Knowledge-based strategic planning: harnessing (in)tangible assets of city-regions

Purpose – The aim of this paper is to investigate the ways of best managing city-regions’ valuable tangible and intangible assets while pursuing a knowledge-based urban development that is sustainable and competitive. Design/methodology/approach – The paper provides a theoretical framework to conceptualise a new strategic planning mechanism, knowledge-based strategic planning, which has been emerged as a planning mechanism for the knowledge-based urban development of post-industrial city-regions. Originality/value – The paper develops a planning framework entitled 6K1C for knowledge-based strategic planning to be used in the analysis of city-regions’ tangible and intangible assets. Practical implications – The paper discusses the importance of asset mapping of cityregions, and explores the ways of successfully managing city-regions’ tangible/intangible assets to achieve an urban development that is sustainable and knowledge-based. Keywords – Knowledge-based urban development, Knowledge-based strategic planning, Tangible assets, Intangible assets, City-regions. Paper type – Academic Research Paper

Beyond the fashionable : strategic planning for critical information literacy education

The challenge for all educators is to fuse the learning of information literacy to an academic education in such a way that the outcome is systematic and sustainable learning for students. This challenge can be answered through long-term commitment to information literacy education bound to organisation-wide, renewable strategic planning and driven through systemic reform. This chapter seeks to explore the two sides of reforming information literacy education in an academic environment. Specifically, it will examine how one Australian university has undertaken the implementation of a rigorous strategic, systemic approach to information literacy learning and teaching.

Strategic planning in a non profit organistion : valuing the process

Non-profit organisations by their very nature are staffed by a variety of different people with a range of backgrounds, experiences and reasons for participation. These differences can lead to “distancing” of certain groups and with little time or money for boundary spanning the organisation can find itself in a fractured state that hampers not just its goal realisation, but its goal determination. Strategic planning is often seen as an expensive, time consuming process that many smaller non-profit organisations can little afford to indulge in. In addition, the ruling elite, whether historical or professional may view the process as unnecessary or threatening. However, strategic planning can offer processes and potential outcomes that non profit organisations can not afford to ignore. This paper provides an analysis through one case study involving a non-profit, health related organisation that moved through a process of strategic planning that ultimately encouraged development and group cohesion through goal identification and determination as well as strategy formulation. The results indicate the importance of valuing the strategic planning process itself rather than the form it takes. Challenging the rulership of the historical or professional elite can be difficult in a non-profit organisation, but diversity of involvement rather than uniformity proved to be a successful strategy. Organisational cohesion through consensus building was the ultimate outcome.

An expert system for the strategic planning of construction projects

This paper describes the instigation and development of an expert system to aid in the strategic planning of construction projects. The paper consists of four parts - the origin of the project, the development of the concepts needed for the proposed system, the building of the system itself, and assessment of its performance. The origin of the project is outlined starting with the Japanese commitment to 5th generation computing together with the increasing local reaction to theory based prescriptive research in the field. The subsequent development of activities via the Alvey Commission and the RICS in conjunction with Salford University are traced culminating in the proposal and execution of the first major expert system to be built for the UK construction industry, subsequently recognised as one of the most successful of the expert system projects commissioned under the Alvey programme

Exploring the usefulness of structural–functional approaches to analyse governance of planning systems

Existing planning theories tend to be limited in their analytical scope and often fail to account for the impact of many interactions between the multitudes of stakeholders involved in strategic planning processes. Although many theorists rejected structural–functional approaches from the 1970s, this article argues that many of structural–functional concepts remain relevant and useful to planning practitioners. In fact, structural–functional approaches are highly useful and practical when used as a foundation for systemic analysis of real-world, multi-layered, complex planning systems to support evidence-based governance reform. Such approaches provide a logical and systematic approach to the analysis of the wider governance of strategic planning systems that is grounded in systems theory and complementary to existing theories of complexity and planning. While we do not propose its use as a grand theory of planning, this article discusses how structural–functional concepts and approaches might be applied to underpin a practical analysis of the complex decision-making arrangements that drive planning practice, and to provide the evidence needed to target reform of poorly performing arrangements.

Reframe QUT's evaluation framework : a case study of planning, policy and positioning leading to educational best practice

Every university in Australia has a set of policies that guide the institution in its educational practices, however, the policies are often developed in isolation to each other. Now imagine a space where policies are evidence-based, refined annually, cohesively interrelated, and meet stakeholders’ needs. Is this happenstance or the result of good planning? Culturally, Queensland University of Technology (QUT) is a risk-averse institution that takes pride in its financial solvency and is always keen to know “how are we going?” With a twenty-year history of annual reporting that assures the quality of course performance through multiple lines of evidence, QUT’s Learning and Teaching Unit went one step further and strategically aligned a suite of policies that take into consideration the needs of their stakeholders, collaborate with other areas across the institution and use multiple lines of evidence to inform curriculum decision-making. In QUT’s experience, strategic planning can lead to policy that is designed to meet stakeholders’ needs, not manage them; where decision-making is supported by evidence, not rhetoric; where all feedback is incorporated, not ignored; and where policies are cohesively interrelated, not isolated. While many may call this ‘policy nirvana’, QUT has positioned itself to demonstrate good educational practice through Reframe, its evaluation framework. In this case, best practice was achieved through the application of a theory of change and a design-led logic model that allows for transition to other institutions with different cultural specificity. The evaluation approach follows Seldin’s (2003) notion to offer depth and breadth to the evaluation framework along with Berk’s (2005) concept of multiple lines of evidence. In summary, this paper offers university executives, academics, planning and quality staff an opportunity to understand the critical steps that lead to strategic planning and design of evidence-based educational policy that positions a university for best practice in learning and teaching.

Natural hazards and land use planning: How resilient must a landowner be?

The past decade has seen an increase in the occurrence of natural hazards and the experience in Australia has led to a reconsideration of the planning for natural hazards by government and to the adoption of a whole-of-nation resilience-based approach to disaster management. A key component of creating community resilience is the integration of disaster management with government and community strategic planning in relation to the social, built, economic and natural environments. Joint responsibility of government and the community for ‘land use planning systems and building control arrangements [which] reduce, as far as is practicable, community exposure to unreasonable risks from known hazards’, is a critical element of a resilient community. As the responsibility for the implementation of land use planning policies in Australia is generally with local governments, this paper will examine whether, in light of improved predictive technology, the failure of a local government to adequately foresee and make provision for a known hazard will give rise to liability for damage or loss of property caused by that hazard.

A decision-analysis-based framework for analysing stakeholder behaviour in scenario planning

Scenario planning is a method widely used by strategic planners to address uncertainty about the future. However, current methods either fail to address the future behaviour and impact of stakeholders or they treat the role of stakeholders informally. We present a practical decision-analysis-based methodology for analysing stakeholder objectives and likely behaviour within contested unfolding futures. We address issues of power, interest, and commitment to achieve desired outcomes across a broad stakeholder constituency. Drawing on frameworks for corporate social responsibility (CSR), we provide an illustrative example of our approach to analyse a complex contested issue that crosses geographic, organisational and cultural boundaries. Whilst strategies can be developed by individual organisations that consider the interests of others – for example in consideration of an organisation's CSR agenda – we show that our augmentation of scenario method provides a further, nuanced, analysis of the power and objectives of all concerned stakeholders across a variety of unfolding futures. The resulting modelling framework is intended to yield insights and hence more informed decision making by individual stakeholders or regulators.

Planning the unplanned City: The story of the gold coast

One of the distinctive features of Gold Coast urbanisation is its historically ad hoc approach to development with little or no strategic planning to guide it. Many have commented on the lack of planning on the Gold Coast calling it ‘an experiment in freedom’ or ‘free enterprise city’. Following a major restructuring of the Queensland’s local councils, the 1990s witnessed a shift from ad hoc decision making to more systematic planning on the Gold Coast. Understanding the past is important for shaping the future. This paper reviews the history of regulatory planning on the Gold Coast, encompassing decisions affecting the form and development of its earliest settlements through to its periods of greatest construction and most streamlined decision–making. It focuses mainly on past planning processes, the problems identified in each planning exercise and the interventions introduced, asking whether these were implemented or not and why. The paper positions the Gold Coast as a physical embodiment of this history of decision making, assessing the effects on the city as a whole of specific measures either affording freedoms or insisting on accountability to various levels of regulation. It examines how the absence of some planning measures influenced the form of the city and its internal arrangements and considers how the shift from ad hoc decision making towards more systematic planning efforts affected the city’s urbanisation. The lessons that the Gold Coast example provides will resonate with places elsewhere in Australia and the world, if not always in scale definitely in substance.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.