Introduction

Enterprise IT (Information Technology) is a $3.8 trillion per year industry worldwide, and $1 trillion in the US alone.1 The Enterprise IT industry is twice the size of the world petroleum industry.2 Capital spending for IT in the US is now $700 billion per year.3 At 32% of the total capital spend, it exceeds construction and is closing in on equipment spending. At least half – and perhaps as much as three fourths – of this spending is wasted. The capabilities that are delivered fall far short of what our technology makes possible.

We (and by “we,” I refer to the people in charge of estimating, proposing, and executing information application projects or system integration projects) have come to simply accept the current state. It has become the norm to have projects cost tens of millions, hundreds of millions, or even billions of dollars, and routinely run over budget and schedule by hundreds of percent. These budget and monetary “overages” are almost all waste. However, the waste is hard to see, after being so marbled through all the products, processes, and guiding principles. That is where this book comes in. We must see, understand, and agree about the problem before we can take coordinated action to address it.

We refer to the current state of affairs as “the Application-Centric Quagmire.” Our root cause analysis, detailed in Chapter 3, pins the industries’ current woes on a firmly entrenched mindset, which we call being “Application-Centric.” We watch firms addicted to this mindset struggle to break free. But struggling to free yourself, while still clinging to the beliefs that keep you stuck is not a solution. We’ve come to refer to this situation as the “quagmire” because after decades of watching executives struggle with their systems, it seems apt. The harder they flail and the more they invest, the more stuck they become.

Not everyone has the problems described in this book. A few firms (mostly those that were founded in the 21st century, often called the “digital natives”) have managed to avoid the quagmire. Avoiding the quagmire is how Instagram managed to scale to 100 million users with a team of five building, deploying, and managing their apps. Amazon pushes changes to its systems up to five times a second. They are not in the quagmire.

Most established companies are well enmeshed in the quagmire. Moreover, failing to understand the behavior and mindsets that got them in the quagmire will keep them stuck. This book is for the companies that are frustrated with their current systems, and suspect that things could be much, much better.

The trajectory of this book is as follows:

• In Chapter 1, we explore how bad the current state is. We’re talking about waste at a terrific scale.
• In Chapter 2, we explore the economics of the software industry. Many of the lessons we’ve brought across from other industries don’t apply here. Additionally, the economic tradeoffs are changing at the speed of Moore’s Law, but our approaches are not keeping pace.
• In Chapter 3, we use “root cause analysis” to reveal the real contributors to this situation.
• Chapter 4 recounts the many attempts we’ve made in the past to deal with information system complexity, and why they have been marginally effective.
• Chapter 5 dismantles seven fallacies that sound good on the surface, but contribute to our remaining stuck.
• The quagmire is not affecting all sectors of the economy equally. Chapter 6 looks at how this is playing out in the government and private sectors, large and small companies, and various parts of the IT industry itself.
• Chapter 7 outlines some action you can take now to begin to extricate yourself.

This book is intentionally bleak. It is intended to get you sufficiently riled up to take action. Chapter 7 provides some immediate actions you can take to stop the pain. The companion book is where we propose a longer-term fix and a way to stay away from quagmires permanently.

Throughout this book when I use the pronouns “we” or “our”, I am usually referring to experience that I or my associates at Semantic Arts have found and concur on, from 18 years of helping large firms tackle these issues. When I say “I”, I refer to personal observations that may not be as widely held.