“It’s moving leaders from playing Caesar with their thumbs up and down on every idea to—instead—putting in the culture and the systems so that teams can move and innovate at the speed of the experimentation system.” – The Lean Startup

Regular readers will note I’ve been offline for a while – my apologies.

Say you have 100 envelopes to address, stuff, and seal. What do you do? Most people would address them all, fold them all, seal them all, etc. Sadly for most people, this is wrong. It is actually faster to do them one at a time! (there is video evidence, honest). Why? Because moving 100 envelopes around is cumbersome, and takes time. Rather than moving piles repeatedly, it’s better to do them in a small batch. Doing them step by step may improve individual performance, but the system performance is bad. In fact, even if it took the same amount of time, the usual method is risky. What if you address all 100 envelopes, and realize the letters don’t fit?

What’s the point? Businesses should do the same. Rather than coming up with an amazing idea, building huge factories, developing vast numbers of the product, and selling them all at once, companies should try to be in continuous deployment. They should be releasing dozens of small changes per day and testing them on small groups of consumers.

The defining feature of a startup, says the Lean Startup, is uncertainty. They aren’t sure who their customers are or what they need. As a result, the key resource is information. Startups must therefore focus on learning above all else. To do so, they need to experiment, try new things, and piece together an awareness of what their context is all about. From that insight, all else in the book flows: that startups should have fast cycles, small batches, develop minimum viable products, etc.

It’s a powerful insight, and one that firms, governments and individuals are usually terrible at. Even in our own lives, it probably doesn’t make sense to come up with a single huge master plan. Rather, we should try new things, experiment, and see if they work for us. If we do, we can do more. If not, we can do something else. Life, as with startups, is all about learning.

Overall, I’d highly recommend the lean startup. A powerful insight into life and business.

“The logical, competent decisions of management that are critical to the success of their companies are also the reasons why they lose their positions of leadership.” – The Innovator’s Dilemma

The Innovator’s Dilemma is simple. ‘Good’ companies, ones that maximize investment returns and listen to their customers, are harming their future prospects. Why? Because to stay on top, you need to innovate, but customers don’t want innovation: they want what they’ve always gotten. To innovate, you need to find new customers, try new things, take on risks, but ex-ante those risks can seem unreasonable or unwise.

The Innovator’s Dilemma argues that many business miss disruptive technologies. They do so not because they aren’t able to produce them, but because their current customers didn’t need or want the new product. When a smaller 5.5 inch hard drive was introduced, the major market for hard drives was users of supercomputers. They cared about power, not size. A well-managed firm in the traditional sense would have listed to their customers and not sold 5.5 inch drives.

It is left to a small firm to find a new market for the product, and indeed such a small market is only really profitable for a small firm. Of course, in the long run such small markets can grow, as did the one for 5.5 inch drives when it sparked the development of the laptop.

Are large firms doomed? No, says Christensen. Innovation requires focus, and it has to be essential to the existence of the organization to succeed. The answer is often to set up a small organization for whom the innovation is their core business, at let if flourish.

A challenge Christensen doesn’t address is how to identify which technologies are disruptive. A large firm can hardly set up a spinoff for every possible idea that crosses its desk, but it isn’t easy to know which will succeed in advance. That said, the book is and remains a classic on innovation, and if excessively long in some parts, it is focused on an important challenge for firms big and small.

“Instead of trying to absorb all of the business information that’s out there–and there’s a lot out there–use this book to help you learn what matters most, so you can focus on what’s actually important.”

Want to be a guaranteed millionaire? Save $10 a day for forty years at 8% interest. Not something that comes up in many MBAs, but actually quite interesting when you think about it. Two lattes a day, and retire a millionaire! Though, 8% is pretty optimistic these days. Anyway.

MBAs are expensive. Really expensive. So expensive, you might wonder if it’s really worth it. For Josh Kaufman, the answer is usually not, unless you’re hoping to work for an investment bank, lead a fortune 500 company, or be at a top management consulting firm. Too many modern MBAs focus largely on finance, which is relevant in those settings but not if you want to, say, actually run a business.

In response, Kaufman has done his best to distill the many business books he has read to some concrete lessons. The ‘Personal MBA’ is a process of reading one hundred best books on business he recommends, focused on how business actually works. What are the key parts of any business? How do you find a grow a business idea? What are the three universal currencies (resources, time, and flexibility)?

Overall, the Personal MBA is excellent: it does a great job distilling concepts into bite-sized pieces, and it is well-written and clear. It stumbles a few times—some of the bite-sized pieces are so small as to be basically useless, and the risk of a personal MBA is that you don’t realize where you’ve misunderstood, so a few of his explanations are not quite correct—but if you’re looking for a clear, concise, and well-written introduction to a wide selection of business concepts, it’s a great resource.

“Businessmen are finding that while they have more numbers than ever before, they still do not know what these numbers mean.”

“This book was written to help organizations overcome the effects of numerical naivete.”

Understanding Variation is a classic in understanding and measuring how businesses work. Its key lesson is that things vary. When we see that trade is down in February compared to last year, it’s tempting to assume that means something. The media will certainly report it as such, but we really don’t have any reason to do so. For that data to be meaningful would require that last year be ‘normal.’ I’m not sure that’s ever happened.

Variation is a significant challenge for businesses. If a business has bad results one month, should it make changes? Wait? Ignore it? There are no hard and fast rules, though entire disciplines have arisen over what type of results mean something (see: Six Sigma). Even good managers fall victim to regression to the mean: when they see results that are worse than average, they reprimand the employee, and things get better! Of course, when they see good results, they reward the employee, and things get worse. Managers learn to always be mean, rather than the true lesson that things can’t permanently stay above or below average.

Wheeler presents a few key rules, including that no data have meaning apart from their context, and that to detect a signal, filter out the noise. Much of the book, however, focuses on laying out tools that can help businesses identify meaningful variation. Wheeler swears by the control or XmR chart, a time series combined with a graph showing the size of the change each period. It means you can track both level and variability simultaneously, and look for significant changes in either.

The book is a bit outdated now, but the lessons ring true. Variation was and remains a challenge, and one it is far too easy to neglect.

“ Performance measurement shouldn’t be a post-mortem; it should be a health plan.”

Performance measurement (PM) is oft-maligned: organizations see it as useless or a waste of time when they should focus on results. What many miss is that without clear evidence and data on progress, it can be hard to deliver results, or even know when you’ve delivered them. Performance measurement may well be unnecessary when things are going well, but it’s hard to know if they’re going well or not without it.

Stacey Barr developed what she calls PuMP: the Performance Measurement Process, with an extra ‘u’ thrown in to make it easy to pronounce. In the book, she runs through an 8-step pilot to implementing the process in an organization. The method places heavy emphasis on using PM for improvement, not accountability: if you punish people based on what is measured, you’ll end up with useless measures, she points out.

The book is well organized and useful. A few points needed more defense or explanation: her rejection of brainstorming because not all the ideas it produces are good felt more like a PR move than a well-considered argument, and her espousal of XmR graphs as a way of reporting performance seemed overly strong as well. Since the book’s purpose is partly salesmanship for her course, that may play a role.

The key lesson from the book is engagement. Several of the 8 steps in the pilot are about getting buy-in from the organization and ensuring others feel ownership: without engagement, she argues, performance measures will be ignored at best, and more likely rejected out of hand. I suspect she’s right in that: for any process that is that embedded in an organization—including PM but also HR, IT management, and others—if it remains the project of only a few people it will not lead to the culture change necessary to provide results and maximize impact. A lesson more of us could learn.

“In this book, we begin with a simple question: Do groups usually correct individual mistakes? Our simple answer is that they do not. Far too often, groups actually amplify those mistakes.”

If you want to find out how an appellate judge will vote about an ideologically connected case, many of us would check if they were appointed by a republican or democrat. That’s a pretty good predictor. But in many areas, there is an even better predictor: who appointed the other two judges on the panel?

Being in a group affects what decisions we take. That much is clear. But should we take a decision alone or with a group? Both methods seem to work in some situations, and not work in others. In Wiser, Sunstein and Hastie set out to explore the difference.

In general, using a group does two things. It increases the cost of making the decision, because all group members have to be consulted and negotiated with: and it reduces the cost of errors, because it means the group can aggregate wisdom and ideas to minimize expensive mistakes. Or at least, that’s the theory.

In practice, groups can help or hinder. At their worst, they can amplify the errors of some of their members, get trapped in groupthink, become more polarized and extreme without become more correct, and focus only on shared information rather than the key information only some members possess. Perhaps the biggest concern is happy talk: group members go along with the consensus or say nothing is wrong, instead of providing new, sometimes critical, information. Good group design—red teams, giving equal voice to members, and other simple methods—can minimize these costs.

At their best, groups can guess how many jelly beans are in a jar. Groups are good when you need to forecast an unknown result, whether a presidential election or the number of jelly beans: they can aggregate opinions and if everyone is slightly off, the final result can often be very close because the average minimizes the individual errors.

Though Wiser discusses these themes at length, it is short on clear lessons, and indeed the book itself can feel repetitive or meandering. It is an interesting idea, and an important subject, but not as well or as clearly explored as I would have liked, making it hard to distill or learn from.