A Dissertation entitled Big and Small Data for Value Creation and Delivery: Case for Manufacturing Firms By Blaine David Stout Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Manufacturing and Technology Management _________________________________________ Dr. Paul C. Hong, Major Advisor __________________________________________ Dr. An Chung Cheng, Committee Member _________________________________________ Dr. Thomas S. Sharkey, Committee Member __________________________________________ Dr. Steven A. Wallace, Committee Member __________________________________________ Dr. Amanda C. Bryant-Friedrich Dean, College of Graduate Studies The University of Toledo December 2018 Copyright 2018 ©, Blaine David Stout This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author. An Abstract of Big and Small Data for Value Creation and Delivery: Case for Manufacturing Firms By Blaine David Stout Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Manufacturing and Technology Management The University of Toledo November 2018 Today’s small-market and mid-market sized manufacturers, competitively face increasing pressure to capture, integrate, operationalize, and manage diverse sources of digitized data. Many have made significant investments in data technologies with the objective to improve on organization performance yet not all have realized demonstrable benefits that create organization value. One simple question arises, do business-analytics make a difference on company performance in today’s information intensive environment? The research purpose, to explore this question by looking through the lens of data-centric pressure placed on management driving the invested use of data-technologies; how these drivers impact on management influence to adopt a digitized organization mindset, effecting data practices, shaping key processes and strategies and leading to capabilities growth that impact on performance and culture. The terms ‘Big Data’ and ‘Small Data’ are two of the most prolific used phrases in today’s world when discussing business analytics and the value data provides on organization performance. Big Data, being strategic to organization decision-making, and Small Data, operational; is captured from a host of internal and external sources. Studying how leveraging business-analytics into organizational value is i of research benefit to both academic and practioner audiences alike. The research on ‘Big and Small Data, and business analytics’ is both varied and deep and originating from a host of academic and non-academic sources; however, few empirical studies deeply examine the phenomena as experienced in the manufacturing environment. Exploring the pressures managers face in adopting data-centric managing beliefs, applied practices, understanding key value-creating process strategy mechanisms impacting on the organization, thus provides generalizable insights contributing to the pool of knowledge on the importance of data-technology investments impacting on organizational culture and performance outcomes. The exploratory and theory building phase of the research uses case studies to examine topics of interest and uncover others adding to the richness of the study on which to build a research model. To hear the voice of practice, multiple in-depth, semi-structured interviews were conducted among senior managers of 10 regional manufacturers located in the central Midwest United States. The research’s confirmatory phase firstly reviews literature on topics revealed in the research model augmenting the depth of data on which to construct a large-scale survey instrument. Secondly, a survey-study is developed and conducted among 333 managers of manufacturers located across North America. The results are presented in two forms, through a multiple regression analysis and structural equation modeling. Both demonstrating the moderating impact of executive management influence and data accessibility and use mechanisms on organization performance in the form of capabilities growth. The research presents a data-centric management influence model generalizing the effect of management influence and investment making on data- technologies; thereby enabling a data-centric mindset or culture to maintain and sustain organization value in knowledge or digital intense competitive environments. ii To my most loving wife, Linda, without her steadfast support, giving of time, care, insights, laughter, smiles, understanding patience, and persistent urges on completing this doctoral pursuit, its achievement would not be possible. With my deepest heartfelt appreciation, Thank You iii ACKNOWLEGEMENTS Life is about learning, learning requires teachers, teachers who appear at the right time in our lives to make the learning experience possible. Some present, some past, some in spirit. To those present, my most grateful appreciation is given to my dissertation chair, Dr. Paul Hong, one of the first professors met when joining the PhD program. Dr. Hong has a unique, engaging curiosity about people, and when asked about interests in that first meeting, he believed we would be doing some ‘great research together’. His mentoring, patience, and wisdom since has been invaluable on this learning experience. The committee members, Dr. Thomas Sharkey, a mentor, friend and supporter of this doctoral pursuit, who I’ve known since my MBA days here at the University and have always appreciated his guidance. Dr. An Chung Cheng, whose involvement from the language arts disciplines adds an affinitive dimension on the committee that is gleaned from global perspectives on how we as people communicate is likewise most appreciated. Dr. Steven Wallace, whose understanding of case study research and serving as a sounding board on similar business analytics topics of interest has been most helpful on this effort. To all of the professors whose seminars shaped my learning, understanding of research, writing papers (many they were) and preparing for this event, my grateful appreciation. To the University of Toledo, and The College of Business and Innovation its Deans and PhD program directors, past and present, for granting me the wonderful opportunity to study with the best and brightest colleagues from distances near and far. From the practical side of learning, the case study participants, whose names are withheld for anonymity reasons, are thanked for contributing on the richness of discovery found in those meetings and conversations. A grateful appreciation to a dear friend and iv professional colleague, Rob Bleile, whose information systems and technology insights, knowledge on data collection, research and analytics, as well as having career manufacturing experience, was instrumental on this research effort, thank you. Those past, are mentors from prior professional careers in manufacturing, providing opportunities on serving in high levels of responsibility and learning the best forms of leadership on which an organization effectively functions; I am very grateful for those learning experiences. To those is spirit, my mom and dad, my wife’s mom and dad, and a host of other relatives and friends who I know have an unseen role in this achievement. To the wisdom of my faith, that God guides us on paths best for our journey in this life, it is meant as it is to be. Thank you v TABLE OF CONTENTS Contents ACKNOWLEGEMENTS ............................................................................................... iv TABLE OF CONTENTS ................................................................................................ vi List of Tables ..................................................................................................................... x List of Figures .................................................................................................................. xii CHAPTER 1: INTRODUCTION .................................................................................... 1 1.1 Research importance .................................................................................................. 1 1.2 Research contribution ................................................................................................ 4 1.2 Essay organization ...................................................................................................... 6 CHAPTER 2: VOICE OF THE MANUFACTURER .................................................. 8 2.0 Grounded theory ......................................................................................................... 8 2.1 Case Study Research ................................................................................................ 11 2.1.1 Case study process ..................................................................................................... 13 2.1.2 Case selection ............................................................................................................ 14 2.1.3 Field interviews ......................................................................................................... 15 2.1.4 Coding and analysis ................................................................................................... 16 2.1.5 Data structure............................................................................................................