“Big Data” and analytics have revolutionized "micro-decisions", those myriads of tiny decisions that follow a similar pattern, are made frequently, but each of which has relatively low risk and low value (e.g. the cross-sell to “things we might also like” that almost every e-commerce checkout page displays using our purchase history and possibly other data). By contrast, "macro-decisions" are less frequent, but higher-stakes. They are more complex and also need to take risk into account. Software support for macro decisions today is usually provided as “Business Intelligence” or “Dashboards”, both of which typically derive aggregate statistics from existing data, and present these in ways that are “meaningful” and “insightful” to humans. However, once the data has been presented, the synthesis and evaluation tasks at the core of the decision-making process are left to the human decision-maker. This is despite a large and well-accepted body of research (most notably by Kahneman and Tversky) clearly demonstrating that humans systematically lack the ability to perform such tasks accurately. A significant and as-yet untapped opportunity therefore exists for augmenting the existing BI paradigm with new data science techniques developed to assist decision makers.
This presentation introduces the “Decision Intelligence” approach which transfers the decision-related inference tasks from human intelligence to machine intelligence. The approach includes a structured framework for decomposing decisions so they can be represented as computable models. Using simulation and optimization techniques, these models generate data sets to which existing BI tools can be applied, giving decision makers the ability to generate data from “possible futures” and to evaluate decision and their outcomes in familiar, existing environments.
Mark is a leader in innovative research, software development and services delivery, and business development in the academic and commercial sectors for over two decades. He is co-founder and CEO of Quantellia, a leading Data Science innovator and developer of the award-winning World Modeler software. From 2000-2010, he held the position of CTO at Spatial info (now Synchronoss) where he co-founded the company’s US operations, and led technical operations. Prior to this, he was the architect of StatPlay, software developed jointly at La Trobe University and the University of Melbourne that explored how computer visualizations affect people’s innate abilities to perform statistical reasoning. Mark has also worked as a systems engineer for EDS (now HP) and Anderson Consulting (now Accenture). In 1994-5, he held a British Council Post Graduate Bursary at the University of Cambridge in the UK and from 1996-2000 was an Honorary Fellow at the University of Melbourne. He is the author of numerous publications and has frequently made speaking appearances.