research. Forty-two percent of the classic errors found by McConnell [12] correspond to those arising in systematic mapping. Planning, risk management, insuficient estimation, user involvement is at the top of the list. A very process-oriented focus evidencing the importance of user involvement and the conflicts associated with the same involvement. However, there is a clear tendency to study organizations as a complex system, focusing on communication that crosses all dimensions as the true causal link. Coordination and flexibility at the organizational level and management and emotional intelligence, giving importance to social and political skills as an emerging element, begin to have relevance not only in the relationship with the client or in the teams, but also as an element of the organization. The ability to learn from the organizations, the exchange and shared experiences of the teams raise the need to translate this learning into a shared vision.

Q3: What are the emerging elements that emerge from the research that are relevant to a framework for managing software development projects? Researchers have a much more complex view of software development projects than simple causal relationships. Analyzing the problem through dimensions highlights the interrelationship of factors. Authors such as [38] strive to highlight the complexity of the mechanisms involved by showing the importance of revealing the reality through integrated subjective and objective strategies. The dynamics of relationships and the visualization of systems as a complex interrelation of dimensions begins to be the objective of researchers with a common goal, productivity, but not anchored in a strict planning generated in the past, but with enough flexibility to visualize the living present. They begin to work on the perception of reality, reflected through discourse [ 43]. Others [44] model contingent proposals to solve a reality that always existed but seeing the factors as causal relationships only made the decision maker rest on structural biases created in the past without positioning himself in the present and analyzing the true context, ambiguous, uncertain and non-linear. Knowledge acquisition and transformation into meaningful learning through collaboration and social interaction seem to be the key. The co-creation of knowledge proposes to go beyond the exchange by creating processes that allow the evaluation and modification of collective ideas that lead to improve one’s own [ 83]. Allowing active participation in knowledge co-creation activities can lead to high quality learning outcomes [84]. One way to promote productive collaborative learning is the use of scripts that explicitly guide participants during their learning [84]. An intelligent collaborative system allows for improved learning and decision-making processes [85]. Content representation [86] is a key dimension of knowledge management [87]. The productive process changes the paradigm to make way for the modeling-experimentation-learning trinomial. Reality over prescription guides the way towards transformation, but it requires multiple views that allow the integration of objective, subjective and social worlds. This can be achieved through communicative action that allows confronting these worlds by adopting logical reasoning instead of domination to resolve disagreements [88]. Communicative action is the basis for change aimed at achieving, sustaining and revising consensus through human potential rooted in language and discourse analysis [89].

5. Conclusions and future lines of research

There is no common definition of complexity among researchers, but many agree on characteristics such as multiple interacting parts, uncertainty and social interactions that produce systemic risks that must be managed with a holistic view [90]. Changes in one component of the system can cause unforeseen events in others, making the project evolve, making it dynamic and unpredictable [91]. The institutionalized absorption capacity through the use of scripts allows the necessary competences to use the new knowledge [92].

Understanding human behavior in projects is the key to predicting the triggering efects of decision making. This requires institutionalizing emergent capabilities to absorb real complexity, adapt and recover quickly. It is key to understand the links between projects and institutions and how they trigger change and establish stabilizing mechanisms for long-term social interaction [93]. The theory of practicality can be useful in understanding aspects of human behavior [90] allowing for meaningful predictive tools [94]. It is important to view the social world as an emergent product of decisions, actions and cognitions. Cognitive operations depend on supporting processes in that reasoning and decision making depend on the availability of knowledge about situations, options for action, and outcomes [95]. Knowledge can be used to read and interpret the world [78] but its nature, value and perceived view of power in conjunction with diferent mindsets form key barriers to exchange not occurring [ 96]. Any team participation in projects is highly dependent on the quality of communication [88]. Communication barriers are an important part of human perception, thus shared social construction can ofer a way to address complexity as a whole by redefining the dimensions that are interrelated through decision making and co-creation of content to modify the mental models of the teams during the project and not after its completion.

The toolbox of reflexive sociology [ 94], the critique in terms of communicative action proposed by [88] and the spiral of knowledge creation [29] provide a solid structure that makes clear the social dynamics in the field of management. The choices we make are not inherent to the situations we are presented with but complex exchanges between the properties of the context and our properties, our doubts and our history [97]. The theory of multiple intelligences [98] proposes a framework for cognitive growth because we must go beyond the ability to see the world through mental representations, we must work with them, manipulate them and transform them. With the elements provided, a model could be formalized that contemplates the diferent scripts integrated in the spiraling of knowledge, promoting practices that allow co-creating and representing the content at key moments of the execution, creating intelligent temporal organizations. The construction implies training people who learn to see as systemic thinkers, who develop their own personal domain and who learn to reveal mental models in collaboration.

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