Ashly Titus

IT Application Section Head, Saudi Aramco Jubail Refinery Company (SASREF)

Overview

Founded in 1981 through an agreement between Petromin Corporation and Royal Dutch Shell plc, Saudi Aramco Jubail
Refinery Company (SASREF) has evolved into a major oil and gas company wholly owned by Saudi Aramco. 
Core values at SASREF are safety, people, ethics, and excellence. The company is making important strides in
protecting the environment. Among key business objectives are optimizing operational performance, achieving sustained cost leadership through transparency and accountability, and exploring cost-reduction opportunities. SASREF decided to overhaul the company’s whole business intelligence (BI) platform. It launched an enterprise-wide project endorsed under a corporate strategic initiative to support the overarching goal of becoming a data-driven organization.

Supernova Award Category

Data to Decisions

The Problem

Each department had developed its own homegrown reporting system, so data preparation for executives often involved manual consolidation of dozens of spreadsheets. After a few high-level strategic meetings went under supported, SASREF resolved to overhaul BI across the organization by empowering staff at all levels and in all functions to make informed decisions. The challenge was to deliver the right information at the right time to the right people – in all strategic encounters.

The Solution

The existing SAP® Business Warehouse (SAP BW), edition for SAP HANA® served as a central data consolidation layer for an array of IT and operational technology (OT) systems. SASREF used a license upgrade to deploy the SAP Analytics Cloud solution to support a modern analytics platform with a rich user experience and intelligent functions for self-service reporting. The project was implemented remotely due to the pandemic; even under that constraint, the system went live within the very ambitious timeline of six months.

The results

Using SAP BW and SAP Analytics Cloud helped SASREF create a cost-effective, clutter-free analytics platform with solutions returned to standard. It also let the company execute its cloud-first strategy by making the transition from a complex web of traditional reporting tools to one highly agile and powerful cloud reporting environment with 250 updated KPIs and 50 new dashboards. Integrating ERP data with operational data from the shop floor empowers SASREF to accurately track and monitor refinery operation KPIs.

Metrics

50% - Reduction in data preparation time for board meetings in just the first year

40% - Reduction in effort for corporate reporting; expected to improve in following years

100% - Return on investment realized; expected to 100% double by end of 2023

The Technology

SAP BW serves as the single source of truth and data-consolidation layer and is especially valuable for its direct connectivity to almost all major company data sources, including OT systems. 
SAP Analytics Cloud serves as presentation layer and  offers self-service through tracking and reporting on 250 KPIs, giving users built-in models for story creation and presenting actionable insights in a set of 50 attractive dashboards on a variety of devices. 

Disruptive Factor

The team chose a hybrid project management methodology – a classic waterfall approach for SAP BW and the SAP Activate methodology for SAP Analytics Cloud. To avoid delays due to contractual requirements, SASREF started the project on a proof-of-concept tenant for SAP Analytics Cloud, saving two months in the schedule. This tenant housed prototypes and development artifacts that were then moved to a production tenant. 

Shining Moment

The team achieved a successful go-live on time and within budget even amid the constraints of the pandemic.
The hybrid data and analytics architecture preserve existing investments while enabling innovation and agility through a robust cloud solution.
The cloud deployment brought a 100% decrease in IT operations and maintenance efforts for reporting.

IT Application Section Head

Submission Details

Year
Category
Data to Decisions
Result