Thoughts on Data: From Culture Change to Process Optimization
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In 2006, British mathematician Clive Humby coined the phrase, ‘Data is the new oil’. Like oil, data is valuable, but if left unrefined, it holds little to no value. For an industry that now relies so heavily on data, this statement still rings true. Whether used for ROI improvements, equipment maintenance, process optimization, decarbonization or health and safety measures, the oil and gas industry is slowly getting majorly influenced by data analytics.
However, for the oil and gas industry to gain a competitive advantage, it needs to perfect the art of identifying, aggregating, analyzing and utilizing its data. A successful organization will employ data analytics to identify areas and processes that need improvement and use that data to analyze how those areas can be perfected.
At a recent online event, Workflow Automation in Oil and Gas, hosted by Oil & Gas IQ, we had industry leaders share valuable thoughts and insights on harnessing data as a transformative tool. Read as Angelo Cianfrocco, Product Manager, Health and Safety at Intelex, Konstantin Osypov, Chief Scientific Advisor, Halliburton and Denis Bogino, Senior Specialist Data & Management Control, Vice President DC&P, Pan American Energy address key questions around data roles, from leveraging it as a culture change agent to using it to drive process optimization across your organization.
“For data to improve connectivity within an organization, that data needs to be put to work”, says Angelo Cianfrocco, Intelex. Only 32% of data available to organizations is put to work, with the remaining 68% going unleveraged, according to Seagate’s ‘Rethink Data’ Report, representing the struggle many organizations, including the oil and gas industry, face in processing data and unlocking its true potential.
READ: The 3 Step Guide To Workflow Automation
The Vicious vs The Virtuous
When using data for collection, analysis or communication, Angelo finds that there’s two kinds of cycles companies get into. The first is the vicious cycle where data being collected goes into a black hole. For example, an organization implements an observation programme out in the field, requests people to collect information by inspecting equipment but does nothing with the data when it comes through for analysis and implementation. This cycle leads to mistrust in an organization where the data collectors feel like their input is not being valued, resulting in less valuable data being collected.
The virtuous cycle, on the other hand, is one where organizations request field data to make improvements and analysis, and leverage it to communicate those improvements to the data collectors. A cycle like that leads to sustained engagement across the organization, especially with those collecting the data, as they know the information they provide can make significant changes to their workflow and processes.
Data As a Cultural Change Agent
When used to its full potential, the virtuous cycle can act as a culture change agent, driving optimized processes and efficiency while improving connectivity between the different levels in an organization. From Angelo’s perspective, there are three key factors which organizations can use to unlock the virtuous cycle.
1. Technology
One of the biggest problems companies face when implementing a software or technology or when starting a data collection effort, is poor-quality data. When implementing a new system, it’s essential to determine what information is most impactful and crucial to collect and start with that.
The next step is continuously monitoring the data once it enters the system. Identify the gaps, blank entries, non-descriptive data and rectify those in the back end to ensure you get valuable insights.
Another aspect, when looking at technology, is lowering the barriers to entry. To ensure the accuracy and quantity of data collected, you want to ensure it is convenient for people to for people to participate in data entry and data collection efforts. For instance, enabling data collection at the point of use is essential, whether it’s in a field for operations, environmental safety, or any other domain.
2. People
When it comes to people, the first step is to establish a clear mission and vision. The mission defines the objective of the initiative while the vision outlines the future position and outcomes of that mission. This helps leaders control the narrative and ensure everyone involved understands the purpose and value of the efforts.
The next step is training. Data is primarily collected by people, training should go beyond just the use of systems and technology, Angelo emphasizes. Explain to your data collectors why their input is vital and how it will contribute to the overall results.
3. Process
When rolling out virtuous data cycle, define the roles each individual will play, as every level has the ability to impact change within the process. For instance, CEOs and executives will act as sponsors, the middle management will facilitate the effort on a day-to-day basis, and the frontline will be concentrating on collection and gathering the data. This helps create an efficient workflow engine where the data is collected, analysed, processed, and actioned by the different stakeholders.
The Role of Data in Oil & Gas
With data analytics becoming increasing popular in streamlining efficiencies across different sectors, the oil and gas industry is not far behind in their understanding of how it can optimally be used.
Once a virtuous data cycle is established, data will start flowing into the right hands to optimize performance at both the frontline and executive levels.
"Sometimes we collect data, but we fail to check or utilize it effectively. Therefore, it is crucial to focus on the quality of data rather than just its presence or quantity. We need to ensure the data we gather is relevant and logically sound. In the process, it's essential to prepare our systems to recognize and analyze such data using suitable software or tools. Another vital aspect is the involvement of multiple people in reviewing the data. When more people review the data, the overall data quality in the company improves. Different individuals may have varying perspectives on data quality, and having diverse insights can lead to better accuracy and understanding.” says Dennis.
When differentiating good data from bad data, there is always the question of how to identify the gaps and inaccuracies to which Konstantin explains, "In all parts of the oil and gas business, integration of various types of data, such as geophysical and well data, is crucial for our workflows. Having systems that can easily accommodate these different data types and enable software to process them in an integrated manner is a significant trend.”
However, the question of how data helps with process automation remains and the answer, as Konstantin puts it, is quite simple. As an example, in subsurface characterization in the upstream sector, organizations deal with various data sources like geophysics and well data. There are different teams of specialists, including geologists, geophysicists, reservoir modelers, and economists, each working on different parts of the data. However, sometimes information gets lost in translation when transitioning between teams.
To address this issue, Halliburton is currently focusing on automation and integration by leveraging modern NLP (Natural Language Processing) models like ChatGPT and developing internal models to enable smoother human interaction and to handle more specific tasks. With this, they are able to automate processes, such as the interpretation of testing data. These technologies not only automate routine data handling tasks but also assist human experts in conducting quality control (QC) and more sophisticated tasks.
Hence, by embracing the power of data and perfecting the data utilization process, the oil and gas industry can shape the future of the sector already going through tumultuous transformations in light of decarbonization and automation.
