Datafication of Knowledge Work: A Framework and Research Agenda

Abstract

Datafication is moving into the center of value creation in the knowledge intensive organization. Datafication describes the transformation of qualitative behavior and tacit knowledge into quantified actions and codified data. While traditional assumptions on knowledge work highlights individual autonomy in shaping job tasks and fitting abilities for productive work, the consequences of datafication for knowledge work are not yet well understood. We build on the contingency theory of performance as theoretical lens to derive a framework that addresses relevant future research questions in the evolving field of datafication in knowledge work. The proposed multi-level framework considers assumptions and elements from traditional productive knowledge work in combination with determinants of digital workplaces and organizational factors along the lines of data-based value creation and (semi-)automated decision making. For the future, we suggest viewing datafied knowledge work as a socio-technical phenomenon, thereby constituted of human-dominated knowledge work in convergence with technological-dominated algorithmic thinking.

How Digital Business Strategy Shapes Task Complexity in Datafication of Knowledge Work

“…As driven by digital value creation, these items allow to capture effects of how data replaces and improves information cues and alters the moderating effect from IT dependency. Referring to [5,[9][10][11], the items measure how TC becomes induced by data and raises timeconsuming preparations caused by decision-making strategies (TCD1-3).…”

“…Datafication subsumes this transition, when qualitative behavior and tacit knowledge are increasingly replaced by quantified actions and codified data. These shifts transform the nature of knowledge work (KW) when human and digital actors begin to jointly act upon data and the organizational framework reaffirms the relevance of data [5]. While we begin to understand how these achievements result in fragmented phenomena, e.g., individualized service for customers, automated decision-making, or the rise of meta-human systems [6], we also recognize concepts on corporate strategic level that describe value creation from the evolving role of data and digital technology [4].…”

“…While we begin to understand how these achievements result in fragmented phenomena, e.g., individualized service for customers, automated decision-making, or the rise of meta-human systems [6], we also recognize concepts on corporate strategic level that describe value creation from the evolving role of data and digital technology [4]. Still, it is yet not well understood how these conversions within knowledgeintensive organizations reflect into socio-technical changes in work-systems [7] and how knowledge workers perceive these shifts from modified characteristics of their job tasks [5].…”

“…In turn, decision-making as a cognitive knowledge job task becomes increasingly supported and partly overtaken by algorithms and artificial intelligence. While the datafication of KW as phenomenon describes this shift from intuitive and qualitative decision-making towards being rather quantitative and codified [5,12,13], it is still unclear how the superior organizational framing of a DBS impacts the complexity of individual knowledge tasks. To better understand the effects on task characteristics through favoring data in KW, we pose the research question: How does a digital business strategy shape the complexity of job tasks in KW?…”

Mapping Knowledge Flows in ExploratoryWeb Searches

“…Finally, Fischer and Wunderlich [28] proposed a multi-level framework considering assumptions and elements from traditional productive knowledge work to illustrate influential factors on job performance based on the contingency theory of action.…”