Preface

The Quest for Financial Impact: Four Years of Research Behind the Book

The original idea to write this book came to me four years ago in a private conversation with one of my clients, the CEO of a leading listed company. Thanks to a longtime trusted advisory relationship he asked me a very tricky question: "Tim, you know my contract with this company ends in two years and for me this is just a platform to move on to a bigger task. Tell me, am I not better off spending a few millions on a digital incubator, investing in one or the other cool start-up, starting to wear jeans and trainers and 'digital wash' my annual report and internal communications, instead of doing what we both know needs to be done-investing half a billion or more to transform my outdated legacy backend over the next five to 10 years to truly differentiate in the market and make my company more resilient for what is yet to come? On a journey likely to be full of pain, failures, and high cash-outs putting a lot of pressure on our stock price and my nerves while I am still here? Who will thank me for that? Will there be a measurable return on invest and positive stock price impact?"

I should not admit it now as a typical strategy consultant, but I had no answer-at least not one with the necessary facts behind me. This I was not willing to accept. So, I started searching, but still could not find it. I talked to experts in my firm and beyond in my network, and I tried to read every piece of practitioner advice out there. Believe me, there is much more than you can digest. Literally hundreds of books, articles, and presentations on digital transformation. Most are terrible and repetitive or self-refencing, but there are also quite a few good ones. So, in the end, in this complex digital world, where you cannot afford to miss a single great idea, I decided to read most of them to make my own experiences. If you would do the same, I am sure you would share my disappointment, as most of them have one of three major shortcomings.

First, there are many inspiring ideas out there but the advice is mostly based on subjective experience, interviews, and conceptual thinking (Brynjolfsson and McAfee 2014; Gale and Aarons 2017; Mazzone 2014; Raskino and Waller 2015; Rogers 2016; Schallmo et al. 2017) with some traits of an almost religious common belief system. For the followers of this system, recent and soon expected disruptive technological advancements generate significant challenges and opportunities that need to be urgently dealt with. In this declared "Digital Revolution" (Rogers 2016), "Second Machine Age" (Brynjolfsson and McAfee 2014), "4th Industrial Revolution" (Schwab 2017) or "5th Information Revolution" (Nazarov, Fitina, and Juraeva 2019) traditional management practices are supposed to no longer suffice to thrive or even survive (Gale and Aarons 2017; Mazzone 2014; Raskino and Waller 2015). Not surprisingly, all authors immediately propose predominantly prescriptive playbooks to achieve digital leadership. They are often also providing many interesting ideas to help differentiate from the numerous companies that fail doing so (Andal-Ancion, Cartwright, and Yip 2003; Bock et al. 2017; Charan 2016; Davenport and Westerman 2018; Gartner 2018; Kane et al. 2017; Rogers 2016).

Second, and potentially as critical as a shortcoming, the digital transformation recipes are typically inspired by famous digital-born companies, singular transformation examples, and successful digital platform strategies (Bughin and Catlin 2017; Rogers 2016). If ever focusing on the larger bulk of established corporates, they leverage anecdotal case examples and anonymous surveys with subjective company responses (Kane 2016; Kane et al. 2017, 2018), which provide great qualitative insights but obviously also face many admitted limitations (Kane 2019). Opposing concerns that, without a specific context understanding, the digital transformation journey should not be universally recommended for every firm in any context, industry, or size are far and few between (Andriole 2017; Davenport and Westerman 2018).

Third, even though the "planned digital shock to what may be a reasonably functioning system" (Andriole 2017, p. 20) is considered to be "no [.] sure salvation" (Davenport and Westerman 2018, p. 3), there seems to be almost no focus on proven financial outcomes for corporates (or any other companies) with the exception of the analysis on EBIT and profit margins by Westerman (Westerman et al. 2014). Quite the opposite; some authors even proclaim that traditional value metrics do not make much sense (Gale and Aarons 2017).

Therefore, and further amplified by the digital transformation surge due to COVID-19, it became very clear to me that there is an urgent business need to develop a more objective, scientifically supported view of digital transformation payback. We needed a new method to navigate the hype, lower the risks of falling into the digital hype trap, and increase return on investments beyond the prescriptions of managerial books and practitioner journals. I thus turned to academia and joined a high-ranked global business school as a researcher to gain access to leading-edge academic know-how. With some shock, I quickly realized that science also has so far put inadequate prominence on the digital transformation theme. The few available publications provide only very limited answers. There is little to find of any use other than some initial tries of empirical value/performance analysis, and, therefore, the worry about a "digital paradox, i.e. being unable to capture value from [.] digital investments" (Parida, Sjödin, and Reim 2019, p. 14) remains.

In addition, given the turbulent history of multidisciplinary research on technology/IT/IS value impact for capital-market-listed companies, nicely summarized by Kohli and Grover (Kohli and Grover 2008), astonishingly little transfer work has been conducted to reach a similar level of understanding for digital transformation value. The same is regrettably true for the findings of innovation value research (Brockhoff 1999; Salomo, Talke, and Strecker 2008; Strecker 2009; Vartanian 2003) and recent corporate finance research (Damodaran 2013, 2017). Only in few cases do researchers provide some depth and positive results, but, rather, focus on subtopics like observable digital strategy and innovation (Beutel 2018; Mani, Nandkumar, and Bharadwaj 2018) or economy-level entrepreneurship impacts (Galindo-Martín, Castaño-Martínez, and Méndez-Picazo 2019). Others apply qualitative text analysis of statements on digital transformation in voluntary and obligatory reporting (Kawohl and Hupel 2018) and then stop there, or focus on text-analysis-based subjective digital maturities (Zomer, Neely, and Martinez 2018) as a baseline. Except for some recent work linking text analysis and analyst recommendations (Hossnofsky and Junge 2019), and early-stage analysis looking deeper into the firm value and performance implications of non-technology companies investing in digital technologies (Chen and Srinivasan 2019), not once was a broader, end-to-end view of the digital transformation process and its value impact found.

So I had no choice; I needed to embark on a journey by myself to solve this puzzle. To provide answers which, years later, hopefully my client still would want to hear, now that he has moved on and is-no surprise-facing the same question only six times bigger. Based on the focus of my experience and interests, I put my emphasis on the value implications for large-capital market-listed incumbent firms with a sufficient size and history to assume a transversal transformation rather than greenfield digital start-ups or smaller firms. Nevertheless, for this book, I will also discuss implications for smaller companies in a small excursus on this topic in Part II of this book.

I developed a more objective, scientific understanding of digital transformation and its (shareholder) value impact. The main contribution of the research behind this book was the first-ever combination of a structured transversal digital transformation framework with an in-depth empirical analysis of financial impact implications enhanced by a unique, Natural Language Processing (NLP) supported dataset (> 20,000 observations) of large, listed corporates. Good news for you: As you will be able to see later, based on this approach, some advanced statistical analysis, and causal machine learning, there are means to better predict the likelihood for a statistically significant market value payday for your digital transformation efforts, depending on the context of your company.

Navigate the Hype: How to Read Digital Transformation Payday

Obviously, you can read only parts of this book based on which topics interest you the most (the chapter titles try to tell you what's inside). Still, I believe you will benefit much more if you follow it in sequential order. Like digital transformation, this book is an end-to-end process where every element needs to have its place. However, there is one thing you must be aware of when doing so. What you will not find in this book are explicit company names when describing the practical examples used to illustrate the ideas. This is for a good reason. The payback mechanisms of digital transformation are one of the best-kept secrets, and the likelihood of...