ERP Implementation Key Performance Metrics (KPIs)


04 Feb

ERP (Enterprise Resource Planning) system cost is divided into two major parts: software cost and hardware cost. Software cost is depends upon many factors, number of users, implementation, customization, user training etc. After investing a huge amount on ERP project organization wants quick and better ROI. For SME, it is a significant decision.

Key Performance Metrics (KPIs) of ERP Implementation Investments in ERP project for organizations in the SME segment is an important decision. Hence the evaluation of an implementation and benefits accrued is an important factor in the overall success of an implementation project. Effectiveness of an implementation can be somewhat gauged by KPIs of business processes. KPIs are benchmarks with qualitative or quantitative values that help an organization assess the effectiveness of the processes that have been implemented in the ERP system. However it may not be suitable to expect important improvement in these values immediately after the implementation. An organization needs to give itself the time to take up the changes brought about in by the ERP system to practically achieve the KPI targets.

Examples of these metrics are as follows:

• What is the financial input necessary for achieving the targeted key performance level?
• What benefits the organization derives from a certain level of performance?
• Are the internal processes effective and efficient in assuring of performance?
• Does the new ERP system have sufficient potential for possible future customer needs?
• Measuring the monetary perspective, customer perspective, internal process perspective and human resource perspective goal
• Measure budget compliance hardware, software, training, and consulting goal
• Measure gamut of processes reduce bottlenecks
• Reduce Operational Problems: problems with customer order processing, problems with inventory processes, problems with standard reports
• Availability of the ERP system: average system availability, average downtime, and maximum downtime

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