A design for business intelligence service in demand driven supply chain management

This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

Buzz-words in business and management studies

The paper presents a theory of the use of buzz-words in academic discourse. It uses economic principles to analyse the incentives to innovate new buzz words and to use existing buzz-words promoted by other people. It argues that the lack of a credible dominant intellectual elite in business studies, combined with the rapid growth of academic employment in business schools, has stimulated an inefficient proliferation of buzz-words in management studies. It argues that this proliferatilon of buzz-words is in danger of bringing the field of study into disrepute.

Enterprise intelligence: searching for a single version of the truth

Multiple versions of information and associated problems are well documented in both academic research and industry best practices. Many solutions have proposed a single version of the truth, with Business intelligence being adopted by many organizations. Business Intelligence (BI), however, is largely based on the collection of data, processing and presentation of information to meet different stakeholders’ requirement. This paper reviews the promise of Enterprise Intelligence, which promises to support decision-making based on a defined strategic understanding of the organizations goals and a unified version of the truth.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Exploring business and IT alignment mechanisms: toward a learning perspective

Numerous studies have attempted to develop strategic alignment mechanisms. The strategic alignment mechanism is broken down into two categories namely: strategy process and strategy content. Our review shows that alignment research has been carried out in isolation. We see this as having had the effect of limiting the extent to which executives can understand elements of performance. We confer with a number of researchers in postulating that using a mechanism such as multilevel learning to combine strategy content and strategy process under one metaphor can greatly facilitate, through exploration and exploitation, the understanding not only of human interactions within a firm, but also of the interaction existent between a firm and its environment. The findings in this study further support the idea of integrating strategy process and content to have a better understating of alignment maturity and impact on business performance. It also elaborates the affect of misalignment in companies on performance.

What matters in business incubation? A literature review and a suggestion for situated theorising

Purpose – The purpose of this paper is twofold: first, to provide a critical assessment of the literature on business incubation effectiveness and second, to submit a situated theoretical perspective on how business incubation management can provide an environment that supports the development of incubatee entrepreneurs and their businesses. Design/methodology/approach – The paper provides a narrative critical assessment of the literature on business incubation effectiveness. Definitional issues, performance aspects and approaches to establishing critical success factors in business incubation are discussed. Business incubation management is identified as an overarching factor for theorising on business incubation effectiveness. Findings – The literature on business incubation effectiveness suffers from several deficiencies, including definitional incongruence, descriptive accounts, fragmentation and lack of strong conceptual grounding. Notwithstanding the growth of research on this domain, understanding of how entrepreneurs and their businesses develop within the business incubator environment remains limited. Given the importance of relational, intangible factors in business incubation and the critical role of business incubation management in orchestrating and optimising such factors, it is suggested that theorising efforts would benefit from a situated perspective. Originality/value – The identification of specific shortcomings in the literature on business incubation highlights the need for more systematic efforts towards theory building. It is suggested that focusing on the role of business incubation management from a situated learning theory perspective can lend itself to a more profound understanding of the development process of incubatee entrepreneurs and their firms. Theoretical propositions are offered to this effect, as well as avenues for future research.

Knowledge and information evaluation practice: an exploratory study in a construction firm

There are a number of challenges associated with managing knowledge and information in construction organizations delivering major capital assets. These include the ever-increasing volumes of information, losing people because of retirement or competitors, the continuously changing nature of information, lack of methods on eliciting useful knowledge, development of new information technologies and changes in management and innovation practices. Existing tools and methodologies for valuing intangible assets in fields such as engineering, project management and financial, accounting, do not address fully the issues associated with the valuation of information and knowledge. Information is rarely recorded in a way that a document can be valued, when either produced or subsequently retrieved and re-used. In addition there is a wealth of tacit personal knowledge which, if codified into documentary information, may prove to be very valuable to operators of the finished asset or future designers. This paper addresses the problem of information overload and identifies the differences between data, information and knowledge. An exploratory study was conducted with a leading construction consultant examining three perspectives (business, project management and document management) by structured interviews and specifically how to value information in practical terms. Major challenges in information management are identified. An through-life Information Evaluation methodology (IEM) is presented to reduce information overload and to make the information more valuable in the future.