The Lean Startup - Eric Ries [114]
Product Development Pseudoscience
I believe that if Taylor were alive today, he would chuckle at what constitutes the management of entrepreneurs and innovators. Although we harness the labor of scientists and engineers who would have dazzled any early-twentieth-century person with their feats of technical wizardry, the management practices we use to organize them are generally devoid of scientific rigor. In fact, I would go so far as to call them pseudoscience.
We routinely green-light new projects more on the basis of intuition than facts. As we’ve seen throughout this book, that is not the root cause of the problem. All innovation begins with vision. It’s what happens next that is critical. As we’ve seen, too many innovation teams engage in success theater, selectively finding data that support their vision rather than exposing the elements of the vision to true experiments, or, even worse, staying in stealth mode to create a data-free zone for unlimited “experimentation” that is devoid of customer feedback or external accountability of any kind. Anytime a team attempts to demonstrate cause and effect by placing highlights on a graph of gross metrics, it is engaging in pseudoscience. How do we know that the proposed cause and effect is true? Anytime a team attempts to justify its failures by resorting to learning as an excuse, it is engaged in pseudoscience as well.
If learning has taken place in one iteration cycle, let us demonstrate it by turning it into validated learning in the next cycle. Only by building a model of customer behavior and then showing our ability to use our product or service to change it over time can we establish real facts about the validity of our vision.
Throughout our celebration of the success of the Lean Startup movement, a note of caution is essential. We cannot afford to have our success breed a new pseudoscience around pivots, MVPs, and the like. This was the fate of scientific management, and in the end, I believe, that set back its cause by decades. Science came to stand for the victory of routine work over creative work, mechanization over humanity, and plans over agility. Later movements had to be spawned to correct those deficiencies.
Taylor believed in many things that he dubbed scientific but that our modern eyes perceive as mere prejudice. He believed in the inherent superiority in both intelligence and character of aristocratic men over the working classes and the superiority of men over women; he also thought that lower-status people should be supervised strictly by their betters. These beliefs are part and parcel of Taylor’s time, and it is tempting to forgive him for having been blind to them.
Yet when our time is viewed through the lens of future practice, what prejudices will be revealed? In what forces do we place undue faith? What might we risk losing sight of with this initial success of our movement?
It is with these questions that I wish to close. As gratifying as it is for me to see the Lean Startup movement gain fame and recognition, it is far more important that we be right in our prescriptions. What is known so far is just the tip of the iceberg. What is needed is a massive project to discover how to unlock the vast stores of potential that are hidden in plain sight in our modern workforce. If we stopped wasting people’s time, what would they do with it? We have no real concept of what is possible.
Starting in the late 1880s, Taylor began a program of experimentation to discover the optimal way to cut steel. In the course of that research,