Data visualisation and decision support for innovation management

Author: Venkata Pavana Sai Jayanth Aravapalli

Aravapalli, Venkata Pavana Sai Jayanth, 2019 Data visualisation and decision support for innovation management, Flinders University, College of Science and Engineering

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Abstract

Australia is experiencing a decline in traditional manufacturing due to downward pressure on exchange rates and a shutdown of several motor vehicle production companies. Innovation is essential to find new industries to replace the old.

The aim of this project is to develop a visual decision support tool where users can identify opportunities to create distinctive, competitive products in key industries based on their potential for exports, diversification and complexity. Based on analytics of global trade data of over 5,000 products, it enables users to determine exports from Australia to various countries for products of interest.

In this study, a dynamic visualisation tool was developed using Microsoft Power BI. More specifically, through iterative qualitative research with a subject matter expert and economist from the South Australian Government, the tool was refined using an Agile. It was then deployed over the GitHub for impact among users. The tool provides innovation intelligence in five key industries: defence and space; advanced manufacturing; renewables; medical technologies; and food and agriculture.

The study makes an important theoretical contribution by developing a model to improve economic complexity for innovation management by integrating interdisciplinary literature on visualisation, innovation and complexity.

It also makes a valuable practical contribution to government on industry development and innovation by identifying relevant product opportunities for Australia in priority industries to increase complexity, exports and diversity.

Keywords: visualisation,Agile,Innovation Management,Complexity, Exports,Diversity,Decision Support,Microsoft Power BI.

Subject: Engineering thesis

Thesis type: Masters
Completed: 2019
School: College of Science and Engineering
Supervisor: Associate Professor Giselle Rampersad