You’ve Data Mined. Now What?

Abstract

Data-mining technologies are within the grasp of many organizations. Commercially available data-mining packages make it relatively easy for firms to transform their data resources into predictive models. Yet, despite technological advances, the precise manner in which data-mining output should be incorporated into an organization’s decision-making processes remains unclear. This paper attempts to clarify the role of data mining by situating it within the context of Simon’s model of decision making. We use a complex decision problem from the video game development industry to illustrate several practical challenges managers face when using data-mining output as a decision making input. We then show how some of these challenges can be overcome by incorporating data-mined predictive models into a conventional decision-analytic formulation of the problem.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.