Qlik > Case Studies > ENI keeps production under control

ENI keeps production under control

Customer Company Size

Large Corporate

Region

Europe

Country

Italy

Product

Qlik Sense
Qlik GeoAnalytics
New Flash

Tech Stack

Data Visualization
Geographical Data Analysis

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Digital Expertise

Technology Category

Application Infrastructure & Middleware - Data Visualization
Analytics & Modeling - Real Time Analytics

Applicable Industries

Oil & Gas

Use Cases

Real-Time Location System (RTLS)
Supply Chain Visibility

Services

Data Science Services

About The Customer

ENI is a multinational company involved in the extraction of natural gas and oil. The company owns more than 160 extraction plants located worldwide. These plants send performance and operations data on a daily basis. The equity of the company is equivalent to the value of the total average daily production of 1.8 million barrels of oil. The company's upstream activities are complex and require constant monitoring and management. The company's objective is to improve the timeliness, quality and granularity of the data from these plants for better managerial decision making.

The Challenge

ENI’s upstream activities are complex with more than 160 natural gas and oil extraction plants located worldwide sending performance and operations data on a daily basis. Keeping track of the overall situation is essential for managing maintenance operations and ensuring that the company reaches its targets. Without a dedicated platform, the data sent by the plants used to be collected via email and analyzed manually, using standard spreadsheets and occupying vast amounts of time and resources. Managers were only able to see an overview of production towards the end of the working day, via a PDF sent by email, with limited possibility for in-depth analysis. ENI needed to improve the control and analysis of this information, not so much for operations but for managerial purposes. The objective was to improve the timeliness, quality and granularity of the data, seeking to create a platform that provided a good customer experience and also enabled the analysis of historical data to allow managers to monitor performance more effectively.

The Solution

ENI, already a QlikView user, embarked on an extensive and demanding project to develop a dashboard in the form of a web application known internally as New Flash. The dashboard was intended for over 1,000 users, including workers, managers and senior company managers. The objective was to make it possible to easily and instantaneously consult the performance data provided by the sites, as well as analyze and compare targets and historical data. This led to the development of an integrated solution that provides, at a single glance, a complete progress overview of the resource extraction process and CO2 emissions worldwide, updated in near real-time. The data can be viewed by ‘field’ (the individual plant), ‘asset’ (a group of plants), or by geographical area. All of which is aggregated and subdivided into oil or gas. Making use of Qlik GeoAnalytics technology, ENI then added the option to locate assets on a map of the territory, using color-coding to quickly identify different situations at all plants.

Operational Impact

The new solution represents a generational leap compared to the previous operational methods, both in terms of the analysis potential (rapid and immediate drill-down and effective comparison with target or historical data) and information quality.
It also updates frequently which, despite not being in real time is very close (the managers used to receive the PDF in the evenings, whereas now the data is available from early afternoon), and a very appealing user interface.
As is often the case in large organizations, the solution developed with Qlik Sense has also been welcomed by other departments within the company, such as the logistics department that monitors the routes of ships and aircraft, and the engineering department, which is looking into similar applications.

Quantitative Benefit

Production data is now available from early afternoon instead of the evening
The elimination of manual data operations has reduced errors and freed up resources
The information is geographically referenced and can be analyzed via an effective drill-down capability