MIS and Illusions of Control: An Analysis of the Risks of Risk Management

2011 ◽  
Vol 26 (4) ◽  
pp. 259-267 ◽  
Author(s):  
Helga Drummond
Keyword(s):  
Risk Management ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Illusion Of Control ◽  
Control Analysis ◽  
Discussion Paper ◽  
The Subject ◽  
High Level ◽  
New Literature

Dysfunctional MIS is an important topic but one that has received comparatively little attention in the literature. This discussion paper attaches new literature to the subject. The new literature centres upon the epistemological status of certain forms of MIS. More specifically, it is argued that MIS, based upon metonymy (part for whole substitution), can seriously mislead managers because the representation gets mistaken for the reality. The demonstration is based on high level risk registers. Risk registers were selected for analysis because they are ubiquitous and important decision support systems. In theory, diligent use of risk registers should virtually eliminate unpleasant surprises. In practice, the result may be an illusion of control. Analysis draws upon sociology and psychology to explain why this may be so.

scholarly journals Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elizabeth Ford ◽  
Natalie Edelman ◽  
Laura Somers ◽  
Duncan Shrewsbury ◽  
Marcela Lopez Levy ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
General Practitioners ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structured Interview ◽  
Qualitative Interview Study ◽  
High Level

Abstract Background Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.

Seasonal forecasts of discharge in the Upper Danube upstream of Vienna

2020 ◽  
Author(s):  
Ignacio Martin Santos ◽  
Mathew Herrnegger ◽  
Hubert Holzmann ◽  
Kristina Fröhlich ◽  
Jennifer Ostermüller
Keyword(s):  
Risk Management ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Meteorological Data ◽  
Seasonal Forecast ◽  
Drought Risk ◽  
Seasonal Forecasts ◽  
Climate Services ◽  
Climate Forecasts

<p>In the last years, the demand of reliable seasonal streamflow forecasts has increased with the aim of incorporating them into decision support systems for e.g. river navigation, power plant operation  or drought risk management. Recently, the concept of “climate services” has gained stronger attention in Europe, thereby incorporating useful information derived from climate predictions and projections that support adaptation, mitigation and disaster risk management. In the frame of one of these climate services currently in development, Clim2Power project, a seasonal forecast system for discharge in the Upper Danube upstream Vienna has been established.</p><p>Seasonal forecasts are generated using a dynamical approach running a hydrological model (COSERO) with forecasted climate input provided by DWD (Germany's National Meterological Service). The climate forecasts are based on a large ensemble of predictions, available up to 6 months. After the application of a statistical downscaling method, the climate forecasts have a spatial resolution of 6km. The predictability is related to two main contributions: meteorological forcings (i.e. temperature and precipitation predictability) and initial basin states at the time the forecast is issued.</p><p>The Upper Danube basin with a catchment area of approx. 100.000 km<sup>2</sup> is characterized by complex topography dominated by the Alps, elevations range from about 150 m to slightly under 4000 m. Therefore, the skill of the seasonal forecast is highly influenced by the resolution of the meteorological data, and likewise by the hydrological processes that take place, especially, regarding melting processes. Downscaled hindcasts over the last 20 years, generated with the identical setup as the seasonal forecasts, are used in this contribution to assess the skill of the seasonal forecasts. In addition, some post-processing corrections, based on historical observations, are used to adjust the bias of the forecasts. Nevertheless, remaining non-systematic error patterns do not allow complete bias correction. Apart from the biases, also the correlation patterns show a limited skill. We conclude that the seasonal discharge forecasting is still not sufficient to incorporate the results into water resources decision support systems within the studied Alpine basins.</p>

Prioritization of IT Product Backlog Items Using Decision Support Systems

2020 ◽  
Vol 26 (11) ◽  
pp. 631-640
Author(s):  
T. K. Kravchenko ◽  
◽  
S. N. Bruskin ◽  
D. V. Isaev ◽  
E. V. Kuznetsova ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Group Decision ◽  
Support Systems ◽  
Problem Situations ◽  
User Stories ◽  
Different Types ◽  
High Level ◽  
Support Methods

The article focuses on the application of decision support systems for prioritization of product backlog items in IT projects implemented using the Scrum methodology. The study identified the features of prioritization of different types of the product backlog items — user stories, epics and themes. It is justified that high-level product backlog items (epics and themes) require comprehensive prioritization, due to the following reasons. First, high-level product backlog items are particularly important because they determine the planning and implementation of detailed user stories within individual sprints. Second, any high-level item can be considered in terms of different criteria. Third, the implementation of epics and themes takes longer time compared to the implementation of user stories, so it is necessary to take into account possible future states of the project's environment. Fourth, prioritizing epics and themes requires increased objectivity and validity, so group decision making with participation of several experts seems reasonable. Taking into consideration the aforementioned features the conclusion regarding limitations of existing methods of prioritization is made. It is argued that prioritization of high-level product backlog items (epics and themes) may be performed using multi-criteria decision making methods with availability of several problem situations (possible future states of the environment), as well as involvement of several experts. The idea of applying decision support methods and systems is illustrated on the appropriate example. It is also argued that increased consumption of time and resources related with setting and solving decision support tasks may be considered as acceptable for high-level product backlog items.

Historical Overview of Decision Support Systems (DSS)

2011 ◽  
pp. 1753-1758 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
United States Of America ◽  
Support Systems ◽  
The United States ◽  
Future Trends ◽  
Historical Overview ◽  
Essential Information ◽  
Organizational Perspective ◽  
The Subject

During the late 1970s the term “decision support systems” was first coined by P. G. W. Keen, a British Academic then working in the United States of America. In 1978, Keen and Scott Morton published a book entitled, Decision Support Systems: An Organizational Perspective (Keen & Scott Morton, 1978), wherein they defined the subject title as computer systems having an impact on decisions where computer and analytical aids can be of value but where the manager’s judgment is essential. Information systems (IS) researchers and technologists have developed and investigated decision support systems (DSS) for more than 35 years (Power, 2003b). The structure of this article is as follows: The background to DSS will be given. Some DSS definitions, a discussion of DSS evolution, development of the DSS field and frameworks are then presented. Some future trends for DSS are then suggested.

Sign in / Sign up

Export Citation Format

Share Document