A Guideline for Decision-making on Business Intelligence and Customer Relationship Management among Clinics
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 8
Abstract
Business intelligence offers the capability to gain insights and perform better in decision-making by using a particular set of technologies and tools. A company’s success to a certain extent depends on customers. The complementary of business intelligence and customer relationship management will improve the efficiency of organizations, hence increase productivity and revenue. Most research works on implementation of business intelligence and customer relationship management in organizations commonly concentrate on architecture, framework, and maturity model. The process on how to implement business intelligence and customer relationship management in an organization, especially in smaller domains has not yet been clarified which make some organizations unclear on how to implement business intelligence and customer relationship management. Thus, this study investigates the process involved in the implementation of business intelligence and customer relationship management among clinics. An infographic guideline was developed based on the six process of data mining which is known as Cross Industry Standard Process for Data Mining. Four elements of business intelligence decision-making process which were gather, store, access, and analyze were also included in the process of developing the guideline. Findings from an expert’s review show that the increase of Content Validity Index was 0.7, from 0.3 during the first iteration to 1.0 in the second iteration. Therefore, this result is acceptable. The guideline appears to be a useful instrument for practitioners to implement business intelligence and customer relationship management in their clinics, however the process involved in developing the guideline could be improvised from time to time.
Authors and Affiliations
Nur Izzati Yusof, Norziha Megat Mohd. Zainuddin, Noor Hafizah Hassan, Nilam Nur Amir Sjarif, Suraya Yaacob, Wan Azlan Wan Hassan
Keywords
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- EP ID EP626816
- DOI 10.14569/IJACSA.2019.0100865
- Views 79
- Downloads 0
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