The Digital Transformation of the Knowledge Worker

Abstract

Technological advances unveil a dual reality in the oil and gas Industry. On one hand, the benefits of blockchain and artificial intelligence (AI), among others, has arrived to revolutionize the industry. On the other hand, industry professionals remain trapped in bureaucratic processes that undermine their performance. The diagnosis: knowledge workers, responsible for optimizing the recovery and economic performance of the fields, are the missing link in the digital transformation chain. They are suffering the digitalization of the status quo. This paper puts forward a broad digital transformation framework designed to increase the knowledge worker's productivity. Digital transformation is not just about the implementation and use of cutting-edge technologies. It is also the response to digital trends, and about adopting new processes and redesigning existing ones to compete effectively in an increasingly digital world. Prioritizing technology as the ultimate goal puts the business processes and the knowledge workers aside from the discussion. The key to this proposal is rethinking the business model according to the possibilities of new technologies based on a six-dimension scheme:Corporate strategy: It defines the long-term vision and investment criteria for value creation. Technology is an element within a business scheme that should not be analyzed in isolation.Digital strategy: Within the corporate strategy, what operational and strategic role does technology play? Should it only support the company's operation, or should it drive strategic reinvention?Culture: While digital transformation is the company's response to digital trends, culture is the muscle that provides (or not) the attributes required to succeed in this transformation endeavor. Innovation and creativity should be promoted as part of the company's DNA.Knowledge processes: A business model, built on new technologies, will necessarily impose new and automated practices. While the automation of physical processes is a fact, the automation of knowledge processes is the weakest link.Data governance: It defines the necessary conditions that guarantee the quality of the information and its strategic acquisition. Two elements are a must: the automation of processes, thereby avoiding arbitrariness in data management; and centralized databases, thereby eliminating data duplicity and criteria discrepancy.Data Science: At this point in the model, the company has efficient, automatic, and fast processes, assuring the quality and availability of the data from its conception to the final storage. Then, data scientists will have all the means, and a clear and aligned vision (corporate strategy) to extract meaningful insights for the business.