Making Sense of Knowledge Intensive Processes: an Oil & Gas Industry Scenario
This addresses sensemaking challenges for collaborative decision-making in domain-specific industries, but it is incremental as it offers an initial set of knowledge types without major breakthroughs.
The paper tackles the problem of understanding sensemaking in knowledge-intensive processes, presenting findings from an Oil & Gas industry scenario that indicate different knowledge types can be combined to compose sensemaking outcomes like decisions.
Sensemaking is a constant and ongoing process by which people associate meaning to experiences. It can be an individual process, known as abduction, or a group process by which people give meaning to collective experiences. The sensemaking of a group is influenced by the abduction process of each person about the experience. Every collaborative process needs some level of sensemaking to show results. For a knowledge intensive process, sensemaking is central and related to most of its tasks. We present findings from a fieldwork executed in knowledge intensive process from the Oil and Gas industry. Our findings indicated that different types of knowledge can be combined to compose the result of a sensemaking process (e.g. decision, the need for more discussion, etc.). This paper presents an initial set of knowledge types that can be combined to compose the result of the sensemaking of a collaborative decision making process. We also discuss ideas for using systems powered by Artificial Intelligence to support sensemaking processes.