Lean Enterprise Software and Systems

Software startups are more popular than ever and growing in numbers. They operate under conditions of extreme uncertainty and face many challenges. Often, agile development practices and lean principles are suggested as ways to increase the odds of succeeding as a startup, as they both advocate close customer collaboration and short feedback cycles focusing on delivering direct customer value. However, based on an interview study we see that despite guidance and support in terms of well-known and documented development methods, practitioners find it difficult to implement and apply these in practice. To explore this further, and to propose operational support for software startup companies, this study aims at investigating (1) what are the typical challenges when finding a product idea worth scaling, and (2) what solution would serve to address these challenges. To this end, we propose the ‘Early Stage Software Startup Development Model’ (ESSSDM). The model extends already existing lean principles, but offers novel support for practitioners for investigating multiple product ideas in parallel, for determining when to move forward with a product idea, and for deciding when to abandon a product idea. The model was evaluated in a software startup project, as well as with industry professionals within the software startup domain.

As the Software Engineering landscape continues to evolve and new paradigms are introduced, there can be a tendency for both industry and academia to enthusiastically embrace new approaches and march forward under whatever banner conventional wisdom has decided to adopt. One such banner is Lean Software Development, a paradigm that continues to see a growth in interest driven by the need for cost reductions within industry. The term lean attracts the attention of business, but precisely how it applies within software development is still being debated. In addition, its relationship to the better understood agile methodologies is also a topic for debate. Having been drawn into this research area ourselves, we present here a review of Lean Software Development and try to distil out for the reader some understanding of this somewhat undefined topic. We conclude with some thoughts on where this subject might go to from here.

Conclusion: Gaps exist with respect to LSD principles. In particular: deferring commitment, respecting people and knowledge creation. The principle of delivering fast is well supported.

The current trends in most software-intensive product development organizations are in striving for high performance. Overall, software product creation has become more and more value-driven. However, from the customer and user satisfaction points of view “software” itself has no value until it is executed in some target machine (including embedded systems) producing certain results. Those outcomes (e.g., web services) bring benefits and even delight which are valued by the customers in terms of quality. In order to address those considerations, this paper proposes a software team-oriented performance analysis and improvement framework supported by provisional instrumentation. The aim is to gauge Lean software teams and organizations to advance their thinking towards the total quality perspective. The industrial cases demonstrate, how it is able to catalyst such team performance drivers and quality aims of software development under different circumstances.

In large operational systems, understanding the status of evolutionary capability development is often difficult. This is particularly true where capabilities depend on significant software components that are managed and operated as interacting subsystems. Schedules are rarely stable due to significant external drivers, thus integrated master schedules are hard to maintain and update. On-demand (pull) scheduling methods have been shown to smooth flow and maximize value across a process. The mechanics of these methods enhance visibility by forcing informed discussions on value, capability, and priority and by providing timely, relevant information to higher-level engineering organizations. This paper uses a notional information management system supporting a large health care system as an illustration of a management architecture that supports such an approach. The architecture includes a network of kanban-based scheduling systems, enhanced visualization, and employs a services approach to systems engineering that allows its work to be quantized as part of the overall development flow.

Beyond Budgeting is an innovation from the management accounting literature that seeks to improve performance and manage organisations through flexible sense-and-respond type mechanisms, rather than the more rigid traditional command-and-control models. This contemporary thinking in management accounting resonates strongly with contemporary thinking in information systems development (ISD). In particular, the Beyond Budgeting model shares many similarities with agile software development (ASD) with both having a distinctly agile and flexible foundation. This paper discusses the history of Beyond Budgeting, its relationship with performance management and its appropriateness for the field of software development.

There has been a request to publish more research results on business impacts of agile adoption in software team. This is an empirical study done in one Fortune 500 company where agility was adopted while the team was working on in order to deliver a product consisting of responsive web design. The adoption resulted in Pragmatic Agile approach, where the agility and Hero team approach was found to result in significant savings in both efforts needed to make the product and quality of the product delivered.

Today, the importance of digital services with social aspects is increasing all the time. Many companies have been strong in new product development, but today they are moving to new service development. Customer value has become the strategic factor for contemporary companies when developing products and services for consumers; even so that companies are selling customer value instead of products or services. Customer orientation and customer involvement play important roles in service industries. This study describes how the case company entered to B-to-C digital service market and developed a new social network cloud service for music lovers. This theory testing case study discusses and reflects the success factors of new service development and the organization against the literature. Mostly the theory is confirmed, but also improvement of the theory is suggested. Finally, future research ideas are proposed.

Customer value determines how products and services succeed in the marketplace. Early assessment of customer value is important for software startups, spin-off companies, and new product development in existing companies. Software technology often influences customer value and typically defines the main competitive advantage in both entrepreneurial and intrapreneurial settings. Value-related feedback from real customers is needed during software development and maintenance, and decision-making should be increasingly based on empirical evidence acquired through experiments. Getting such value-related feedback usually requires a so-called minimum viable product (MVP), i.e., an artefact that may be incomplete in functionality or quality, but displays characteristics that allows determining its customer value. In this article we report on a case study which used industry-academia collaboration for creating such an MVP. Our goal was to identify strengths and weaknesses of such an approach to creating MVPs while providing practical recommendations for improvement. The process followed in the case study was found to be very suitable for creating MVPs, reducing company-specific risks when testing customer-value, and advancing university education.

Today, products within telecommunication, transportation, consumer electronics, home automation, security etc. involve an increasing amount of software. As a result, organizations that have a tradition within hardware development are transforming to become software-intensive organizations. This implies products where software constitutes the majority of functionality, costs, future investments, and potential. While this shift poses a number of challenges, it brings with it opportunities as well. One of these opportunities is to collect product data in order to learn about product use, to inform product management decisions, and for improving already deployed products. In this paper, we focus on the opportunity to use post-deployment data, i.e. data that is generated while products are used, as a basis for product improvement and new product development. We do so by studying three software development companies involved in large-scale development of embedded software. In our study, we highlight limitations in post-deployment data usage and we conclude that post-deployment data remains an untapped resource for most companies. The contribution of the paper is two-fold. First, we present key opportunities for more effective product development based on post-deployment data usage. Second, we propose a framework for organizations interested in advancing their use of post-deployment product data.

As development teams’ resources are limited, selecting the right features is of utmost importance. Often, features are considered right if they result in increased business value at acceptable implementation cost. Predicting implementation cost and prioritizing features is well documented in literature. However, there has only been little work on the prediction of business value. This article presents an approach for feature proioritization that is based on mock-purchases. Considering several limitations, the approach allows key stakeholders to depict the real business value of a feature without having to implement it. Hence, the approach allows feature prioritization based on facts rather than on predictions. The approach was evaluated with a smartphone application. The business value of two features which were subjectively considered to be equally important was investigated. Moreover, the users were assigned different price categories for the features. Combined with live customer feedback, the approach allows us to identify an adequate pricing for the features. The study yielded insightful results as it showed which of the features incorporates higher revenue as well as how users react to the approach. It contributes to the body of knowledge in requirements engineering and software engineering as it enables practitioners to select features based on facts rather than predictions and to find ideal price points.

A lot of discussion on how to efficiently develop software by using agile methods in enterprises and what kind of implications enterprises face on their path towards enterprise agility exists in nowadays. This paper describes how Fuzzy Cognitive Maps (FCM) can be used as Computational Intelligence (CI) tools for Decision Support (DS) in reducing the risks of the implications in this adaptation or transformation process. Particularly, FCM are used in understanding the effect of a set of critical Agile Adoption Factors (AAF) proposed in literature in the success of adopting agile. A set of preliminary experiments have been conducted to show that AAF can be evaluated with the use of FCM and their effect on adoption success is validated in three specific contexts. The scenarios investigated show that a critical implication is corporate bureaucracy. Also, results indicate that some enablers are the project teams’ personal traits, such as collaborative attitude and readiness to change, as well as, the customers’ level of commitment. The proposed FCM model provides an insight on the usefulness of the method for assessing agile transformation success.

Without doubt much of the success in developing software solutions are due to proper project management, supported by many prominent and dedicated organizations and professionals. During the recent years the volatility and uncertainty in software development have, however, undermined the success. The agile and lean software development approaches have also brought up a profound difference between dealing with ordinary problems and wicked problems, but have failed to provide the management with solid theoretical background helping them to take proper decisions. Generally, the complexity theory is often referred to, but only at a superficial level. This paper attempts to explore what it means to build a leadership approach for software development that is based actually on complexity theory. We propose a novel approach called the unproject leadership model. The proposed model translates and maps the specific complexity concepts to the software development domain, consolidating them with the contributions already achieved by the lean and agile literature. As a result, the proposed model reverses many of the core project management practices. There are severe ramifications to large parts of contemporary organization management: converting leadership into interaction between people, flattening hierarchies and removing formal structures, abandoning top-down rules and plans. An initial validation of the proposed model is presented as well as the future directions are outlined.

Agile practices and Software Project Portfolio Management (SPPM) have both been individually investigated, but the relationship between them remains poorly understood. The different emphases of SPPM and agile can lead to tensions between the portfolio and the project. This research-in-progress identifies those tensions and sets out a plan to examine the financial and project portfolio literature for potential solutions that can be adapted to Information Systems Development to mediate between SPPM and agile.