Diagnosing and treating operational and implementation barriers in synoptic marketing planning

Strategic marketing planning is now widely adopted by business-to-business organizations. While marketing planning principles are well established, practitioners attempting to implement the process often find their progress impeded by a variety of barriers. These barriers are explored through a review of published evidence and case study analysis of several organizations. This analysis exposes three levels of barriers to effective business-to-business marketing planning, relating to (i) organizational infrastructure, (ii) the planning process and (iii) implementation. These barriers reflect the synoptic nature of planning in many organizations. The findings lead to the development of a practitioner-oriented diagnostic and treatment tool which guides managers through the marketing planning process. Although this diagnostic deals specifically with issues which are relevant to the marketing planner, its wider implications for strategic planning are also explored.

Challenges in communicating and using ensembles in operational flood forecasting.

Following trends in operational weather forecasting, where ensemble prediction systems (EPS) are now increasingly the norm, flood forecasters are beginning to experiment with using similar ensemble methods. Most of the effort to date has focused on the substantial technical challenges of developing coupled rainfall-runoff systems to represent the full cascade of uncertainties involved in predicting future flooding. As a consequence much less attention has been given to the communication and eventual use of EPS flood forecasts. Drawing on interviews and other research with operational flood forecasters from across Europe, this paper highlights a number of challenges to communicating and using ensemble flood forecasts operationally. It is shown that operational flood forecasters understand the skill, operational limitations, and informational value of EPS products in a variety of different and sometimes contradictory ways. Despite the efforts of forecasting agencies to design effective ways to communicate EPS forecasts to non-experts, operational flood forecasters were often skeptical about the ability of forecast recipients to understand or use them appropriately. It is argued that better training and closer contacts between operational flood forecasters and EPS system designers can help ensure the uncertainty represented by EPS forecasts is represented in ways that are most appropriate and meaningful for their intended consumers, but some fundamental political and institutional challenges to using ensembles, such as differing attitudes to false alarms and to responsibility for management of blame in the event of poor or mistaken forecasts are also highlighted. Copyright © 2010 Royal Meteorological Society.

Developing green supply chain management taxonomy-based decision support system

The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.

On a resurgence of management simulations and games

The past few years have seen a significant resurgence of interest in ‘management games’ and ‘management flight simulators’, one particularly active source of such work being the system dynamics community. After proposing a distinction between games and simulations, this paper provides some background to these developments by briefly describing the historical roots of the field and the fundamental ideas of the system dynamics community, which are now giving rise to ‘microworlds’. The training advantages of management simulations and games are then discussed. The paper closes with a note on the research and findings of the system dynamics field and by offering some words of warning on the perils of simulation and game use. Two scenarios for how the use of simulations and games as management education devices might develop in the future are proposed. An Appendix describes five examples of very different types of management simulations and games.

Modelling as learning: a consultancy methodology for enhancing learning in management teams

This article reviews the experiences of a practising business consultancy division. It discusses the reasons for the failure of the traditional, expert consultancy approach and states the requirements for a more suitable consultancy methodology. An approach called ‘Modelling as Learning’ is introduced, its three defining aspects being: client ownership of all analytical work performed, consultant acting as facilitator and sensitivity to soft issues within and surrounding a problem. The goal of such an approach is set as the acceleration of the client's learning about the business. The tools that are used within this methodological framework are discussed and some case studies of the methodology are presented. It is argued that a learning experience was necessary before arriving at the new methodology but that it is now a valuable and significant component of the division's work.

Operational active fire mapping and burnt area identification applicable to Mexican Nature Protection Areas using MODIS and NOAA-AVHRR direct readout data

Since 1999, the National Commission for the Knowledge and Use of the Biodiversity (CONABIO) in Mexico has been developing and managing the “Operational program for the detection of hot-spots using remote sensing techniques”. This program uses images from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites and from the Advanced Very High Resolution Radiometer of the National Oceanic and Atmospheric Administration (NOAA-AVHRR), which are operationally received through the Direct Readout station (DR) at CONABIO. This allows the near-real time monitoring of fire events in Mexico and Central America. In addition to the detection of active fires, the location of hot spots are classified with respect to vegetation types, accessibility, and risk to Nature Protection Areas (NPA). Besides the fast detection of fires, further analysis is necessary due to the considerable effects of forest fires on biodiversity and human life. This fire impact assessment is crucial to support the needs of resource managers and policy makers for adequate fire recovery and restoration actions. CONABIO attempts to meet these requirements, providing post-fire assessment products as part of the management system in particular for satellite-based burnt area mapping. This paper provides an overview of the main components of the operational system and will present an outlook to future activities and system improvements, especially the development of a burnt area product. A special focus will also be placed on the fire occurrence within NPAs of Mexico

Supply management capabilities, routine bundles and their impact on firm performance

Despite the generally positive contribution of supply management capabilities to firm performance their respective routines require more depth of assessment. Using the resource-based view we examine four routines bundles comprising ostensive and performative aspects of supply management capability – supply management integration, coordinated sourcing, collaboration management and performance assessment. Using structural equation modelling we measure supply management capability empirically as a second-order latent variable and estimate its effect on a series of financial and operational performance measures. The routines-based approach allows us to demonstrate a different, more fine-grained approach for assessing consistent bundles of homogeneous patterns of activity across firms. The results suggest supply management capability is formed of internally consistent routine bundles, which are significantly related to financial performance, mediated by operational performance. Our results confirm an indirect effect of firm performance for ‘core’ routines forming the architecture of a supply management capability. Supply management capability primarily improves the operational performance of the business, which is subsequently translated into improved financial performance. The study is significant for practice as it offers a different view about the face-valid rationale of supply management directly influencing firm financial performance. We confound this assumption, prompting caution when placing too much importance on directly assessing supply management capability using financial performance of the business.

Multi-criteria analysis and the resolution of sustainable development dilemmas: a stakeholder management approach

We demonstrate that stakeholder-oriented multi-criteria analysis (MCA) can adequately address a variety of sustainable development dilemmas in decision-making, especially when applied to complex project evaluations involving multiple objectives and multiple stakeholder groups. Such evaluations are typically geared towards satisfying simultaneously private economic goals, broader social objectives and environmental targets. We show that, under specific conditions, a variety of stakeholder-oriented MCA approaches may be able to contribute substantively to the resolution or improved governance of societal conflicts and the pursuit of the public good in the form of sustainable development. We contrast the potential usefulness of these stakeholder-oriented approaches – in terms of their ability to contribute to sustainable development – with more conventional MCA approaches and social cost–benefit analysis.

Soil bacterial phoD gene abundance and expression in response to applied phosphorus and long-term management

Bacterial transformation of phosphorus (P) compounds in soil is largely dependent on soil microbial community function, and is therefore sensitive to anthropogenic disturbances such as fertilization or cropping systems. However, the effect of soil management on the transcription of bacterial genes that encode phosphatases, such as phoD, is largely unknown. This greenhouse study examined the effect of long-term management and P amendment on potential alkaline phosphatase (ALP) activity and phoD gene (DNA) and transcript (RNA) abundance. Soil samples (0–15 cm) were collected from the Glenlea Long-term Rotation near Winnipeg, Manitoba, to compare organic, conventional and prairie management systems. In the greenhouse, pots of soil from each management system were amended with P as either soluble mineral fertilizer or cattle manure and then planted with Italian ryegrass (Lolium multiforum). Soils from each pot were sampled for analysis immediately and after 30 and 106 days. Significant differences among the soil/P treatments were detected for inorganic P, but not the organic P in NaHCO3-extracts. At day 0, ALP activity was similar among the soil/P treatments, but was higher after 30 days for all P amendments in soil from organically managed plots. In contrast, ALP activity in soils under conventional and prairie management responded to increasing rates of manure only, with significant effects from medium and high manure application rates at 30 and 106 days. Differences in ALP activity at 30 days corresponded to the abundance of bacterial phoD genes, which were also significantly higher in soils under organic management. However, this correlation was not significant for transcript abundance. Next-generation sequencing allowed the identification of 199 unique phoD operational taxonomic units (OTUs) from the metagenome (soil DNA) and 35 unique OTUs from the metatranscriptome (soil RNA), indicating that a subset of phoD genes was being transcribed in all soils.

Operations research/management science tools for integrating people with disabilities into employment. A study on Valencia`s Sheltered Work Centres for Disabled

People with disabilities have a right to a full life in every sense and one of those fundamental rights is the possibility to work. In this paper, the importance of social employment integration of disabled people is highlighted as one of the stakeholders to be satisfied by companies in the new framework that corporate social responsibility is constructing. The objective of the paper is to revise the benefits of some well-known operations research/management science tools that, if applied correctly, have a double positive impact on work accessibility and improved productivity. The responses collected from managers of Valencia`s ShelteredWork Centres for Disabled by means of a structured questionnaire are used to analyse the level of implementation of these tools and their impact depending on the type of centre, the kind of disability and other structural variables.

Implementing Policy Management through BDI

The requirement for Grid middleware to be largely transparent to individual users and at the same time act in accordance with their personal needs is a difficult challenge. In e-science scenarios, users cannot be repeatedly interrogated for each operational decision made when enacting experiments on the Grid. It is thus important to specify and enforce policies that enable the environment to be configured to take user preferences into account automatically. In particular, we need to consider the context in which these policies are applied, because decisions are based not only on the rules of the policy but also on the current state of the system. Consideration of context is explicitly addressed, in the agent perspective, when deciding how to balance the achievement of goals and reaction to the environment. One commonly-applied abstraction that balances reaction to multiple events with context-based reasoning in the way suggested by our requirements is the belief-desire-intention (BDI) architecture, which has proven successful in many applications. In this paper, we argue that BDI is an appropriate model for policy enforcement, and describe the application of BDI to policy enforcement in personalising Grid service discovery. We show how this has been implemented in the myGrid registry to provide bioinformaticians with control over the services returned to them by the service discovery process.

Effective Data Management Enables Intelligent Utility Management

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

On Real-Time Monitoring And Control For Efficient Management Of Drinking Water Networks: Barcelona Case Study

Drinking water utilities in urban areas are focused on finding smart solutions facing new challenges in their real-time operation because of limited water resources, intensive energy requirements, a growing population, a costly and ageing infrastructure, increasingly stringent regulations, and increased attention towards the environmental impact of water use. Such challenges force water managers to monitor and control not only water supply and distribution, but also consumer demand. This paper presents and discusses novel methodologies and procedures towards an integrated water resource management system based on advanced ICT technologies of automation and telecommunications for largely improving the efficiency of drinking water networks (DWN) in terms of water use, energy consumption, water loss minimization, and water quality guarantees. In particular, the paper addresses the first results of the European project EFFINET (FP7-ICT2011-8-318556) devoted to the monitoring and control of the DWN in Barcelona (Spain). Results are split in two levels according to different management objectives: (i) the monitoring level is concerned with all the aspects involved in the observation of the current state of a system and the detection/diagnosis of abnormal situations. It is achieved through sensors and communications technology, together with mathematical models; (ii) the control level is concerned with computing the best suitable and admissible control strategies for network actuators as to optimize a given set of operational goals related to the performance of the overall system. This level covers the network control (optimal management of water and energy) and the demand management (smart metering, efficient supply). The consideration of the Barcelona DWN as the case study will allow to prove the general applicability of the proposed integrated ICT solutions and their effectiveness in the management of DWN, with considerable savings of electricity costs and reduced water loss while ensuring the high European standards of water quality to citizens.

Reservoir Management For Flood And Drought Protection Using Infinite Horizon Model Predictive Control

Model Predictive Control (MPC) is a control method that solves in real time an optimal control problem over a finite horizon. The finiteness of the horizon is both the reason of MPC's success and its main limitation. In operational water resources management, MPC has been in fact successfully employed for controlling systems with a relatively short memory, such as canals, where the horizon length is not an issue. For reservoirs, which have generally a longer memory, MPC applications are presently limited to short term management only. Short term reservoir management can be effectively used to deal with fast process, such as floods, but it is not capable of looking sufficiently ahead to handle long term issues, such as drought. To overcome this limitation, we propose an Infinite Horizon MPC (IH-MPC) solution that is particularly suitable for reservoir management. We propose to structure the input signal by use of orthogonal basis functions, therefore reducing the optimization argument to a finite number of variables, and making the control problem solvable in a reasonable time. We applied this solution for the management of the Manantali Reservoir. Manantali is a yearly reservoir located in Mali, on the Senegal river, affecting water systems of Mali, Senegal, and Mauritania. The long term horizon offered by IH-MPC is necessary to deal with the strongly seasonal climate of the region.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.