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What's an
Executive Support System?
What's a ESS?
A ESS (or DSS more in general) is a software system under control of one of many decision-makers that assists in their activity of decision making by providing and organised set of tools intended to impart structure to portions of the decision making situation and to improve the ultimate effectiveness of the decision outcome".
Sharing the same concepts of a DSS, an ESS focuses more in the end-user requirements of maximum interactivity and user-friendlyness. An ESS can be understood as a friendly, fully customised and interactive DSS to be mostly used by top executives and policy-makers to get permanent and updated assessment in relation to key questions (information and knowledge).
While a complete DSS will have efficient links to external large databases and advanced models, an ESS focuses only on interactive and executive assessment tools, those which can be used personally by end-users. An ESS requires a previous expert work filtering information and knowledge into meaningful indicators and tools.
Because of ESS definition, its design and implementation must integrate future users as much as feasible, since a ESS represents both a challenge and an opportunity to improve their working processes. Although software development play an integral role in any Executive Support System design (and more in general in the Decision Support System world) the analysis of ESS and DSS is about how people think and make decisions Anyway a ESS will induce organisational changes which can not be succesful in complex institutions unless they are clearly preceived and desired since the begining. Recent developments on ESS and DSS tend to integrate the multiple decisions being taken by the institution, so they become Organisational DSS.
An ODSS is therefore a participative process, instead of a mandatory product. In the figure, the green circle represents the domain area of a typical Executive Support System.
| Rational decisions by "computers" | Emotional decision-makers ("people") |
| Start with the data: Almost free from prejudicies. | Start with a provisory solution to be validated and modified |
| Rational formulation | Adaptative behaviour |
| Large volums of information | Limited access to information |
| Inductive in-depth analysis | Intuitive-deductive search for "patterns" |
| Specialised: Sectorial analysis | Global: Multisectorial synthesis |
| Large volums of calculations, slow conclusions | Rapid expression of personal perceptions |
| Optimisation strategy from all possible solutions | Satisfying strategy based on "acceptable" possibilitie |
| Decision-making approaches | ||
| FUNCTIONAL-ECONOMIC | STRATEGIC-POLITICAL | |
| stakes | economic efficiency allocating scarce resources |
political interest |
| paramount objective | maximum marginal social benefit-cost |
create social consensus and social mobilization |
| goals | maximize users (travelers) utility and minimize externalities | maximize voters perception |
| issues | sectorial | multi-sectorial |
| timing | basically short-term | long-term in theory, short-term in most cases |
| framework | cost-benefit quantitative results | multi-party negotiation |
| period | transport projects | development paradigm | decision-making goals | decision-making leadership |
| Pre-Industrial | Military Roads and Ports | Colonization | Permanent territorial control | Military-Religious imposition |
| 1800-1900 Early Industrialization | Firsts Canals and Railways | Exogenous in National scale | Short-term private interest | Private iniciative |
| 1900-1975 Mass Industrialization | Developing National Transportation Networks | Exogenous International scale | Long-term development strategy | Political iniciative |
| 1975-1985 Industrial Crisis | Managing the existing transport capacity | Close endogenous | Short-term social-economic rationality | Bureaucratic rationality |
| >1985 Post Industrialization | International and Local Networks Development | Open endogenous | Permanent environmental and development negotiation | Social agreement |
| SCIENTIFIC ANALYSIS | EXPERT ANALYSIS | POLICY ANALYSIS |
| Evaluation Models (e.g. CBA,
Multicriteria...)
Forecast Models (e.g. 4-Steps)
Statistic Models (e.g. Linear regression) |
Explanatory Models Backcast Model Conceptual Models |
Policy Indicators |
Conceptual structure of an DSS (implications for an ESS)
Despite the particularities of each ESS, they share with more general DSS some fundamental elements: -Information system: Databases with consistent structure -Models to generate unknown information (e.g. Impacts of alternative decisions). In an ESS model should ideally be interactive and their results linked to policy relevant indicators. -Knowledge basis to put in a political context information and model's outcomes, and evaluate them. Policy actions are the result of adding purposes and goals to knowledge. -User-Interfaces The users of the ESS must ideally get friendly and customised access to information, models and knowledge (policy relevant indicators), according to their needs). Interactivity is a requirement to make "reinforcing learning" possible. Each module, and the links between them, require specific software and hardware solutions, which should be designed together by system’s experts and end-users.
Information component:
Giving structure to policy-relevant Data descriptors and indexes.
Models component:
Predicting impacts of policy actions in different overall scenarios to produce meaningful and consistent indicators to evaluate alternative policy actions.
Knowledge component
ESS knowledge-base could integrate few major elements:
-Policy indicators monitoring the impacts and needs of EU policies (calculated in the model base)
-Knowledge-based tools (e.g. Interactive models supporting policy evaluation).
-All other fuzzy knowledge elements which can not be encapsuled within strict "scientific methods"
User-friendly interface component
User-Interfaces must be adapted to end- users:
-ESS for top decision makers (which require already-made analysis in a friendly manner, but as well proper connections to other elements in the DSS)
-Experts (which requiere access to both data and models to carry on the analysis, but as well links to modelling tools and raw data in order to check and understand models formulation and data sources reliability). An ESS does not have "experts" as main target users.
More information:
For additional to ESS, DSS and ODSS issues click the
following key reference books:
G.M.Marakas "Decision Support Systems in the 21th Century",1999
G.M. Carter, M.P.Murray, R.G. Walker, W.E.Walker "Building Organisational Decision Support Systems", 1992
Turban E. & Aronson J.E. "Decision Support Systems and Intelligent Systems", 1998"Decision Support Systems and Intelligent Systems", 1998
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