Machine Manipulable Models for Informed and Data-Driven Decision-Making
Speaker:Vinay Kulkarni, TRDDC, PuneDate: September 10, 2014
Abstract
Modern enterprises are complex systems operating in highly dynamic environment. The time to respond to the various change drivers is short and the cost of incorrect decisions is prohibitively high. Large enterprises adopt organizational structure best suited for ease of management and control. Scattered and fractured knowledge - about goals, operational processes, IT systems, design rationale, IT infrastructure, guidelines and best practices etc - is the undesirable side-effect. As a result, response to a change can at best be locally optimal and sequence of locally optimal responses hardly ever leads to global optimality. Moreover, many a change response ripple across the width and depth of enterprise – from strategy to operational processes to IT systems to IT infrastructure - all of which need to be kept in sync before, during and after. Today this concern is addressed by relying solely on human experts who are expected to keep track of the various influencing factors, their inter-dependence, the decisions these factors influence, and interdependence of these decisions. This is too big an ask considering the size and complexity of modern enterprises. We are developing an approach based on modeling the relevant aspects of enterprise, its IT systems and IT infrastructure so as to address this challenge in a pro-active manner leading to enhanced quality of decision-making.
Speaker bio
Vinay Kulkarni is a Principal Scientist with TRDDC, Pune. His research interests are meta modelling, model driven software development, distributed components, software architectures, business processes, software Engineering, language Processing, object oriented programming.