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Supporting Business Decision-making: One Professional at a Time

Bednar, Peter LU ; Welch, Christine and Imrie, Peter (2014) In DSS 2.0 – Supporting Decision Making with New Technologies 261. p.471-482
Abstract
This paper discusses the potential for personalized, user-owned decision-support systems. It can be readily seen that there are benefits from analysis of ‘Big Data’ that could not be attained through more traditional means, e.g. insurance and credit card fraud can be detected more readily when it is possible to analyze integrated data across multiple servers owned and controlled by separate organizations. However, high-level data analysis, though useful, cannot be trusted to provide all the answers to organizational ‘questions’. Individuals need to be able to inform themselves in complex decision situations and for this purpose there can be no substitute for ‘little data’ from wherever this is to be drawn. We explore a potential type of... (More)
This paper discusses the potential for personalized, user-owned decision-support systems. It can be readily seen that there are benefits from analysis of ‘Big Data’ that could not be attained through more traditional means, e.g. insurance and credit card fraud can be detected more readily when it is possible to analyze integrated data across multiple servers owned and controlled by separate organizations. However, high-level data analysis, though useful, cannot be trusted to provide all the answers to organizational ‘questions’. Individuals need to be able to inform themselves in complex decision situations and for this purpose there can be no substitute for ‘little data’ from wherever this is to be drawn. We explore a potential type of support that could overcome the barriers to professional creativity arising through lack of trust in decision-support systems owned and controlled from senior management. The Virtual Personal Assistant described uses natural language processing to interact with a professional user in the context of messy, situated problems, and in private. It has capability to learn from user-interactions and therefore to co-evolve contextually. A ‘little data’ system such as this can therefore help to improve relevance of user understandings in a relatively risk free environment. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Virtual Assistant, Little Data, Personalized Support Technology, Natural Language Processing, Contextual Inquiry, Situated Problems, Professional Support, User Owned Decision Support, User Controlled Support, Information System, Decision Support System, Personal decision-support systems, virtual personal assistant, contextual dependencies
in
DSS 2.0 – Supporting Decision Making with New Technologies
editor
Phillips-Wren, Gloria; Carlsson, Sven; Respício, Ana and Brézillon, Patrick
volume
261
pages
471 - 482
publisher
IOS Press
external identifiers
  • Scopus:84902250222
ISBN
978-1-61499-398-8
978-1-61499-399-5
DOI
10.3233/978-1-61499-399-5-471
language
English
LU publication?
yes
id
1d9b6c2c-a0cc-4dbc-8c7b-4b09babf0e1b (old id 4452093)
date added to LUP
2014-06-02 16:01:36
date last changed
2016-10-13 04:41:04
@misc{1d9b6c2c-a0cc-4dbc-8c7b-4b09babf0e1b,
  abstract     = {This paper discusses the potential for personalized, user-owned decision-support systems. It can be readily seen that there are benefits from analysis of ‘Big Data’ that could not be attained through more traditional means, e.g. insurance and credit card fraud can be detected more readily when it is possible to analyze integrated data across multiple servers owned and controlled by separate organizations. However, high-level data analysis, though useful, cannot be trusted to provide all the answers to organizational ‘questions’. Individuals need to be able to inform themselves in complex decision situations and for this purpose there can be no substitute for ‘little data’ from wherever this is to be drawn. We explore a potential type of support that could overcome the barriers to professional creativity arising through lack of trust in decision-support systems owned and controlled from senior management. The Virtual Personal Assistant described uses natural language processing to interact with a professional user in the context of messy, situated problems, and in private. It has capability to learn from user-interactions and therefore to co-evolve contextually. A ‘little data’ system such as this can therefore help to improve relevance of user understandings in a relatively risk free environment.},
  author       = {Bednar, Peter and Welch, Christine and Imrie, Peter},
  editor       = {Phillips-Wren, Gloria and Carlsson, Sven and Respício, Ana and Brézillon, Patrick},
  isbn         = {978-1-61499-398-8},
  keyword      = {Virtual Assistant,Little Data,Personalized Support Technology,Natural Language Processing,Contextual Inquiry,Situated Problems,Professional Support,User Owned Decision Support,User Controlled Support,Information System,Decision Support System,Personal decision-support systems,virtual personal assistant,contextual dependencies},
  language     = {eng},
  pages        = {471--482},
  publisher    = {ARRAY(0x83c62d0)},
  series       = {DSS 2.0 – Supporting Decision Making with New Technologies},
  title        = {Supporting Business Decision-making: One Professional at a Time},
  url          = {http://dx.doi.org/10.3233/978-1-61499-399-5-471},
  volume       = {261},
  year         = {2014},
}