Data Quality Management (DQM) is an effective methodology for reducing Data Verification Time in Upstream Oil and Gas. Odin makes it easy for companies to implement DQM by combining over 50 years of experience into a powerful yet easy to use software solution.
Overview
At the center of Data Quality Management (DQM) sits the DMAIC process, a methodology in Six Sigma that focuses on Defining the problem, Measuring the quality, Analyzing the root cause, Improving the quality, and Controlling the quality to ensure it is maintained. Odin is built around supporting the DMAIC process in upstream oil and gas data to improve data quality and reduce data verification time.
Define
Odin plays a vital role in the Define step by helping to clearly outline the data scope and convert friction points into actionable Epics. It begins by assisting users in identifying all relevant data sources and processes, ensuring the project’s scope is comprehensive. Odin then analyzes key friction points—areas of inefficiency or error—and translates these challenges into Epics. These Epics serve as high-level objectives that direct improvement efforts, ensuring the project remains strategically focused and aligned with business goals. This approach lays a strong foundation for success in the DMAIC process.
Area of Interest
The Area of Interest defines the scope of the data in the project and is defined by the geographical boundaries, data object types, and the various data sources where the data exists. This usually involves defining a project in Odin for each business unit. Previous DQM solutions were difficult to manage because they required many projects to handle all the data for a single business unit. Odin’s ability to handle big data enables business units to define a single project.
Defining the Epic
The second goal of the Define step is to translate a business unit’s friction points into one or more Epics. Odin users are easily able to translate their friction points into a series of Epics by selecting the data object types and attributes that relate to their friction points.
Traditional DQM solutions did not support Epics and were not able to establish separately measured DQM journeys. Odin’s ability to do this allows users to separate their DQM journey into a series of stages, focusing on the most critical friction points and working their way through in 8-10 weeks of work.
Using built in expert knowledge, Odin automatically selects the assessment and correction rules that relate to the Epic. The assessment rules enable measuring the data quality of an Epic and the correction rules generate the corrections for addressing data defects in the data.
Traditional DQM solutions were not able to automatically select assessment and correction rules. Odin’s ability to do this saves users time and reduces required expert knowledge.
Odin isn’t limited to a single Epic either, users are ablet to define as many Epics as they want and even share Epics between their projects and business units so that each business unit is following the same Epic.
Measure
Measuring the data quality is important for determining where the journey begins and how effective steps takin in the Improvement and Control steps are. Odin uses Sigma Six Scoring to measure data quality through its dashboard that enables users to measure data quality overtime by many different dimensions including by each project and/or epic, but also holistically so that the data can be measured across all projects and/or epics.
Six Sigma Scoring
Sigma Level is a statistical measure of process performance, indicating how many standard deviations (sigma) a process is from its mean defect rate. It’s often represented by Defects per Million Opportunities (DPMO), which measures the number of defects occurring per million chances for defects. The sigma level corresponds to specific DPMO values, with higher sigma levels indicating fewer defects and greater accuracy. For example, 1 Sigma equals approximately 691,462 DPMO (69.1% accuracy), while 6 Sigma represents only 3.4 DPMO (99.99966% accuracy), reflecting near-perfect performance.
Odin can measure up to Sigma 7 which data quality is such that there are only 0.019 DPMO defects per billion opportunities.
Analyze
Understanding and addressing the root cause of data defects is crucial. Odin’s advanced dashboard and insight tools empower users to thoroughly investigate the origins of data defects, identifying whether external factors are contributing to the issues.
With the support of Odin’s team of data quality experts, users can implement changes that prevent data defects from occurring in the first place, ensuring a more reliable and accurate data environment.
Improvement
Enhancing data quality in Odin involves a strategic combination of correction rules, data flows, and work items. Odin's extensive built-in correction rules swiftly identify data defects and determine the appropriate actions to resolve them by generating work items. These work items specify the exact corrective actions the system needs to take to address the identified defects. Adding to this robust approach, data flows serve as the final layer, guiding how data moves between sources. They dictate whether data transitions automatically or requires approval, ensuring that data integrity is maintained throughout the process. This three-pronged strategy creates a powerful framework for minimizing data defects and maintaining high data quality within Odin.
“I cannot believe how easy Odin has made my day. Before I spent all day, now I sign-in and after 15 minutes I am done.” – DQM Specialist
Control
The last step in the DMAIC process is where Odin helps to make sure that all the progress made is maintained. Odin is constantly monitoring and constantly auditing data to ensure that the data quality remains high. The dashboard sits at the center of this step by providing real-time insights and alerts that enable proactive decision-making. By leveraging Odin's continuous monitoring capabilities, any deviations from the expected performance are quickly identified, allowing for immediate corrective actions. This ensures that the improvements achieved during the DMAIC process are sustained over time, reinforcing a culture of quality and continuous improvement. The dashboard also serves as a central hub for all stakeholders to track progress, review performance metrics, and stay aligned with the project's goals, making it an indispensable tool for maintaining the gains realized through the DMAIC methodology.
Summary
In summary, Odin is revolutionizing Data Quality Management (DQM) in the upstream oil and gas industry by seamlessly integrating the DMAIC process into its platform. By simplifying the Define, Measure, Analyze, Improve, and Control steps, Odin empowers companies to achieve and sustain high data quality standards efficiently and reduce their data verification time. With features like automatic rule selection, real-time monitoring, and the ability to handle large-scale projects within a single system, Odin not only reduces data verification time but also ensures continuous improvement. As a result, Odin is standing out as an indispensable tool for maintaining the integrity and reliability of critical data, ultimately driving better decision-making and operational efficiency in the industry.
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