The role of MVP strategy in increasing company competitiveness in a fast-paced environment

The use of lean software development methodology and business model experimentation has become popular in software companies in recent years. Business model experimentation is used to validate assumptions made on a product from real customers before the actual product is created. A minimum viable product is used to test the business model by gathering and measuring customer feedback. However, in many cases creating a minimum viable product requires the development team to take shortcuts and workarounds in the product. This phenomenon in software development is called ‘technical debt’, where companies trade long-term software quality to short-term gain in time-to-market. We investigated four software companies and conducted nine interviews to understand the relationship between business model experimentation and technical debt. The goal was to study how business model experimentation is affecting to technical debt. The results showed that business model experimentation has a clear relationship to technical debt.KeywordsBusiness model experimentationTechnical debtCase studyStartup companyLarge companySoftware development lifecycleMinimum viable product

Learning outcomes To analyze the development of Indian Fintech Industry, the revenue, cost and risk drivers. To appreciate the concept of minimal viable product. To generate valuable data-driven insights from the user stories, voice of customer and competitor benchmarking for the creation of minimum viable product. To devise the Blue Ocean Strategy for the digital products. To develop the plan for the minimum viable product. Case overview/synopsis This case is about a fintech firm, Dinero, that was facing the dilemma of how to launch its investing app as a minimum viable product in the background of the original plan that was to launch the credit operations along with the investing operations. Now, with the newly-imposed regulatory constraints on the credit business, Dinero had to go ahead with the investing functionality only and had to decide upon the value proposition of the product from among several alternatives. Dinero also wanted to find out the ways for creating blue ocean strategies through value innovation and relook at the product design and launch a suitable minimum viable product (MVP). It also wanted to explore the alternatives for new uncontested markets through innovative differentiated products so that the competition could be made irrelevant. Therefore, it wanted to use in-depth consumer surveys and competitor product benchmarking to come up with a strong MVP that could help it capture the market. The study of the voice of customer could generate a lot of insights for Dinero to move forward. Complexity academic level This case is intended for teaching in the graduate studies programs in business, management, information systems and digital business to enable the students to appreciate the decision-making related to digital product management using the approaches such as voice of customer, minimum viable product, competitive benchmarking, breakthrough innovation and blue ocean strategy. This case can be used for teaching in the product management course and the strategy course. The case also be used in the fintech course, which is taught as an elective course to students specializing in the fintech domain. Supplementary material Teaching notes are available for educators only. Subject code CSS8: Marketing.

Model‐Based Systems Engineering (MBSE) is the growing practice of systems engineering (SE) in which descriptive models replace documents as the embodiment of SE knowledge. These descriptive models capture SE information in place of documents, are developed in a similar manner to software source code, and are encoded and used in machine‐to‐machine applications as data. This paper describes how the Technical Debt concept widely used in the software domain—rework deferred to the future for expediency—needs to be modified for the domain of descriptive models. Technical Debt is often associated with agile development practices of software or descriptive models, which emphasize the rapid creation and iterative evolution of a Minimum Viable Product (MVP). Consciously applying appropriate modeling principles and practices is essential to make informed decisions during the modeling process to prevent the accumulation of excessive model Technical Debt—particularly during this iterative evolutionary process—which can require substantial rework to correct. The paper establishes a foundation for characterizing the Technical Debt implications of key model architecture and implementation decisions that are made explicitly or implicitly by modelers when developing descriptive models. To illustrate the model Technical Debt concept, several examples of modeling principles pertaining to model purpose and implementation are described along with their implications on model Technical Debt.

Software startups are an essential source of innovation and software-intensive products. The need to understand product development in startups and to provide relevant support are highlighted in software research. While state-of-the-art literature reveals how startups develop their software, the reasons why they adopt these activities are underexplored. This study investigates the tactics behind software engineering (SE) activities by analyzing key engineering events during startup journeys. We explore how entrepreneurial mindsets may be associated with SE knowledge areas and with each startup case. Our theoretical foundation is based on causation and effectuation models. We conducted semi-structured interviews with 40 software startups. We used two-round open coding and thematic analysis to describe and identify entrepreneurial software development patterns. Additionally, we calculated an effectuation index for each startup case. We identified 621 events merged into 32 codes of entrepreneurial logic in SE from the sample. We found a systemic occurrence of the logic in all areas of SE activities. Minimum Viable Product (MVP), Technical Debt (TD), and Customer Involvement (CI) tend to be associated with effectual logic, while testing activities at different levels are associated with causal logic. The effectuation index revealed that startups are either effectuation-driven or mixed-logics-driven. Software startups fall into two types that differentiate between how traditional SE approaches may apply to them. Effectuation seems the most relevant and essential model for explaining and developing suitable SE practices for software startups.

The article solves the actual scientific task of optimizing the use of server resources of a military cluster system in the process of processing a large number of client requests. The setting of this scientific task is due to the need to eliminate the dependence of the efficiency indicators of the existing methods of balancing the load of cluster systems on the quality of training, as well as a rather narrow approach of the analyzed scientific studies to the study of the influence of the properties of verifiability, robustness and the guarantee of optimality on the final decision-making result. A study of existing approaches to the optimal use of cluster system resources was conducted. Based on the results of the analysis, methods based on the game-theoretic scientific-methodical apparatus were selected as the most appropriate approach to the formal description of the functional interaction of servers with client requests, as well as an approach that does not require the generalization of empirical experience (learning). A model of the optimal use of resources of the military cluster system is proposed, which is based on the hybridization of the application of the game-theoretic approach and the theory of fuzzy logic. The essence of the proposed model is to determine the necessity of decomposition of the received task into subtasks, initiated by the client request, by means of the theory of fuzzy logic with the aim of further finding the optimal distribution of the use of cluster system servers based on the Nash equilibrium, taking into account the generalizing indicator of the current level of their workload. The obtained results are considered as a basis for the implementation of new adaptive systems for balancing the load of nodes of the cluster system, the application of which allows optimal use of the resources of the cluster system of military purpose in a stable balance.

Founding a start-up entails numerous risks and uncertainties. To minimise these risks and to deal with uncertainties, the popular concepts of Effectuation and Lean Startup, among others, are discussed in entrepreneurship research. Although both concepts are not new, they have gained importance in recent years. Effectuation focuses on dealing with uncertainty and contrasts with causation, which focuses on planning. The starting point for Effectuation is the resources available to the founders, which leads to different business ideas. The core of Effectuation includes four key dimensions: available means, affordable losses, exploiting contingencies and building partnerships. Lean Startup can be understood as a framework for decision-making in which direct interaction takes priority over extensive planning. The approach is based on three fundamental principles: experimentation rather than planning, focus on customer feedback and iterative learning. The core elements include a clear entrepreneurial vision, close contact with the customer, the Build-Measure-Learn feedback loop and the Minimum Viable Product. The key dimensions of Effectuation and the core elements of Lean Startup also form the frame of reference for the empirical investigation. The article examines the extent to which these concepts are applied by Swiss entrepreneurs and whether a combination of the two takes place. The data comes from the business plans of 25 finalists of a Swiss innovation competition from 2022. The business plans are evaluated and analysed in a multi-stage process. The study provides insight into the behaviour of Swiss start-ups, whether they proceed according to Effectuation and apply the Lean Startup principles. Surprisingly, the study reveals that many start-ups proceed according to Effectuation, while relatively few start-ups apply the Lean Startup principles. We were able to show the extent to which the two approaches are used and how they relate to each other. We also found that the origin of the start-up (research-based or industry experience-based) plays a significant role.

This article is devoted to the analysis of marketing features of IT companies, particularly startups. The field of developing innovative and digital products is evolving rapidly, and marketing tools in this industry are constantly being updated. Key stages and factors influencing the creation of a startup's marketing strategy have been identified. A description of the startup's lifecycle is provided, along with examples of successful launches of innovative products. Definitions of the terms MVP (minimum viable product) and pivot and their significance for a startup's marketing strategy are formulated. Development strategies for startups are proposed based on different stages of the lifecycle. Marketing startups have their own peculiarities compared to marketing for more stable and well-established companies. Startups often have limited budgets and resources, which requires marketers to adopt a more creative and efficient approach. The differences in startup marketing compared to traditional marketing include explaining the essence of the innovative idea to the target audience; conducting marketing research for an idea that may not yet exist in a tangible form; developing marketing strategies based on the industry-specific nature of the product or the presence of invested capital; utilizing marketing tools according to the stages of the startup's lifecycle. The uniqueness of the startup lifecycle lies in the need to focus on executing a development plan at each stage to attract funding from investors and ensure successful company growth. If consumers show little interest in the product, the startup must change its strategy, completely revamp the concept, and make a pivot. MVP is a product development strategy where developers create a minimum viable product that allows them to test the hypothesis of its market success and receive feedback from the target audience. The proposed marketing strategies for startups are divided into three conditional categories: independent operation with minimized influence on management, acceleration for scaling, and revival of a failed launch; incubation of the startup with significant authority in financial and marketing policies transferred to business mentors, agents, or incubators.

The object of research is the corporate culture of dignity as an interdisciplinary determinant of organizational behavior that operates at the intersection of IT engineering, cognitive science, behavioral economics and knowledge management. The analytical focus is on the impact of cultural variables on cognitive distortions in strategic decision-making, as well as on the dynamics of technical and social debt in IT companies. The problem to be solved is the absence of a holistic cognitive-behavioral model that would describe the mechanisms of the transformative impact of a culture of dignity on organizational biases and structural inefficiencies in engineering systems. Existing approaches largely ignore the relationship between managerial ethics, team interaction architecture, and the cognitive ecology of decision-making. The research methodology included a critical analysis of theoretical sources, the development of the author's analytical model, and a content analysis of cases of three global technology companies (Spotify, Google, Airbnb). A qualitative analysis of corporate practices and the content of open reports revealed a strong correlation between a high level of transparency, autonomy, psychological safety and feedback in organizations with a strong culture of dignity and a reduction in the frequency of cognitive distortions and the pace of technical debt elimination. The data are the result of analytical generalization rather than empirical quantitative research. Estimates show that such organizations demonstrate an acceleration in the pace of technical debt reduction by 15–20% compared to those without established feedback practices. The practical significance of research lies in the possibility of using the results to develop organizational development policies, training programmes for IT team leaders, strategic management systems and technical debt audits. The findings contribute to the expansion of theoretical understanding of the role of humanistic factors in high-tech management and have the potential to implement the UN Sustainable Development Goals, in particular in terms of decent work, inclusive governance and innovation sustainability.

This paper (SPE 54447) was revised for publication from paper SPE 49182, prepared for the 1998 SPE Annual Technical Conference and Exhibition, New Orleans, 27–30 September. Original manuscript received 1 June 1998. This paper has not been peer reviewed. Summary This paper discusses the added value obtained in a joint business development (JBD) between an operator and a service company. The JBD is founded in a joint operations agreement that both parties formalized and signed in early 1996. This JBD is unique because of its structure; because of its systematic approach to improving quality and communication and to developing technology jointly to meet needs; and because of the resulting added value to both parties. The project was started in 1994 when the operator restructured its contract portfolio to achieve improved cost-efficiency and closer cooperation with suppliers and to reduce overall contract administration. This was to be done by both reducing the overall number of contractors and transferring increased responsibility to the service company. As a result of the contract award, a joint operations agreement that focused on extensive cooperation was formalized and signed by critical suppliers and joint organizational structures were put in place. For a cooperative business structure to succeed, the ability to measure progress is critical. As a result, initial focus was put on developing a novel measuring system, a "quality rating system" (QRS). This system, together with other nonconformity and health, safety, and environment (HSE) systems, is used by both parties to focus on quality and to optimize resource use. A system to identify gaps in behavior, communication, and expectations also was put in place. Once the measuring systems were operational, a large-scale cooperative survey was conducted that focused on both technological and cooperational improvement opportunities. The results of this survey were used to establish project-specific quality action teams with representatives from both parties. This way of working together has resulted in demonstrated improvements that have given the parties added value in several critical areas. The process is under continuous development, and, on the basis of experience to date, the parties are preparing to take appropriate elements of the JBD process to the international arena. Why JBD One of our industry's main challenges is to obtain increased oil and gas recovery through optimum use of available resources while maintaining high HSE standards. This challenge is especially critical in the North Sea because of very high operating and development costs. Close cooperation between all parties involved in a development project can create synergies that contribute to achieving this objective. In well construction, the service industry contributes up to 90% of the manpower and total cost. By developing close cooperation with selected suppliers, the operator can create efficiencies that provide value. Improved cooperation and the resulting quality normally result in a long-term business relationship that benefits both parties. The key to success lies in improving the use of resources through improved communication, a systematic approach to technology development, and improvement of quality. This has been achieved through joint management commitment and willingness of both parties to dedicate and re-evaluate resources to fulfill the objectives in the cooperation agreement. The foundation for this cooperative project was laid when the operator revised its contract philosophy. The aim was to obtain more efficient contracts and also to reduce the overall number of contracts and suppliers. The following are the five key drivers of the process.Centralization of contract administration, resulting in large tenders covering the entire scope of work across all fields.Long-term contracts, with a scope of 4 to 10 years.Close cooperation with select strategic suppliers.Ability to address technology needs.Volume discounts and total cost benefits. To position itself to handle the challenge, the supplier established new product lines of strategic importance. The supplier also focused strongly on capacity and capability to meet the operator's requirements. As a result, the supplier was awarded a major part of operator's work. Cooperation Strategies The company strategies were compared and good compatibility confirmed. The focus at this stage was on a long-term relationship, optimum use of resources, and willingness to invest in each other. Once the contract foundation was established, the parties started the process of establishing a common cooperation agreement. This was initiated through two workshops where senior management exchanged current and future technological and operational challenges and suggested solutions. The main focus areas identified were quality, technology development, organizational development, competency, and HSE. These areas formed the foundation for the cooperation agreement, which was signed by senior representatives from both companies. This cooperation agreement was used to build a bridge between the various contracts. After the agreement was signed, the mission statement, strategy, and initial goals were established and presented. (Figs. 1 through 4)

The knowledge about technical debt and its management has increased in recent years. The interest of academia and industry has generated many viewpoints on technical debt. Technical debt management consists of technical and organizational aspects, which make it a challenge in software development. To increase technical debt visibility and manageability, new processes must be developed and thoroughly empirically tested for their applicability. In this paper, we use the action research methodology to design processes for identification, documentation, and prioritization of technical debt. Our partner in this research is a large Nordic IT company Tieto, currently in a need for new ways to improve their technical debt management. The results include a set of processes and templates that were successfully used to identify and document technical debt. The identified technical debt items were later prioritized based on evaluation by Tieto employees. Tieto was able to create a prioritized technical debt backlog, which is now used for reduction activities to create a healthy and sustainable product for the future.

The Environmentally Friendly Drilling (EFD) program is taking a renewed look at dealing with the issue of waste management and re-use particularly with regards to produced water and water based drilling wastes, developing solutions that would possibly reduce the size of reserve pits needed in drilling operations and achieve significant waste volume reduction through the extraction of water from drilling wastes encouraging reuse of the extracted water in drilling operations and the concentration of suspended solids. The EFD is investigating the use of membrane-filtration technologies in the aforementioned aim of waste volume reduction and water extraction from drilling wastes. The investigation involves processing actual drilling wastes using various membrane types and configurations in developing solutions to challenges facing membranes particularly fouling. We are investigating the ability of these membranes to effectively remove the suspended solids from waste streams and refine the waste to levels where they could be used in drilling operations or sent for further treatment such as desalination. Our aim is to develop a mobile treatment unit made of a suitable membrane system that could be deployed to drilling sites to be used as an onsite option aimed at recycle or re-use of water resources. We are currently investigating in our laboratories various membrane-filtration technologies with water based oilfield wastes and coupling this with our prior development of field deployed technologies in developing a cost efficient membrane filtration system for field application. We show in this report how membranes have been used in the filtration of actual solids laden field supplied water based muds and a solids simulated laboratory water based mud, highlighting the compatibility of membrane systems with water based muds. In light of the evolving stringent regulatory standards and in demonstrating good stewardship of the environment, the Oil and Gas industry is expected to be active in reducing the footprint of its various activities on the environment and in showing optimal use of resources. This approach to dealing with drilling wastes confers the two-fold advantage of optimal use of water resources through re-cycle and the reduction of the footprint of drilling operations well within reasonable economic costs by saving significant waste treatment, hauling and freshwater costs.

Environmental Impact Assessment has gained a prominent position as a tool to evaluate the environmental effects of economic activities. However, all approaches proposed so far use a burden‐oriented logic. They concentrate on the different environmental impacts in order to ascertain the overall environmental damage caused by economic activity. This paper argues that such a burden‐oriented view is (a) hampered by a series of methodological shortcomings which hinders its widespread use in practice; and (b) is analytically incomplete. The paper proposes a value‐oriented approach to impact assessment. For this purpose an economic analysis of the optimal use of environmental and social resources is conducted from both a burden‐oriented and a value‐oriented standpoint. The basic logic of a value‐oriented impact assessment is explained, as well as the resulting economic conditions for an optimal use of resources. In addition, it is shown that value‐ and burden‐oriented approaches are complementary to achieve optimality. Finally, the paper discusses the conditions under which the use of burden‐ or value‐oriented impact assessments is appropriate, respectively.

Finding the optimal use of health-care resources requires the reliable estimation of costs and consequences. Acquiring these estimates may not be difficult for some common treatments. More difficult is the optimization of resources in the area of diagnostics. Only a few attempts have been made to optimize the use of resources in the area of prevention. Several aspects have to be considered when optimizing the resources for prevention: (1) participation rates in structured prevention programs are low, (2), acquiring data on follow-up and outcomes is difficult, (3) there are concerns about the quality of information available to public, and (4), the public is often unaware of scientific assessments of prevention programs. As prevention programs are costly long-term projects, a strategy to select these programs according to possible predictors of success might be useful. The few analyses of cancer prevention in the literature have been directed towards the most common malignant diseases (as assessed by incidence) such as cancer of the breast, colon, lung and prostate. We argue that incidence is a poor marker for selecting secondary prevention programs. Incidence may be a misleading indicator for two reasons: incidence of disease does not predict efficiency of management or good health outcomes, and incidence does not separate clinically significant from non-significant disease. The traditional strategy is based on the assumption that more screening increases the chance of cure. We propose an alternative outcomes model that suggests better disease management justifies new prevention programs. Indicators for better disease management are effective and efficient treatments as well as high-quality screening (sensitivity and specificity) techniques and possibly "side-effects of prevention programs," which provide early signs of success to motivate the patient's participation, to keep up with the program and finally to succeed.

Globalization of global markets have led to the development of turbulent markets where it is indispensable to have high-quality information in order to efficiently use scarce resources. Therefore, it is necessary that every company conducts a qualitative collection of information about the status on the market in order to minimise the risk of making wrong decisions. This high-quality information is indispensable for optimal use of company's resources. The optimal use of resources can be achieved by applying methods of linear programming, especially simplex method. This paper wants to make a bridge between market research and the optimal usage of internal resources.

BackgroundPublic health and primary care are distinct sectors within western health care systems. Within each sector, work is carried out in the context of organizations, for example, public health units and primary care clinics. Building on a scoping literature review, our study aimed to identify the influencing factors within these organizations that affect the ability of these health care sectors to collaborate with one another in the Canadian context. Relationships between these factors were also explored.MethodsWe conducted an interpretive descriptive qualitative study involving in-depth interviews with 74 key informants from three provinces, one each in western, central and eastern Canada, and others representing national organizations, government, or associations. The sample included policy makers, managers, and direct service providers in public health and primary care.ResultsSeven major organizational influencing factors on collaboration were identified: 1) Clear Mandates, Vision, and Goals; 2) Strategic Coordination and Communication Mechanisms between Partners; 3) Formal Organizational Leaders as Collaborative Champions; 4) Collaborative Organizational Culture; 5) Optimal Use of Resources; 6) Optimal Use of Human Resources; and 7) Collaborative Approaches to Programs and Services Delivery.ConclusionWhile each influencing factor was distinct, the many interactions among these influences are indicative of the complex nature of public health and primary care collaboration. These results can be useful for those working to set up new or maintain existing collaborations with public health and primary care which may or may not include other organizations.