企業導入資料倉儲績效評估準則之探討

A study on the Performance Estimating Model For Enterprises with Data Warehouse

張欣義(Hsin-Yi Chang)

指導教授 ： 黃遵鉅

大同大學/經營設計學院/資訊經營學系所/碩士(2007年)

摘要

隨著資訊科技的迅速發展和企業決策支援系統的迫切需求，在短短的幾年內將資料倉儲從純粹的理論迅速轉化為決策支援領域中一種具豐富實用性的技術，企業導入資料倉儲來輔助企業流程或是輔助決策的情形越來越普遍。然而資料倉儲的建置是一項複雜、高風險且昂貴的投資，放眼國內外論文期刊，多為如何建立規劃優良的資料倉儲系統，極少針對資料倉儲系統建置後的使用情況進行評估。企業實在需要一套適合的績效評估方法，以評估其導入資料倉儲的營運績效！
本研究運用「平衡計分卡」多構面的績效評估觀點，並經由文獻的探討與專家學者的訪談中，建立評估導入資料倉儲的績效指標，在財務構面有二十個、在顧客構面有十九個、在內部流程構面有二十一個、在學習與成長構面有十四個，總計有七十四個績效衡量指標；透過第一階段問卷調查，以敘述統計方法篩選四構面的關鍵績效指標，在財務構面有四個、在顧客構面有七個、在內部流程構面有六個、在學習與成長構面有四個，總計有二十一個關鍵績效衡量指標；透過第二階段問卷調查，以層級分析法來分析確認四構面及關鍵績效指標的權重分配，財務構面為 0.23 、顧客構面為0.37 、內部流程構面為0.27 、學習與成長構面為0.13 ，並利用這些評量指標及權重來建立企業導入資料倉儲績效評估評量表；此研究成果不僅可提供企業作為實際評估資料倉儲營運績效之用，亦可作為後續學者研究之參考。

關鍵字

資料倉儲 ； 績效評估 ； 平衡計分卡

並列摘要

Along with the rapid expansion of information technology and the urgent demand of Decision Support System, only in a few years, data warehouse have been converting absolute theory into practical technology. more and more enterprises have been plunging into the data warehouse for supporting business process and decisions.However, the implementation of data warehouse is complicated, risky and apparently expensive. To take a brand view , most of related articles were found discuss about how to establish data warehouse fine, but performance evaluation of data warehouse is little. The enterprises indeed need Performance Evaluation to estimate the effects of operation in data warehouse.
This study sets up ways to estimate Performance Evaluation of data warehouse by using diverse Performance Evaluation of Balanced Scorecard. Also, it sets up a standard based on literature review and interviews with researchers of enterprises. There are 20 indicators in financial perspective, 19 indicators in customer perspective, 21 indicators in internal process perspective, and 14 indicators in learning and growth perspective. Through the first questionnaire,using descriptive statistics to sift the Key Performance Indicators of four perspectives, 4 indicators in financial perspective, 7 indicators in customer perspective, 6 indicators in internal process perspective, and 4 indicators in growth and earning perspective. Through the second questionnaire, using AHP application to measure the weights of the key performance factors, according to the research result, the weight of the factor “financial perspective” is 0.23 , the weight of the factor “customer perspective” is 0.37 , the weight of the factor “internal process perspective” is 0.27 and the weight of the factor “learning and growth perspective” is 0.13 , then create the balanced scorecard of Performance Estimating Model for Enterprises with data warehouse. The results of this study both provides practical estimate of Performance Evaluation in data warehouse and is worth investigating in the future.

並列關鍵字

Data Warehouse ； Performance Estimating ； BSC

參考文獻

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