ACE research vignette 041: Business Planning and the emergence of new ventures

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. In this vignette, Christophe Garonne and Per Davidsson examine the value of business planning for business start-ups.

Development and parameterization of a rain- and fire-driven model for exploring elephant effects in African savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree-grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation. © 2007 Springer Science+Business Media B.V.

Enterprise business technology governance: A validation of three technology-governance competencies for boards of directors

The competent leadership and governance of digital transformation needs to involve the board of directors. The reported lack of such capability in boards is becoming a pressing issue. Underpinning leadership in such transformation are the competencies to effectively govern Enterprise Technology (ETG). In this paper we take the position that ETG competencies are essential in boards because competent enterprise business technology governance has been shown to contribute to increased revenue, profit, and returns. We report the industry validation processes of a set of three board-of-director competencies needed for effective ETG related to strategy and planning; investment and risk; and, innovation and value creation. We conclude that gaps in board ETG competence remain.

From music student to industry professional: An entrepreneurial learning design

This design-based research project addresses the gap between formal music education curricula and the knowledge and skills necessary to enter the professional music industry. It analyses the work of a teacher/researcher who invited her high school students to start their own business venture, Youth Music Industries (YMI). YMI also functioned as a learning environment informed by the theoretical concepts of communities of practice and social capital. The students staged cycles of events of various scales over a three-year period, as platforms for young artists to engage and develop new, young audiences across Queensland, Australia. The study found that students developed an entrepreneurial mindset through acquisition of specific skills and knowledge. Their learning was captured and distilled into a set of design principles, a pedagogical approach transferrable across the creative industries more broadly.

Culture in Business Process Management: How cultural values determine BPM success

There is consensus among practitioners and academics that culture is a critical factor that is able to determine success or failure of BPM initiatives. Yet, culture is a topic that seems difficult to grasp and manage. This may be the reason for the overall lack of guidance on how to address this topic in practice. We have conducted in-depth research for more than three years to examine why and how culture is relevant to BPM. In this chapter, we introduce a framework that explains the role of culture in BPM. We also present the relevant cultural values that compose a BPM culture, and we introduce a tool to examine the supportiveness of organizational cultures for BPM. Our research results provide the basis for further empirical analyses on the topic and support practitioners in the management of culture as an important factor in BPM initiatives.

Noise Filtering of Process Execution Logs based on Outliers Detection

This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

Log delta analysis: Interpretable differencing of Business process event logs

This paper addresses the problem of identifying and explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

Evidence-based business process management: Using digital opportunities to drive organizational innovation

Process improvement and innovation are risky endeavors, like swimming in unknown waters. In this chapter, I will discuss how process innovation through BPM can benefit from Research-as-a-Service, that is, from the application of research concepts in the processes of BPM projects. A further subject will be how innovations can be converted from confidence-based to evidence-based models due to affordances of digital infrastructures such as large-scale enterprise soft-ware or social media. I will introduce the relevant concepts, provide illustrations for digital capabilities that allow for innovation, and share a number of key takeaway lessons for how organizations can innovate on the basis of digital opportunities and principles of evidence-based BPM: the foundation of all process decisions in facts rather than fiction.

Barriers, drivers and enablers for transitioning towards innovation in the Australian water sector

The Australian water sector needs to adapt to effectively deal with the impacts of climate change on its systems. Challenges as a result of climate change include increasingly extreme occurrences of weather events including flooding and droughts (Pittock, 2011). In response to such challenges, the National Water Commission in Australia has identified the need for the water sector to transition towards being readily adaptable and able to respond to complex needs for a variety of supply and demand scenarios (National Water Commission, 2013). To successfully make this transition, the sector will need to move away from business as usual, and proactively pursue and adopt innovative approaches and technologies as a means to successfully address the impacts of climate change on the Australian water sector. In order to effectively respond to specific innovation challenges related to the sector, including climate change, it is first necessary to possess a foundational understanding about the key elements related to innovation in the sector. This paper presents this base level understanding, identifying the key barriers, drivers and enablers, and elements for innovative practise in the water sector. After initially inspecting the literature around the challenges stemming from climate change faced by the sector, the paper then examines the findings from the initial two rounds of a modified Delphi study, conducted with experts from the Australian water sector, including participants from research, government and industry backgrounds. The key barriers, drivers and enablers for innovation in the sector identified during the initial phase of the study formed the basis for the remainder of the investigation. Key elements investigated were: barriers – scepticism, regulation systems, inconsistent policy; drivers – influence of policy, resource scarcity, thought leadership; enablers – framing the problem, effective regulations, community acceptance. There is a convincing argument for the water sector transitioning to a more flexible, adaptive and responsive system in the face of challenges resulting from climate change. However, without first understanding the challenges and opportunities around making this transition, the likelihood of success is limited. For that reason, this paper takes the first step in understanding the elements surrounding innovation in the Australian water sector.

Liquid Business Process Model Collections

Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Service Interface Synthesis in Business Networks

Mismatches between services needing to interoperate have been addressed through the adaptation of structural and behavioural interfaces of services, which in practice incur long lead time through manual, coding effort. We propose a framework, complementary to con- ventional service adaptation, to synthesise service interfaces in the open setting of business networks, allowing consumers to introspect service interfaces and formulate service invocations. The framework also allows evolved service requests, as new features of service capabilities are discov- ered, through interactions with other, similar services. Finally the frame- work fosters reuse of adaptation efforts through normalisation of struc- tural and behavioural interfaces of similar services. This paper provides a first exposition of the service interface synthesis framework, describing patterns containing novel requirements for unilateral service adaptation and detailing the interface synthesis technique. Complex examples of ser- vices drawn from commercial logistic systems are then used to validate the synthesis technique and identify open challenges and future research directions.

Understanding the business case for infrastructure sustainability

The relationship between corporate and sustainability performance continues to be controversial and unclear, not withstanding numerous theoretical and empirical studies. Despite this, views on corporate responsibilities “meet where management can show how voluntary social and environmental management contributes to the competitiveness and economic success of the company.” This approach is fundamental to the business case for infrastructure sustainability. It suggests that beyond-compliance activities undertaken by companies are commercially justified if they can be shown to contribute to profitability and shareholder value. Potential public good benefits range across a wide spectrum of economic (for example employment, local purchasing, reduced demand for electricity generation), social (indigenous employment and development, equity of access), and environmental (lower greenhouse gas emission, reduced use of non-renewable resources and potable water, less waste, enhanced biodiversity). Some of these benefits have impacts that lie in more than one of the economic, social, and environmental areas of public goods. Using a sustainability rating schemes and potential business benefits from sustainability initiatives, this paper presents a brief summary of an online survey of industry that identifies how rating scheme themes and business benefits relate. This allows for a case to be built demonstrating which sustainability themes offer particular business benefits.

A smooth transition logit model of the effects of deregulation in the electricity market

This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market and ascertain whether increased competition has resulted in significant changes in the behaviour of the spot price of electricity, specifically with respect to the occurrence of periodic abnormally high prices. The model allows the timing of any change to be endogenously determined and also market participants' behaviour to change gradually over time. The main results provide clear evidence in support of a structural change in the nature of price events, and the endogenously determined timing of the change is consistent with the process of deregulation in Queensland.