Fundamentals of Software Startups

In recent years, there has been an explosion of interest in entrepreneurship from both practical entrepreneurs and researchers. While theories are helpful for explaining business-driven activities in a startup, they are also valid in reasoning for the practical activities occurring in the entrepreneurial context. We believe that startups would benefit from the awareness of these entrepreneurial theories and the understanding of how they can be connected to decision-making in both business and engineering perspectives. In particular, we want to focus on theories that are already used by practical entrepreneurs and their advisors. As an example, we have studied the Scandinavian entrepreneurial ecosystem. We selected six groups of theories that might be particularly relevant for the startup population, namely (1) core competence and resource-based view, (2) effectuation, (3) the fulfillment of entrepreneurial opportunities, (4) bricolage, (5) business model innovation, and (6) lean startup. In this chapter, we explain these theories including the ongoing research around them, the connections among these theories, and how they can be applied in a real case study.

To be able to handle intense time pressure and survive in dynamic markets, software startups make critical decision constantly on whether to change directions or stay on chosen path. This is known as to pivot or to persevere in terms of lean startup. Pivot is an essential and crucial activity for software startups to initially survive, and then grow and eventually obtain a sustainable business model. We find several examples of software startups (Twitter, Instagram, etc.) that successfully pivoted during their entrepreneurial journey and became successful software companies. There is a lack of empirical evidences on why and how software startups make pivots. This chapter provides reader a better understanding on pivots, different types of pivots, and factors that trigger pivots. We employ case study and case survey methods. The results show that customer need, customer segment, product zoom-in, and technology pivots are the major types of pivots software startups have made. We also identify several new pivot types including market zoom-in, market zoom-out, complete, and side project pivots. Negative customer reaction and flawed business model are the prominent factors triggering pivots. The findings provide practical knowledge to software startups and practitioners, which they can utilize to better understand and perform pivots.

Startup companies are based on the founders’ innovations and visions of new business opportunities. Software startups are commonly considered as especially innovative. Besides the importance of the innovation and business vision, in the early stages of the startup, the initial team plays a key role in transforming the innovation into a product or a service. At the same time, software startups are often small, immature companies with very limited resources. That highlights the importance of the initial team’s capabilities to address the challenges of product development from the innovation—the knowledge, experiences, skills, and other cognitive abilities. In this chapter, we present the results of studies on the initial team’s capabilities from the viewpoint of the product development, planning, designing, implementing, and verifying the targeted product or service. The studies were conducted on a group of 13 software startups in Italy, Norway, and Finland. The studies revealed that from a group of very heterogeneous software startups a generic structure of the initial team could be identified, consisting of three different roles, each having a specific set of responsibilities and capability needs. This team structure provides a software startup with a balance between the team’s capabilities and problems and challenges to be solved during the early product development process. In addition, we present the sources of the needed capabilities, the initial knowledge, experience, and skills of the founder, and broadening and deepening the initial capabilities by validated learning and by growth toward the identified team structure.

The software startups are a particular scenario where Technical Debt (TD) may occur in an intentional or unintentional way. However, the current knowledge about the perception and management of TD are mainly related to mature software organizations. This chapter contextualizes the startups’ characteristics that can lead to TD incurrence, the concepts related to TD and its management, and presents the results of a survey with Uruguayan software startups. The survey’s primary goal was to understand how software startups perceive and manage TD in their projects. The results refer to the level of understanding of the startup’s practitioners concerning TD concept, the adopted Technical Debt Management (TDM) activities, and the strategies and technologies used in their projects to support such activities. The findings show that startups seem to invest time and effort in TDM activities being TD prevention, one of the most conducted activities. Besides that, it was observed that the participant’s experience and the size of the organization seem to be also related to the perception and management of TD.

For early-stage high-tech startups, Minimum Viable Products are the most important artifacts for both business development and product development. In an entrepreneurial journey with build–measure–learn loops, startups need to be certain about what they learn to be closer to a product–market fit. Grounded from insights of 40 active digital startups, we proposed the 6W3H framework that captures a comprehensive set of context factors for developing an MVP. The framework represents an effectual MVP development with the relationships among the existing competence (Who question), business ideas (Why question) and current customers (For Whom questions), MVP’s features (What to build question), Startup metrics (What to measure question), and the development processes and practices (How questions). We demonstrate how 6W3H framework can be used for visualizing startup development, supporting decision-making, and mitigating product risks. The benefits of using the framework are highlighted when MVPs associating with significant uncertainty and fast-changing requirements and team resources.

Software startups need to work in a systematic fashion just like mature organizations. However, existing software engineering methods and practices are not aimed at software startups. They do not account for the business aspect of startups and may not be well suited for software startups in general. The Lean Startup Methodology on the other hand contains some useful practices for software startups but is nonetheless impractical, offering little in the way of telling you what to do. Software startups are thus required to tailor their own method. Currently, many software startups simply work ad hoc or use various Agile methods and practices. In terms of Agile methods and practices, little consensus exists between startups. In this chapter, we discuss methods and method tailoring. We give guidelines on how to create your own way of working and recommend a tangible tool for doing so: the Essence Theory of Software Engineering.

Metrics can be used by firms to make more objective decisions based on data. Software startups in particular are characterized by the uncertain or even chaotic nature of the contexts in which they operate. Using data in the form of metrics can help software startups to make the right decisions amid uncertainty and limited resources. However, whereas conventional business metrics and software metrics have been studied in the past, metrics in the specific context of software startups have not been studied. In this chapter, we present the results of a multivocal literature review to offer you 118 metrics practitioner experts think software startups should measure. These metrics can give you ideas for what your startup should measure.

Software startups have a low probability of success. In their early-stage days, they face several challenges from different types that make it even harder to progress to the following stages. Some papers in the scientific literature focused on understanding these challenges. Meanwhile, others proposed solutions to these problems. In this chapter, we present a literature review of the challenges and patterns displayed in the scientific literature. Challenges are divided into four categories: related to product, market, finance, and team. The patterns presented in this chapter are (1) Get help from the methodologies, (2) Acquire customers, (3) Hack money incomes and outcomes, (4) Use available and simple tools, (5) Go up to the cloud, (6) Find your mentors, (7) Long-term purpose instead of money, and (8) Networking. We also show how the presented patterns could be used to tackle the identified challenges.

This chapter aims to explore supporting factors, such as incubators, accelerators, co-working spaces, mentors, and events in the startup ecosystem. To understand these five aspects and to explore their roles in startups, we investigated an Oulu startup ecosystem. In this case study, we conducted research interviews with practitioners working with startups, accelerators, incubators, venture capital firms, and co-working space organizations. By using real case examples, the results discussed in this chapter can help entrepreneurs understand the commonalities and differences between incubators and accelerators, their types (university-based or profit/nonprofit), the kinds of business ideas, and the entrepreneurs they focus on. Furthermore, the roles of co-working spaces, mentors, and events and their effects on entrepreneurs and startups are discussed. At the end of the chapter, we also show the interrelationships between these five aspects in the Oulu startup ecosystem and their influence on different startup development stages.

Coworking spaces and open innovation are two trends that emerged in the early 2000s and have gained considerable attention. Although there exists a vast amount of research on either of these topics, the connection between them has not been much explored. The aim of this research study was to assess the state of practice of open innovation in coworking spaces and to propose a model that captures this phenomenon. Empirical data were collected by surveys and interviews with seven entrepreneurs operating Norwegian coworking spaces and two managers of coworking spaces. We found that coworking spaces express a large potential to foster open innovation among early-stage startups. Also, open innovation was found to already occur in coworking spaces: Among the four coworking space dimensions analyzed—places, spaces, events, and projects—events were regarded as the most important ones, since they act as enablers for cooperation dynamics.

A healthy startup ecosystem, an environment with a well-balanced variety of agents and supporting processes, is crucial for the development of innovative startups. However, not all startup ecosystems are equally developed, and it is difficult to have all the elements of a startup ecosystem in advanced and prolific states, especially due to the fact that startup ecosystems are dynamic and evolve over time. In this chapter, we present a maturity model for startup ecosystems, which is built upon an analysis of three major startup ecosystems—Tel Aviv, São Paulo, and New York. We also present the visualization of the maturity model enabled by a web-based application that provides a user-friendly graphical representation of the maturity of a startup ecosystem. The chapter demonstrates that the maturity model, aided by the proper visualization, can serve as a basis for stakeholders in a startup ecosystem to analyze their environment, identify weak spots, and propose policies and practical actions to improve their ecosystem over time.

Software startups are currently very popular in Thailand, and existing information reveals an increase in the number of participants and investors in software startup businesses. Moreover, widespread events have been held to showcase the products and services these businesses have contributed. Software startups primarily develop innovations in the form of software produced from limited resources within a limited time. This software must be able to contribute to a sustainable business, and must be adjustable to each business size. Previous research indicates that both attention and emphasis must be placed on the importance of studying software startups in the form of empirical research. This will assist decision-making for those who are interested in initiating software startups and those who want to support them. Research has scarcely studied software startups in Thailand, and therefore, we are interested in Thai startups’ current situation as well as the startup ecosystem. This study clarifies that software startups in Thailand are defined as newly emerging businesses anticipated to help businesses grow quickly. Each software startup is in search of a different business model, as current software startups in Thailand have been created to help and support particular businesses. However, software startups rarely invent their own unique, exotic business models or apply advanced technologies and research in their startups.

New software startups are born every day around the globe. Dropbox and Netflix are examples of successful startups. However, failure is the fate of most of them. Several facts, such as market competition or lack of resources, can impact the destiny of a startup. Nonetheless, little has been explored in terms of the impact of software startup education on the success or failure of startups. Even though universities are adapting their curriculum in order to embrace such important subject, the challenge relies on how to provide real-world experiences for students to develop relevant startups. Hence, this chapter intends to present the main contributions, initiatives, and lessons learned found in the literature regarding software startup education.

Entrepreneurship education varies from theoretical courses that take a “teacher-centered” perspective to more hands-on, “learning by doing” ones that put students to the center of the attention and engage them in acquiring entrepreneurship competencies through experience. In this chapter, we present our experience of teaching the Lean Startup methodology to university students from diversified academic background. Rather than describing our teaching experience in the past years as a whole, we focus on a particular interesting part of our experience, which is, while we teach students Lean Startup and guide them to work on real startup projects during the course, we were also developing our own startup idea related to the course—Startuppuccino, a startup education platform to support active entrepreneurial learning. Through this unique experience, we reflect on how to better organize the course and enhance the active learning of the students using a supportive platform.

To compete in this age of disruption, large and established organizations cannot rely on the traditional way of advancement, which focuses on cost efficiency, lead time reduction, or quality improvement. They are now looking for new ways to innovate like startups. With greater resource in-house, they hope that they can bring innovative products to market with new customer value as startups do. Along with it, the awareness and adoption of the Lean startup approach have grown rapidly amongst large and established organizations in recent years. While Lean startup method is originated from the software startup community, the core ideas behind Lean startup can offer benefits for large companies as well. If the obstacles can be minimized, the opportunities can be very beneficial to leverage software product innovation. This chapter illustrates some of the typical challenges that were met during real-world new Lean internal startups, and how they were solved.

Marketing is a vital activity for software startups as they seek high growth. A specific type of digital marketing, growth hacking, in particular has attracted a lot of attention in software startups. Growth hacking is about utilizing low-cost marketing practices and existing platforms to rapidly increase the user count of a service. Though topics related to growth hacking such as marketing on a general level have been extensively studied in the past, growth hacking has not seen much direct interest in the academia thus far. As a result, we currently have few tools to teach growth hacking in startup education. In this chapter, we present two board games intended to serve as an introduction to growth hacking.

Hardware startups, i.e., wearable devices, robotics, and Internet of Things, are a significant sector of technology startups, in which software development is relevant and needed. Compared to pure software startups, hardware development in startup contexts lacks a systematic approach and guidelines. This chapter describes an empirical model that captures common elements in product development approaches among many hardware startups. Grounded from insights of 18 active hardware startups, we constructed a trilateral model of resource, speed, and quality in early-stage product development. For startups with relevant contexts, the work suggests the preparation of internal, external resources, and good practices of prototyping and matching prototypes to business activities.

This chapter presents a postmortem analysis of the collapse of a Latvian enterprise software company Clusterpoint that attempted to enter the global market with a Cloud-based database-as-a-service (DBaaS) offering to compete with MongoDB and other vendors in the NoSQL database category. The beginning of Clusterpoint is dated back to 2006 when three co-founders established the Clusterpoint Ltd. Company in Riga, Latvia. Clusterpoint developed its proprietary, closed source Clusterpoint database software and sold it in the local Latvian market using traditional enterprise licensing model. In 2015, Clusterpoint used more than 2 million EUR for launching its Cloud-based DBaaS offering and entering primarily the US market. In 2016, it was recognized by market research agency Gartner as one of Cool Vendors in platform-as-a-service (PaaS) segment. However, by the end of 2017 the company was unable to attract another investment round for financing its operations and was forced to file for insolvency due to liquidity issues. Research results suggest that the main reason for company collapse was related to the inabilitytoachieve product/market fit due to the lack of Clusterpoint integration with the major Cloud infrastructure vendors (Amazon WS, Microsoft Azure, etc.) and its focus on closed-source business model. The effect of these two factors was amplified by premature scaling. The authors use the research method of an empirical case study and postmortem analysis approach, analyzing the outcome in the retrospect (doing the “research-in-the-past”) of a completed project. One of the co-authors has worked as an employee at Clusterpoint during from February 2015 till March 2016.

Startups in Russia have a very low survival rate. The main sources of failure are financial and managerial mistakes, as well as the influence of external factors. The purpose of this study was to find out what are the triggers of business success for startups that have passed acceleration programs and survived for 3 years since their launch. We present the results of the case study, which were realized through a qualitative methodology framework. The target population of the study was three owners of startups that participated in acceleration programs and whose startups continued to generate income. The startups researched were located in three cities of Russia: Moscow, St. Petersburg, and Tomsk. We relied on Raheem and Akhuemonkhan’s theory of enterprise development as the conceptual framework of our study. Data collection included semi-structured interviews, review and analysis of company documents, reflective journal entries, and direct observation of the business processes in the startups. We analyzed the data using Yin’s five-step data analysis process. Data analysis revealed four important themes: the evolution of the entrepreneur, sales strategy, the impact of the acceleration program, and recommendations for accelerators and incubators. Interpretation of the research results can contribute to the survivability of startups in Russia, as well as the development of new successful experiences among entrepreneurs. For those people who are intending to start a business, this research outlines the skills that are necessary to launch a startup.

Brazil is consolidating itself in the world of software startups, both by the strength of the market and by the innovation ecosystems that help these new companies to start and grow. In this chapter, we present the technical challenges that these software startups encounter. We share our experience at Tecnopuc, one specificSTP located in the south of Brazil, with more than 170 organizations, from which 90 are startups. We present a set of technical challenges that relate to the following steps in developing an MVP: requirements engineering, product prototyping, architectural design, and software testing. Based on the analysis of these challenges, we reflect on how innovation ecosystems such as science and technology parks (STP) could help startups on addressing the challenges identified.