The full text of this article

 

Predictive business operations management
by Malu Castellanos, Norman Salazar, Fabio Casati, Umeshwar Dayal, Ming-Chien Shan
International Journal of Computational Science and Engineering (IJCSE), Vol. 2, No. 5/6, 2006

 

Abstract: The ability to forecast metrics and performance indicators for business operations is crucial to proactively avoid abnormal situations, and to do effective business planning. However, expertise is typically required to drive each step of the prediction process. This is impractical when there are thousands of metrics to monitor. Fortunately, for business operations management, extreme accuracy is not required. It is usually enough to know when a metric is likely to go beyond the normal range of values. This gives opportunity for automation. In this paper, we present an engine that completely automates the prediction of metrics to support a better management of business operations.

Online publication date: Wed, 08-Aug-2007

 

is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

 
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

 
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

 

    Username:        Password:         

Forgotten your password?


 
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

 
If you still need assistance, please email subs@inderscience.com