A Framework for Embedding Analytics in a Business Process

Competition and cost pressures are creating the need for enterprises to innovate business processes to create new business value, increase operational efficiency, and detect and respond to organizational real time challenges. In order to achieve this, in the past, most organisations have automated t...

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Main Authors: SHANKARARAMAN, Venky, GOTTIPATI Swapna
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/2901
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spelling sg-smu-ink.sis_research-39012016-01-08T07:42:07Z A Framework for Embedding Analytics in a Business Process SHANKARARAMAN, Venky, GOTTIPATI Swapna, Competition and cost pressures are creating the need for enterprises to innovate business processes to create new business value, increase operational efficiency, and detect and respond to organizational real time challenges. In order to achieve this, in the past, most organisations have automated their manual processes using business process management technologies and enterprise systems. However, going forward, in order to stay competitive, organizations have to go beyond automating their processes, by making them more intelligent, by embedding analytics into their processes and business applications. In this paper, we propose "Analytics Driven Business Process Improvement (ADBPI) Framework" that provides a structure for how an organization can examine its current business process and enhance this process by embedding analytics within the process. 2015-07-13T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/2901 info:doi/10.1109/CBI.2015.10 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University business applications business processes embedded analytics framework process improvement Databases and Information Systems Management Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic business applications business processes embedded analytics framework process improvement
Databases and Information Systems
Management Information Systems
spellingShingle business applications business processes embedded analytics framework process improvement
Databases and Information Systems
Management Information Systems
SHANKARARAMAN, Venky,
GOTTIPATI Swapna,
A Framework for Embedding Analytics in a Business Process
description Competition and cost pressures are creating the need for enterprises to innovate business processes to create new business value, increase operational efficiency, and detect and respond to organizational real time challenges. In order to achieve this, in the past, most organisations have automated their manual processes using business process management technologies and enterprise systems. However, going forward, in order to stay competitive, organizations have to go beyond automating their processes, by making them more intelligent, by embedding analytics into their processes and business applications. In this paper, we propose "Analytics Driven Business Process Improvement (ADBPI) Framework" that provides a structure for how an organization can examine its current business process and enhance this process by embedding analytics within the process.
format text
author SHANKARARAMAN, Venky,
GOTTIPATI Swapna,
author_facet SHANKARARAMAN, Venky,
GOTTIPATI Swapna,
author_sort SHANKARARAMAN, Venky,
title A Framework for Embedding Analytics in a Business Process
title_short A Framework for Embedding Analytics in a Business Process
title_full A Framework for Embedding Analytics in a Business Process
title_fullStr A Framework for Embedding Analytics in a Business Process
title_full_unstemmed A Framework for Embedding Analytics in a Business Process
title_sort framework for embedding analytics in a business process
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/2901
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