Changing The Dynamics of Performance Management - The Micro KPI Concept

Abstract

Abstract The current volatility in the oil and gas sector underscores the importance of delivering consistent top quartile performance. To remain competitive, a robust performance management plan prior to drilling is key to successfully completing the project in time and under budget. Key Performance Indicators (KPIs) have historically been used to evaluate well construction performance. KPI targets are set to evaluate cost, time and quality of drilling operations. In The Shell Petroleum Development Company (SPDC), a benchmark method using the actual regional average performance data of similar wells drilled in the African region is used to generate high-level KPI targets (Macro KPIs) in terms of cost and time for ‘dry hole’ drilling. This method is recognised globally for target-setting and provides inputs used in forming a business plan. However, the use of Macro KPI targets to communicate performance requirements at the wellsite has been observed not to be as effective as required, since it does not clearly articulate performance required at the micro task level. It also does not allow effective real time monitoring of daily wellsite activities, making traditional performance monitoring retrospective. Micro KPIs are measures of smaller, repetitive actions that when added up, contribute a significant proportion of the time to drill a well. Breaking each phase of the drilling project into Micro KPIs (Tripping time, Running Tubular, BOP Testing and Handling, BHA Handling etc.) easily shows what it takes to win; what the sources of competitive advantage are; and what drives value. In order to make the transition from Macro to Micro KPI-based performance management flawless, the challenge of standardising Micro KPI target-setting needs to be addressed. This paper builds on the traditional performance management process, and by leveraging existing benchmark data, presents a process of generating and setting Micro KPIs for the drilling phase in an empirical and replicable manner.