Using Hypothesis Testing to Evaluate Key Performance Indicators in Real Time: An Edge Computing Use Case

2019 ◽  
Author(s):  
Peter Kowalchuk
Keyword(s):  
Hypothesis Testing ◽  
Real Time ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Edge Computing ◽  
Use Case

Implementation of a Digital Roadmap with Best-in-Class Applications

2021 ◽  
Author(s):  
John McIntosh ◽  
Renata Martin ◽  
Pedro Alcala ◽  
Stian Skjævesland ◽  
John Rigg
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Third Party ◽  
Commercial Application ◽  
Time Data ◽  
Operating Model ◽  
Wide Range ◽  
Real Time Data

Abstract The paper describes a project known internally as "InWell" to address multiple requirements in Repsol Drilling & Completions. InWell is defined by a new Operating Model comprising Governance, People, Process, Functions and Technology. This paper addresses changes to the Technology element - often referred to as "Digitalization". The paper includes a discussion about the business transformation strategy and case studies for addressing three of 18 functionalities identified in the first round of development. The InWell development strategy followed four steps; identification of performance issues, envisioning of a future operating model, identification of functionalities required/supporting this operating model and matching to digital solutions. Our case studies focus on three functionalities provided by three separate companies, Unification of Planning and Compliance, Real Time Data aggregation and Key Performance Indicators. Each functionality was addressed with an existing commercial application customized to meet specific requirements. A corporate web-based Well Construction Process (WCP) was initially piloted and then extended to include all well projects. The WCP identifies the key Tasks that must be completed per project, and these are all tracked. Data from this application is used by a third-party Business Analytics application via an API. Real time data from many sites and a wide range of sources was aggregated and standardized, Quality Controlled and stored within a private secure cloud. The data collation service is an essential building block for current third-party applications such as the operating centre and is a prerequisite for the goal of increased automation. A suite of Operator specific Key Performance Indicators (KPIs) and data analytics services were developed for drilling and completions. Homogenized KPIs for all business units provide data for objective performance management and apples-to-apples comparison. Results are presented via custom dashboards, reports, and integrations with third party applications to meet a wide range of requirements. During a four-month Pilot Phase the InWell Project delivered € 2.5 million in tangible savings through improvements in operational performance. In the first 12 months € 16 million in savings were attributed to InWell. By 2022 forecast savings are expected to exceed € 60 million (Figures 1 & 2). The value of Intangible benefits is thought to exceed these objective savings. Figure 1 The Business Case for InWell – Actual & Projected Savings and Costs. Figure 2 InWell Services addressing Value Levers and quantified potential impact. A multi-sourced digital strategy can produce quick gains, is easily adapted, and provides high value at low risk. The full benefit of digital transformation can only be realised when supported by an effective business operating model.

scholarly journals On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities

2020 ◽  
Vol 11 (1) ◽  
pp. 181
Author(s):  
Carmen Botella-Mascarell ◽  
Joaquin Perez ◽  
Juan Soria ◽  
Sandra Roger
Keyword(s):  
Network Management ◽  
Communication Networks ◽  
Mobile Communications ◽  
Performance Indicators ◽  
Data Science ◽  
Mobile Network ◽  
Key Performance Indicators ◽  
Composite Indicators ◽  
Use Case ◽  
Universal Mobile Telecommunications System

Beyond 5G networks will be fundamental towards enabling sustainable mobile communication networks. One of the most challenging scenarios will be met in ultra-dense networks that are deployed in densely populated areas. In this particular case, mobile network operators should benefit from new assessment metrics and data science tools to ensure an effective management of their networks. In fact, incorporating architectures allowing a cognitive network management framework could simplify processes and enhance the network’s performance. In this paper, we propose the use of composite indicators based on key performance indicators both as a tool for a cognitive management of mobile communications networks, as well as a metric which could successfully integrate more advanced user-centric measurements. Composite indicators can successfully synthesize and integrate large amounts of data, incorporating in a single index different metrics selected as triggers for autonomous decisions. The paper motivates and describes the use of this methodology, which is applied successfully in other areas with the aim of ranking metrics to simplify complex realities. A use case that is based on a universal mobile telecommunications system network is analyzed, due to technology simplicity and scalability, as well as the availability of key performance indicators. The use case focuses on analyzing the fairness of a network over different coverage areas as a fundamental metric in the operation and management of the networks. To this end, several ranking and visualization strategies are presented, providing examples of how to extract insights from the proposed composite indicator.

scholarly journals Demand-side management strategies based on energy key perfomance indicators in real-time: Case study

2020 ◽  
Vol 10 (1) ◽  
pp. 5-16
Author(s):  
Sandra Milena Tellez- Gutierrez ◽  
Oscar German Duarte Velasco ◽  
Javier Rosero García
Keyword(s):  
Real Time ◽  
Performance Indicators ◽  
Energy Savings ◽  
New Technologies ◽  
Management Strategies ◽  
Demand Side Management ◽  
Key Performance Indicators ◽  
Demand Side ◽  
Advanced Metering

This paper sets out features of traditional Energy Key Performance Indicators (KPIs) employed in energy management programs; then, new indicators are proposed based on Advanced Metering Infrastructure (AMI) usage. These indicators make it possible to directly relate the amount of energy, type of end use and user consumption patterns. Analysis of AMI system information enables planning for differentiated Demand-Side Management (DSM) strategies. A case study developed at Universidad Nacional de Colombia - Bogotá campus is presented, which proposes new Energy Key Performance Indicators in Real Time. These indicators enable information analysis and DSM strategies that are appropriate for new technologies and that are aimed at increasing energy efficiency. Additionally, this paper presents the factors that have to be taken into account when implementing KPIs (Key Performance Indicators) and the decision-making process. This results in variable overall energy savings between 5 and 40%, according to the DSM strategy implemented.

scholarly journals ANALISIS PENGARUH KEY PERFORMANCE INDICATOR, PENETAPAN TARGET PAJAK, DAN JOB GRADE SYSTEM TERHADAP KINERJA KARYAWAN KPP PRATAMA KEBUMEN

1970 ◽  
Vol 7 (1) ◽  
Author(s):  
Gunarso Wiwoho
Keyword(s):  
Hypothesis Testing ◽  
Multiple Regression ◽  
Performance Indicators ◽  
Quantitative Methods ◽  
Performance Indicator ◽  
Employee Performance ◽  
Key Performance Indicators ◽  
Grade System ◽  
Clear Understanding ◽  
Key Performance Indicator

The management performance is a process of ongoing communication which involves building hope and clear understanding of work functions that expect to be done by employees and how they give contribution to organizational goals. Employee performance in any organization is always running fluctuatively. It needs requiring the performance growth including in The tax Servicing Office (LTO) Pratama that influenced by the application of ‘key performance indicators, attention toward the tax decision and job grade system (system peningkatan pekerjaan) which has long been applied in the KPP Pratama Kebumen. The existence of this is the writer background to do the research titled ‘The Effect Analysis of ‘Key Performance Indicators, Tax Target Decision and Job Grade System toward The Employee Performance at The Tax Servicing office (Kantor Pelayanan Pajak (KPP)) Pratama Kebumen’ The respondents were 30 employees who work at KPP Pratama Kebumen. The research uses descriptive method and quantitative analysis by SPSS 16:00. By quantitative methods, It tested by validity, reliability, the assumptions of classical testing, the analysis of multiple regression, hypothesis testing by using the test ‘t’ or test ‘f’. The hypothesis testing of the test ‘t’ shows that all variables have a significant effect on the performance except for the variable application of key performance indicators. Whereas the test ‘f’ results that the application of key performance indicator, tax target decision and job grade systems that have a significant effect to the employee performance of KPP Pratama Kebumen. Key words: the application of key performance indicators, tax target decision, job grade system, employee performance, multiple regression.

Digitalization for Effective Performance Management Using Key Performance Indicators in Miscible Gas Injection Projects in South Oman

2021 ◽  
Author(s):  
Kamlesh Kumar ◽  
Tushar Narwal ◽  
Zaal Alias ◽  
Pankaj Agrawal ◽  
Ali Farsi ◽  
...  
Keyword(s):  
Performance Management ◽  
Real Time ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Production Optimization ◽  
Utilization Efficiency ◽  
Analysis Tool ◽  
Time Data ◽  
Short Term ◽  
Web Based

Abstract South Oman has several pre-Cambrian reservoirs that are highly pressured (400-1000 bar), deep (3-5 km) and critically sour (H2S up to 10%). The combined STOIIP of these reservoirs makes it one of the largest gas EOR projects in the world. The objective here is to highlight the key performance indicators and digitalization techniques used for continuous and effective well, reservoir and facility management (WRFM) and production optimization, while honoring the facility constraints and gas export requirements. Real time pressure data such as tubing head pressures, injection/production rates along with other data including maps, static pressures and production logs are used to define an appropriate set of performance metric at various levels, e.g. reservoir, sector or well. Digitalization of surveillance data helps in real time production optimization such as offtake management based on creaming curves according to gas sink availability and facility constraints. Key business performance indicators include gas utilization efficiency; MGI performance indicators include incremental oil, throughput, instantaneous and cumulative voidage replacement ratios, gas breakthrough level and time, ratio of reservoir pressure to the target minimum miscibility pressure; and facility constraints are optimized through gas balance, along with tracking field performance against the initial FDP forecasts. Real time performance data is tracked using a commercial Real-Time Data Analysis tool (RTDA) and Database Analytics Visualization Tool (DAVT), with surveillance indicators targeted at well, reservoir and facility level. The above-defined Key Performance Indicators (KPI) are tracked against predictions from the field development plan in web-based portal developed at PDO (Nibras). Digitalization has enabled quick and effective monitoring of these KPI, short-term optimization of injection distribution and offtake rates to maximize oil production and overall value within facilities constraints and varying export gas commitments based on South Oman Gas Line (SOGL) network optimization. Using dimensionless plots and a standardized set of parameters help in developing a common understanding and benchmarking the MGI reservoir response with analogs and amongst different reservoirs. This work presents a set of performance KPIs and short-term optimization methodology using digitalization and LEAN framework that are tracked in a web-based portal, RTDA and DAVT. It provides means to facilitate offtake decisions to meet variable export requirements while honoring facilities constraints, assess reservoir performance, providing valuable insights that helps in speedy reservoir management decisions. This process has been replicated across PDO for all related MGI projects and can benefit other development types, e.g. chemical/steam injection.

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