企業導入大數據分析系統的流程與影響因素之探討

Abstract

隨著科技的發展，大數據所帶來的潛在機會與影響越來越受到企業與研究者的重視，麥肯錫（McKinsey）顧問公司早在2011年就曾發表文章，說明「大數據是下一個創新、競爭、及生產力的先鋒代表」。儘管數據分析富含巨大的商業價值，企業亦明白數據分析可以帶來的潛在價值，但是企業該如何有效導入大數據分析系統並發揮其價值，仍是一大挑戰。本論文主要的目的即是針對此一重要議題進行探討。\n本研究針對大數據分析的概念、資訊系統導入流程與關鍵成功因素等文獻進行探討與整理，進而提出一個包含「組織管理」、「參與人員」、「科技系統」、「資訊系統導入流程」與「導入成效與價值」等五構面的研究架構，其中導入流程包括：「導入階段」、「執行階段」與「後執行階段」。接著選擇一家代表性的公司，進行深入的質性個案研究。所得到的主要研究結論如下：\n結論一：企業導入大數據分析系統時，在執行階段會採取近似敏捷式管理與做 中學的方式；而在後執行階段，則會透過經驗與產業知識的累積，以逐步發揮成效。\n結論二：企業導入大數據分析系統時，會強調資料的正確性與資料定義的釐清。也會強調累積知識的儲存、更新與安全性。\n結論三：企業導入大數據分析系統時，在流程上，會透過適時地重新設計流程與汰換工具以強化流程再造。也會強調系統工具轉換時的檢查。\n結論四：企業導入大數據分析系統時，其數據分析團隊成員的IT技術與商業洞察都是很關鍵的能力。\n結論五：企業在導入大數據分析系統時，高階主管的支持，不論是在導入前、執行或後執行階段，皆扮演重要的角色。\n結論六：企業導入大數據分析系統時，特別在執行階段與後執行階段，其企業流程再造會影響系統運作的效率與跨部門間的合作。\n本研究最後並提出實務上的意涵與後續研究的建議。

With the ever-changing nature of technology, advanced analytics are capable of extrapolating data from a wide range of source to predict future outcomes with amazing accuracy. McKinsey had published an article in 2011 stating that " Big data: The next frontier for innovation, competition, and productivity ". Big data is invaluable to today’s businesses, but how to effectively introduce big data analysis system and achieve productive result is still a major challenge facing companies. The main purpose of this research is to investigate this important issue.\nBased on the literature review of big data, key success factors and the process of information system implementation, this research originally proposed a conceptual framework which includes five construct: organization management, participants, technology, process of information system implementation and effectiveness and value of implement. There’re three stage of information system implementation, pre-implementation phase, implementation phase and post-implementation phase. This research chooses a representative company for in-depth interviews. The preliminary conclusions through the case study are as below:\nConclusion 1: When companies introduce big data analysis systems, they will adopt agile management and learning by doing approaches in the implementation stage; in the post-implementation stage, they will use the accumulation of experience and industry knowledge to gradually achieve results.\nConclusion 2: When companies import big data analysis systems, they will emphasize the correctness of data and the clarification of data definitions. It will also emphasize the storage, update and security of knowledge.\nConclusion 3: When an enterprise introduces a big data analysis system, the process reengineering will be strengthened by redesigning the process and replacing tools. It also emphasizes the examination when the system tool is converted.\nConclusion 4: When an enterprise introduces a big data analysis system, IT technology and business insights are all critical capabilities, based the insights of data analysis team members.\nConclusion 5: When an enterprise introduces a big data analysis system, it will be affected by the attitude of the senior executives. The support of the senior executives plays an important role in the pre- implementation, implementation, or post-implementation phase.\nConclusion 6: When an enterprise introduces a big data analysis system, especially in the implementation phase and the post- implementation phase, its business process reengineering will affect the efficiency of system and cross-functional communication.