Scenario planning:teaching how to anticipate perceived environmental uncertainty within strategy development

Scenario Planning is a strategy tool with growing popularity in both academia and practical situations. Current practices in the teaching of scenario planning are largely based on existing literature which utilises scenario planning to develop strategies for the future, primarily considering the assessment of perceived macro-external environmental uncertainties. However there is a body of literature hitherto ignored by scenario planning researchers, which suggests that Perceived Environmental Uncertainty (PEU) influences micro-external or industrial environmental as well as the internal environment of the organisation. This paper provides a review of the most dominant theories on scenario planning process, demonstrates the need to consider PEU theory within scenario planning and presents how this can be done. The scope of this paper is to enhance the scenario planning process as a tool taught for Strategy Development. A case vignette is developed based on published scenarios to demonstrate the potential utilisation of the proposed process.

Perceived environmental uncertainty in scenario planning

Scenarioplanning is a strategy tool with growing popularity in both academia and practical situations. Current practices of scenarioplanning are largely based on existing literature which utilises scenarioplanning to develop strategies for the future, primarily considering the assessment of perceived macro-external environmentaluncertainties. However there is a body of literature hitherto ignored by scenarioplanning researchers, which suggests that PerceivedEnvironmentalUncertainty (PEU) influences the micro-external as well as the internal environment of the organisation. This paper reviews the most dominant theories on scenarioplanning process and PEU, developing three propositions for the practice of scenarioplanning process. Furthermore, it shows how these propositions can be integrated in the scenarioplanning process in order to improve the development of strategy.

Scenario planning at business unit level

The scenario planning literature is focused on corporate level interventions. There is a general consensus on the method, but there is little debate about the stages involved in building and using the scenarios. This article presents a case study of a scenario planning intervention, which was conducted at a business unit of the British division of one of the largest beauty and cosmetic products multinationals. The method adopted in this case study has some fundamental differences to the existing models used at corporate level. This research is based on the principles of autoethnography, since its purpose is to present self-critical reflections, enhanced by reflective and reflexive conversations on a scenario planning method used at business unit level. The critical reflections concern a series of critical incidents which distinguish this method from existing intuitive logic scenario planning models which are used at corporate level planning. Ultimately this article contributes to the scenario planning method literature by providing insights into its practice at business unit level. © 2012 Elsevier Ltd.

A robustness framework for monitoring real options under uncertainty

This paper presents a problem structuring methodology to assess real option decisions in the face of unpredictability. Based on principles of robustness analysis and scenario planning, we demonstrate how decision-aiding can facilitate participation in projects setting and achieve effective decision making through the use of real options reasoning. We argue that robustness heuristics developed in earlier studies can be practical proxies for real options performance, hence indicators of efficient flexible planning. The developed framework also highlights how to integrate real options solutions in firms’ strategic plans and operating actions. The use of the methodology in a location decision application is provided for illustration.

A Conceptual Foresight Model to Investigate the Adoption of Radio Frequency Identification Technology in the English National Health Service

Radio Frequency Identification Technology (RFID) adoption in healthcare settings has the potential to reduce errors, improve patient safety, streamline operational processes and enable the sharing of information throughout supply chains. RFID adoption in the English NHS is limited to isolated pilot studies. Firstly, this study investigates the drivers and inhibitors to RFID adoption in the English NHS from the perspective of the GS1 Healthcare User Group (HUG) tasked with coordinating adoption across private and public sectors. Secondly a conceptual model has been developed and deployed, combining two of foresight’s most popular methods; scenario planning and technology roadmapping. The model addresses the weaknesses of each foresight technique as well as capitalizing on their individual, inherent strengths. Semi structured interviews, scenario planning workshops and a technology roadmapping exercise were conducted with the members of the HUG over an 18-month period. An action research mode of enquiry was utilized with a thematic analysis approach for the identification and discussion of the drivers and inhibitors of RFID adoption. The results of the conceptual model are analysed in comparison to other similar models. There are implications for managers responsible for RFID adoption in both the NHS and its commercial partners, and for foresight practitioners. Managers can leverage the insights gained from identifying the drivers and inhibitors to RFID adoption by making efforts to influence the removal of inhibitors and supporting the continuation of the drivers. The academic contribution of this aspect of the thesis is in the field of RFID adoption in healthcare settings. Drivers and inhibitors to RFID adoption in the English NHS are compared to those found in other settings. The implication for technology foresight practitioners is a proof of concept of a model combining scenario planning and technology roadmapping using a novel process. The academic contribution to the field of technology foresight is the conceptual development of foresight model that combines two popular techniques and then a deployment of the conceptual foresight model in a healthcare setting exploring the future of RFID technology.

Simulating the value of collaboration in multi-actor conservation planning

The loss of habitat and biodiversity worldwide has led to considerable resources being spent for conservation purposes on actions such as the acquisition and management of land, the rehabilitation of degraded habitats, and the purchase of easements from private landowners. Prioritising these actions is challenging due to the complexity of the problem and because there can be multiple actors undertaking conservation actions, often with divergent or partially overlapping objectives. We use a modelling framework to explore this issue with a study involving two agents sequentially purchasing land for conservation. We apply our model to simulated data using distributions taken from real data to simulate the cost of patches and the rarity and co-occurence of species. In our model each agent attempted to implement a conservation network that met its target for the minimum cost using the conservation planning software Marxan. We examine three scenarios where the conservation targets of the agents differ. The first scenario (called NGO-NGO) models the situation where two NGOs are both are targeting different sets of threatened species. The second and third scenarios (called NGO-Gov and Gov-NGO, respectively) represent a case where a government agency attempts to implement a complementary conservation network representing all species, while an NGO is focused on achieving additional protection for the most endangered species. For each of these scenarios we examined three types of interactions between agents: i) acting in isolation where the agents are attempting to achieve their targets solely though their own actions ii) sharing information where each agent is aware of the species representation achieved within the other agent’s conservation network and, iii) pooling resources where agents combine their resources and undertake conservation actions as a single entity. The latter two interactions represent different types of collaborations and in each scenario we determine the cost savings from sharing information or pooling resources. In each case we examined the utility of these interactions from the viewpoint of the combined conservation network resulting from both agents' actions, as well as from each agent’s individual perspective. The costs for each agent to achieve their objectives varied depending on the order in which the agents acted, the type of interaction between agents, and the specific goals of each agent. There were significant cost savings from increased collaboration via sharing information in the NGO-NGO scenario were the agent’s representation goals were mutually exclusive (in terms of specie targeted). In the NGO-Gov and Gov-NGO scenarios, collaboration generated much smaller savings. If the two agents collaborate by pooling resources there are multiple ways the total cost could be shared between both agents. For each scenario we investigate the costs and benefits for all possible cost sharing proportions. We find that there are a range of cost sharing proportions where both agents can benefit in the NGO-NGO scenarios while the NGO-Gov and Gov-NGO scenarios again showed little benefit. Although the model presented here has a range of simplifying assumptions, it demonstrates that the value of collaboration can vary significantly in different situations. In most cases, collaborating would have associated costs and these costs need to be weighed against the potential benefits from collaboration. The model demonstrates a method for determining the range of collaboration costs that would result in collaboration providing an efficient use of scarce conservation resources.

Simulating the value of collaboration in multi-actor conservation planning

The loss of habitat and biodiversity worldwide has led to considerable resources being spent on conservation interventions. Prioritising these actions is challenging due to the complexity of the problem and because there can be multiple actors undertaking conservation actions, often with divergent or partially overlapping objectives. We explore this issue with a simulation study involving two agents sequentially purchasing land for the conservation of multiple species using three scenarios comprising either divergent or partially overlapping objectives between the agents. The first scenario investigates the situation where both agents are targeting different sets of threatened species. The second and third scenarios represent a case where a government agency attempts to implement a complementary conservation network representing 200 species, while a non-government organisation is focused on achieving additional protection for the ten rarest species. Simulated input data was generated using distributions taken from real data to model the cost of parcels, and the rarity and co-occurrence of species. We investigated three types of collaborative interactions between agents: acting in isolation, sharing information and pooling resources with the third option resulting in the agents combining their resources and effectively acting as a single entity. In each scenario we determine the cost savings when an agent moves from acting in isolation to either sharing information or pooling resources with the other agent. The model demonstrates how the value of collaboration can vary significantly in different situations. In most cases, collaborating would have associated costs and these costs need to be weighed against the potential benefits from collaboration. Our model demonstrates a method for determining the range of costs that would result in collaboration providing an efficient use of scarce conservation resources.

Mobility changes in older age: neuropsychological, neurophysiological and cognitive predictors of successful adaptation in a real world scenario

The aims of this thesis were to investigate the neuropsychological, neurophysiological, and cognitive contributors to mobility changes with increasing age. In a series of studies with adults aged 45-88 years, unsafe pedestrian behaviour and falls were investigated in relation to i) cognitive functions (including response time variability, executive function, and visual attention tests), ii) mobility assessments (including gait and balance and using motion capture cameras), iii) motor initiation and pedestrian road crossing behavior (using a simulated pedestrian road scene), iv) neuronal and functional brain changes (using a computer based crossing task with magnetoencephalography), and v) quality of life questionnaires (including fear of falling and restricted range of travel). Older adults are more likely to be fatally injured at the far-side of the road compared to the near-side of the road, however, the underlying mobility and cognitive processes related to lane-specific (i.e. near-side or far-side) pedestrian crossing errors in older adults is currently unknown. The first study explored cognitive, motor initiation, and mobility predictors of unsafe pedestrian crossing behaviours. The purpose of the first study (Chapter 2) was to determine whether collisions at the near-side and far-side would be differentially predicted by mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function (including spatial planning, visual attention, and within participant variability) with increasing age. The results suggest that near-side unsafe pedestrian crossing errors are related to processing speed, whereas far-side errors are related to spatial planning difficulties. Both near-side and far-side crossing errors were related to walking speed and motor initiation measures (specifically motor initiation variability). The salient mobility predictors of unsafe pedestrian crossings determined in the above study were examined in Chapter 3 in conjunction with the presence of a history of falls. The purpose of this study was to determine the extent to which walking speed (indicated as a salient predictor of unsafe crossings and start-up delay in Chapter 2), and previous falls can be predicted and explained by age-related changes in mobility and cognitive function changes (specifically within participant variability and spatial ability). 53.2% of walking speed variance was found to be predicted by self-rated mobility score, sit-to-stand time, motor initiation, and within participant variability. Although a significant model was not found to predict fall history variance, postural sway and attentional set shifting ability was found to be strongly related to the occurrence of falls within the last year. Next in Chapter 4, unsafe pedestrian crossing behaviour and pedestrian predictors (both mobility and cognitive measures) from Chapter 2 were explored in terms of increasing hemispheric laterality of attentional functions and inter-hemispheric oscillatory beta power changes associated with increasing age. Elevated beta (15-35 Hz) power in the motor cortex prior to movement, and reduced beta power post-movement has been linked to age-related changes in mobility. In addition, increasing recruitment of both hemispheres has been shown to occur and be beneficial to perform similarly to younger adults in cognitive tasks (Cabeza, Anderson, Locantore, & McIntosh, 2002). It has been hypothesised that changes in hemispheric neural beta power may explain the presence of more pedestrian errors at the farside of the road in older adults. The purpose of the study was to determine whether changes in age-related cortical oscillatory beta power and hemispheric laterality are linked to unsafe pedestrian behaviour in older adults. Results indicated that pedestrian errors at the near-side are linked to hemispheric bilateralisation, and neural overcompensation post-movement, 4 whereas far-side unsafe errors are linked to not employing neural compensation methods (hemispheric bilateralisation). Finally, in Chapter 5, fear of falling, life space mobility, and quality of life in old age were examined to determine their relationships with cognition, mobility (including fall history and pedestrian behaviour), and motor initiation. In addition to death and injury, mobility decline (such as pedestrian errors in Chapter 2, and falls in Chapter 3) and cognition can negatively affect quality of life and result in activity avoidance. Further, number of falls in Chapter 3 was not significantly linked to mobility and cognition alone, and may be further explained by a fear of falling. The objective of the above study (Study 2, Chapter 3) was to determine the role of mobility and cognition on fear of falling and life space mobility, and the impact on quality of life measures. Results indicated that missing safe pedestrian crossing gaps (potentially indicating crossing anxiety) and mobility decline were consistent predictors of fear of falling, reduced life space mobility, and quality of life variance. Social community (total number of close family and friends) was also linked to life space mobility and quality of life. Lower cognitive functions (particularly processing speed and reaction time) were found to predict variance in fear of falling and quality of life in old age. Overall, the findings indicated that mobility decline (particularly walking speed or walking difficulty), processing speed, and intra-individual variability in attention (including motor initiation variability) are salient predictors of participant safety (mainly pedestrian crossing errors) and wellbeing with increasing age. More research is required to produce a significant model to explain the number of falls.