Oracle based Master Data Management solution is a Master Data Management (MDM) application used by many companies.
MDM consists of several platforms and technologies that consolidate, clean and support enterprise master data, and it therefore synchronizes all platforms, operational processes and analytical tools (Oracle, 2011). As a result, the MDM enhances operational efficiency, reporting and supports fact-based decision-making in organisations.
Description of the company using it
The National Oil Company of Abu Dhabi Company for Onshore Oil Operations (ADCO) has implemented Oracle based MDM for its operations.
Established in 1971, ADCO operates onshore and in shallow coastal water of the Emirate of Abu Dhabi. The company strives to achieve highest standards in performance, develop technical knowhow for its complex business processes, enhance efficiency, optimum development of reservoir, ensure integrity in business practices and embrace technologies and strategies to support field operations and developments.
Oracle noted that ADCO was experiencing critical data management issues, including “corporate data governance, corporate performance management and business intelligence hurdles” (Oracle, 2012). At the same time, the company needed to collect and analyse exploration and production data on a real time basis to enhance management of enterprise data on a single application with known definitions and standards.
Purpose of use
The main purpose of deploying Oracle based MDM at ADCO was to enhance operational efficiency, save costs and improve decision-making by relying on data. ADCO developed and installed the platform alongside the Professional Petroleum Data Management (PPDM) data model supported by Oracle Database application. The system was developed as a part of the high performance solution for data.
The solution was also going to provide a single platform for data access. This enhanced a holistic view of operations such as drilling and production data and improved greater management of data.
Ultimately, the solution created one source of business information for the company.
Main functionality of the Enterprise Resource Planning
To achieve its integrated role, Oracle MDM had to meet certain provisions. First, the solution had to profile data. It aimed to manage data centrally. Therefore, all systems that updated or created data had to be checked to ensure high quality data and any deviation from the expected data had to be analysed and corrected. In this case, data completeness and ongoing data quality assurance were mandatory.
Second, the MDM had to consolidate data as a primary role in managing master data. This would ensure that data could be blended from different sources and therefore consolidation was a mandatory process. At the same time, it had to guarantee data quality and eliminate all duplicates.
Third, data had to be cleaned and governed. Master data are profiled and consolidated for cleansing and governance purposes. Data cleansing entails “standardization, error correction, matching, de-duplication, and augmentation of the data” (Oracle, 2011). On the other hand, data governing involves “data definition, data quality rule definitions, privacy and regulatory policies, auditing, and access controls” (Oracle, 2011). Data cleansing and governing are two complementary roles that support data sharing across the company when MDM is deployed.
Fourth, data sharing remains an important role of Oracle based MDM. Data cleaning and augmenting provide little advantage to data manage in MDM. Hence, there is always a need to enhance capabilities and effectiveness of MDM. This process requires the propagation of master data to the platform and provide data to business activities. Augmenting processes must get full support from other applications. Oracle based MDM was built to provide high integration repository to ensure Web service compatibility and usability.
Lastly, the application was developed to provide data leverage. That is, the solution had to provide a single platform for handling all data in the organisation. In turn, the data would be leveraged to understand operational processes and analytical systems within the organisation. Beyond this, the company relied on the MDM to generate important insights to support decision-making. It offered complete views on the organisation based on analytical results. What-if analysis was found to be useful for the enterprise.
Type of data it uses
Oracle MDM has three types of real business data, namely analytical, transactional and master data. Analytical data are mainly used to support decision-making processes within the company. ADCO analyses customers’ activities and identify patterns that could support business operations, marketing and profitability. The platform helps the company to categorise various suppliers based on their performance trends for a given period to enhance decision-making within the supply division. It reviews product behaviours for significantly longer periods to note signs of failures.
The collected data are stored in the company’s data warehouse with small data mart storage systems that can support different data types, segregation, aggregation, data mining and random queries. Generally, data are collected and then stored in large tables with various sub-categories such as customers, suppliers, location, products and accounts among others.
Transactional data are generated from the company’s business operations (Villacís, 2007). There are many automated business processes, which generate data. Data are mainly collected from four sources. First, there are data from assets that include production, repairs, and costs of assets among others. Second, the company generates geospatial data to manage its field service crews, inventory and exploration among others. Third, data are also obtained from work management and field service management processes. Finally, the company also collects data related to outages to keep track of troubles.
The company, therefore, gathers significant amount of data to run its operations effectively. All data involved in transactions are collected for analytical purposes. For instance, the company must manage data from its distribution channels, customers’ issues and product details. Specific attention must go to customer and product data. In this case, data related to place, time, price, payment trends, methods, pricing and discounts among others are gathered for later analysis. Oracle MDM has capabilities to store data in “OnLine Transaction Processing (OLTP) tables, which can support high volume low latency access and update” (Oracle, 2011).
Master data are components of business data that are shared across an organisation. These data are core components of organisational business transactions. They are also useful for core analytical processes for a company. Master data are used to generate and consolidate reports across different IT platforms of an organisation. Oracle MDM has abilities to control all master data gathered from various IT landscapes in an organisation. Master data include data from sales, suppliers, assets, field activities, sites and accounts among others. In addition, other data sources may also include services, campaigns, or invoices.
These data may require cleansing, standardisation, consolidation and sharing. It is also imperative to note that not all companies are the same even in one industry. Therefore, companies may have additional data objects to support their smooth operations and critical business processes. Oracle MDM must also support high volumes of transactions that the company handles. Therefore, the solution must exist in supportive environments, designed for key architectural requirements under OLTP.
Impact on the business performance
Oracle MDM has addressed two critical roles at the company. It has improved decision-making capabilities, which has in turn enhanced business operations and performance (McKnight, 2009). Today, many tasks related to data have been optimised and automated for efficiency. Oracle MDM has improved data integrity in the company. Accurate data are available in a timely manner to manage business processes. This has created business agility for the company.
The company has also created trusted sources of data for integrity and developed data as its core asset. Hence, data from different sources are gathered, cleaned, consolidated, analysed and distributed to support operations.
Type of output and reports it generates
The MDM generally generates reports from geospatial data, outage management, work management and field service management and asset management. In addition, there are transactional data generated from business processes. Data captured from operational systems are used to update transactions and support decision-making.
Other comments
Managing data is important for any organisation. ERP applications such as Oracle MDM ensure data quality and integrity in an organisation. Ensuring that business units have the right master data in a timely manner is critical for business success (Morris & Vesset, 2005).
Not all organisations are the same and therefore, it is imperative to select the right ERP to meet unique business processes. The data management system must be able to provide the right data for decision-making purposes. This should be a priority for an organisation.
References
McKnight, W. (2009). Understanding Master Data Management and the Benefits. Web.
Morris, H., & Vesset, D. (2005). Managing Master Data for Business Performance Management: The Issues and Hyperion’s Solution. Web.
Oracle. (2011). Master Data Management. Web.
Oracle. (2012). Oracle Honors Winners of the Oil and Gas Industry Excellence Awards. Web.
Villacís, J. (2007). Master Data Management and Business Performance Management. Web.