For oil and gas digital transformation is not a project where you make a roadmap and have a defined finish line, which, once crossed, constitutes a company being digitalized. Digitalization is achieved by implementing hundreds of use cases in a scalable manner.
“We often find companies engaged in a multitude of consultancy driven proofs of concepts (PoCs), leaving little of scalable nature behind once over,” Francois Laborie, general manager of Cognite North Americas explains. “At the same time, our experience shows that when engaging business and operations directly, the key reported obstacle hindering digitalization remains access to data. Data, understandable to humans and machines, and available when you need and in the form you need it is necessary for driving digital transformation. Data transformation is therefore clearly at the heart of digital transformation.”
In parallel, and in the same companies, data management in the context of digital transformation is commonly addressed through the lens of conventional master data management and data quality governance, owned by CIO or CTO, leaving operations and business at arm’s length at best. “This approach runs a high risk of missing operational and business management from the critical triage required to embed data management into the core fabric of continuous digital transformation,” Laborie adds.
Seeing digital transformation and future data management as two sides of the same coin, and moving from PoCs to scalable transformation requires close collaboration between business, operations and IT. This remains a real challenge.
Seeking help
The answer according to Laborie is the support of companies such as Cognite who help customers deliver real data-driven business value faster. “We are founded in oil and gas, affording us deep domain knowledge across operations, asset classes, value, and deployment in real-world operational environments,” he explains. With Cognite, O&G operators can fast-track data and digital transformation, moving past temporal PoCs and legacy master data management initiatives, and instead, focus on scaling the business application layer that has real bottom line impact, not only data architecture impact.
“It comes down to being able to focus on where the value lies immediately and to do so with scale and the only way to do it is by merging domain expertise with software development expertise and data science.
Action from data
There is a significant difference between data, siloed or aggregated into a data lake, and actual insight. Data along with data visualizations is available in abundance — in fact, many consider themselves drowning in data and dashboards — yet contextualization of data, adding semantic meaning through linkages, remains much less developed.
“Equally underdeveloped is true democratization of data access, or as we call it, data liberation,” Laborie continues. “Turning data into actionable information happens foremost by contextualizing and liberating data, and making it accessible across the organization, neither being central elements of traditional data warehousing initiatives.
“Contextualization is about giving data human and machine-readable meaning, while liberation is about freeing the data from the siloes of the legacy systems. Once the data is freed, enriched by contextualization and made accessible, it can drive value realization through business-specific use cases. At the core of Cognite’s technology is driving contextualization and liberation of data.”
Liberating data
Data liberation is one of our core pillars enabling digital transformation. Data liberation is about freeing data from the siloes, a typical Oil & Gas operator will have several systems storing a variety of data, often overlapping, and enabling everyone, from an offshore field worker to a machine learning analytics application partner to access contextually enriched, real-time data when and where needed to be more efficient.
“Data liberation is essential to unlocking employee-wide empowerment and change,” Laborie says. “Once liberated, the data itself needs to be contextualized to give it semantic and environmental meaning beyond the raw data itself. This comes back very much to above point on the disconnect between data and actionable information.”
Scalable infrastructure
Cognite, as a fast-growing technology company, needs to focus on its strengths and leverage the best infrastructure and managed services to build upon. They have been working very closely with Google from its inception.
“We need to be sure that our infrastructure is truly scalable both in its technological components but also across geographies,” Laborie continues. “Google was proposing a solid, scalable and secure infrastructure for us to build upon. Advanced analytics and machine learning are equally critical for our solution and our customers’ success, by working very closely with Google we manage to bring to market innovative solutions in a fraction of the time it would take us otherwise.
“When considering the wider IT landscape where our solution is deployed into we also embrace the importance of interconnectivity and open platforms; loosely coupled systems in other words. The boundaries of a conventional platform will become increasingly blurred, and rightly so. Customer environments are increasingly hybrid clouds wherein different IaaS, PaaS and SaaS solutions all interact via loose coupling to create a more resilient and adaptive holistic architecture focused on adaptiveness to change and time to value. Imposing strict boundaries around for example platforms is contrary to how we see open innovation in open ecosystems.”
Digital developments
Asset-intensive industries, such as oil and gas, are all pressured to increase their level of digital maturity across the full spectrum from subsurface discovery to life-cycle management. The imperative to lay the foundation towards autonomously operated assets as future vision is clear.
“Smart maintenance, improving HSE by embracing the digital worker and production optimization — to just mention select application areas — all hold enormous value for all asset-intensive industries, especially as for example in O&G, the ultimate product is a commodity,” Laborie concludes. “We see access to liberated and contextualized data transforming the industry, and ultimately changing the business models between suppliers and operators, companies developing new data-driven services and new ecosystems emerging.”
