Hard Facts: First Section Review

This book is organized into three sections, for this post, I will be talking about the section called "setting the stage" in Pfeffer and Sutton's book.

Pfeffer and Sutton start the book by describing what evidence based decision making is. It's essentially defined as a process to find the best evidence that you can. Through primary or secondary research, collecting the data and acting on that data. They say that there is an inherent perception blindness when making decisions from what you've always done, what you thought was true, your personal philosophies or beliefs and what ever fad is gripping the business world at the moment. I was impressed with the description of evidence based management or decision making is not a "thing you do", it doesnt have discreet boundaries, it's a process, it's a way to make decisions with a little data to help you out.

One of the examples they explore is how mergers and acquisitions tend to show strain about a month after the merger. Cisco has a great record for mergers because they measure several aspects for its merger targets, not just product or service, not just market share.. but culture as well. They've walked away from deals when the culture didn't match.

Pfeffer and Sutton identify common problems that consistently cause failure.

• Casual benchmarking
• Repeating what's worked in the past, or what's worked for others
• Following deeply held, yet unexamined ideologies
• Substituting facts for conventional wisdom
  

Each of these common problems can cause failure in strategies because they either ignore the data that's there, they fail to take into account new, unmeasured data or they assume that their belief is enough to make decisions. One of my favorite quotes (which I have in my quote generator) is David Hume's quote: "A wise man proportions his belief to the evidence". It's not wrong to believe, but in business and strategy, you need to have evidence to support those beliefs.

They provide logical and interesting anecdotes (which, in and of themselves are not evidence) that elucidate some of the principles, and they do an excellent job in documentation and referencing the examples they provide.

In my niche market of "search intelligence", I live and breathe data. Whether it's analytics or mined data, I try to be very careful to either only say what I can prove, or qualify any statement that has more intuition than data.

I just finished the second section, and without finishing it yet, I can say... buy this book. Read it, and let me know what you think. It's good.