More from Hixie's Natural Log
When you build something, you have to pick some design goals and priorities. Ideally you do so explicitly, but even if you don't, you're still implicitly doing so based on your design choices. These choices are trade-offs. If you want to write a quiet song, it won't be loud. If you are writing a software tool and you want to prioritize speed over simplicity, then it won't be as simple as if you'd prioritized simplicity over speed. There are two main signs that you've succeeded at your goals. The first, and more pleasant, is that you get compliments about how your thing is like you wanted it to be. "I love that song, it's so quiet!" "Your tool is so fast!" Why thank you, that's exactly what I was going for. The second sign, though, is that you will get complaints. Specifically, people will complain that your thing does not achieve the things you didn't set out to achieve. "I wish this song was louder", "this tool is so hard to use". That you are receiving complaints at all means that people are aware of your creation; that they are complaining about what you specifically set out to make a non-goal is a side-effect of the fact that you made that trade-off. The worst thing to do, when you receive such complaints, is take them to heart and try to fix them. This is because by definition you wanted these complaints. They are a sign that the thing you built is built as you wanted to build it. The people complaining want something different, they don't want your thing. It's just that your thing is so good that it's the thing they're compelled towards even though it doesn't prioritize the things they care about most. If you try to fix these complaints, you will, again by definition, be compromising on your goals. If you make the song have a loud part, then it's no longer a quiet song. You wanted a quiet song. Now it's a song that's quiet in parts and loud in parts. It probably still doesn't satisfy the needs of the people who want a loud song, and now it also doesn't satisfy the needs of the people who wanted your original quiet song. If you make your tool easier to use by compromising on the speed, then now you have a tool that's both not as fast as it could be and not as usable as it could have been if you'd started with that as a goal. It's important, therefore, to separate out complaints into those that are complaints you expect based on your design goals (which you should acknowledge but not fix), vs complaints that are either orthogonal to your goals (which you can fix without compromising your goals), or that are in line with your goals (which you should prioritize, since that's what you said to yourself was most important in the first place).
My involvement in web standards started with the CSS working group. One of the things that we struggled with as a working group was that we would specify how the technology should work, but the browser vendors' implementations weren't exactly what we intended, and web authors would then write web pages that worked with those browsers, even though that meant the web pages themselves were also not doing things like the specifications said they should. The folks I worked with at the W3C (especially the academics and people working for organizations that did not themselves implement browsers) would frequently bemoan this state of affairs, expressing surprise at how they, the people in charge of the standards, were not being respected by the people implementing the standards. One of the key insights I had very early on in my work, before working on HTML5, which really influenced the WHATWG and its work, is the realization that the power dynamics at work were not at all the power dynamics that the folks at the W3C described. The reality of the situation was that the power lay entirely in the hands of the users. The users chose browsers. A browser vendor that ignored what the users wanted would lose market share. Market share is everything in this space. Browser vendors want users because they can convert users into dollars (in various ways, but they typically boil down to someone showing them ads and paying the browser vendors for the privilege). In turn, the browser vendors had more power than the specifications. What they implement is, by definition, what the technology is. The specification can say in absolute clarity that the keyword "marigold" should look yellow, but if a browser vendor makes it look red, then no web author is going to use it to mean yellow, and many will use it to mean red. There is a feedback loop here: if one browser implements "marigold" to mean red, and some important web site (or many unimportant web sites) rely on it, and say something like "best viewed in ThisOrThat browser!" because that's the one they use and in that browser it looks red and red is what looks best, then the other browser vendors are incentivised to make sure that the web page looks good in their browser too. Regardless of what the specification says, therefore, they are going to make "marigold" look red and not yellow. When I realized this, I also realized a corollary: if you have two competing specifications that both claim to define the same technology, but one matches what the browsers already do while the other one does not, the browser vendors are going to find it more useful to follow the one that matches what they do. This is because they can trust that implementing that specification will get them more market share. It means they won't have to stop and think at every step, "will following this specification cause me to lose users?". It is easier for them to use a specification that takes into account their needs in this way. We actually tried to explain this to the W3C membership. There was a big meeting in 2004 at Adobe in San Jose, the "W3C Workshop on Web Applications and Compound Documents". We tried to convey the above (I didn't quite understand it in the stark "power dynamic" terms yet, or at least, I didn't really express it in those terms, but if you read our position paper you can see this insight starting to crystalize). At this meeting, we made a pitch for the W3C to continue to maintain HTML and to care about what the browser vendors wanted. Representatives from Microsoft and Sun (in many ways arch enemies at the time) supported us. I seem to recall Apple being more quiet about it at the meeting but also essentially supporting the principles. The W3C membership resoundly rejected this whole concept. One of the W3C staff even explicitly said something along the lines of "if you want to do this you should do it elsewhere". That's what led to the WHATWG being founded a few weeks later. The WHATWG was founded on this core principle — the specifications need to actually specify reality. When the browsers disagree with the spec, the spec is by definition incorrect and needs to change, regardless of how much technically superior the design in the spec is. Naturally, when you provide browser vendors with something that valuable, they will follow. You end up with a weird inverted power dynamic. The spec writer (when they follow this principle) has all the power, but only within the space that the browser vendors are themselves willing to play; and the browser vendors have all the power, but only within the space that the users are willing to put up with. It's very easy to appear to be in control when you tell people to do the thing they were going to do anyway (or at least, one of the things they were willing to do if they were to think about it). There is a (probably apocryphal) quote supposedly by Alexandre Auguste Ledru-Rollin that is often cited in mockery of bad leadership, but that perfectly matches the power dynamic here: "There go my people; I must find out where they are going so I can lead them". (Thanks to Leonard Damhorst for prompting me to write this post.)
I often get asked how many people contribute to Flutter. It's a hard question to answer because "contribute" is a very vague concept. There's tens of thousands of packages on pub.dev, all of which are written by contributors to the community. There's over 100,000 of issues filed in our issue database, filed by more than 35,000 people over the years (the exact number is hard to pin down because people sometimes delete their GitHub accounts; about 700 issues have been filed by people who have since deleted their account). Many more people still have used the "thumbs-up" reaction to indicate that an issue matters to them, with almost 165,000 thumbs up from about 45,000 people. All of these people are valuable contributors to Flutter. Usually, when pressed, people try to clarify by asking about "the core team". Again though it's hard to say exactly what that means, but let's assume they mean "people with commit access". That is, people we trust enough to have added to the GitHub repo as collaborators. This includes people who work on Flutter for companies like Google, Canonical, or Nevercode, and it includes people like me who are self-employed and/or contribute to Flutter on a volunteer basis. Currently that's about 280 people. So is that the answer? Well, no, not really. Some people have commit access but aren't active (maybe they got access because of their employer, but were then reassigned to work on another project, and the bureaucracy hasn't caught up with them yet — we only audit the membership occasionally because it's rather tedious to do). Some people have been very active recently but don't have commit access (e.g. because they were just laid off and a bot automatically removed their access; they might even resume working on Flutter in the future, as a volunteer or funded by another company). So what's the answer? I recently drilled down through our data to see if I could answer this. I will caveat the following numbers by saying that this changes all the time. We added a new team member just today (hi Nate!) who is not counted as a team member in the following numbers because we collected the data a few weeks ago (it takes literally days to scrape all the data from GitHub, and then hours to explore the resulting very large and very slow spreadsheet). Also, some of my definitions are a bit arbitrary, and slightly tweaking the limits would probably change the numbers noticeably. First, I collected a list of everyone who has ever created an issue, commented on an issue, put an emoji reaction on the first comment of an issue, or submitted a PR, excluding bots and people who deleted their GitHub account. (Actually Piinks did the actual data collection. Thanks!) I limited this to a subset of the GitHub repos of the flutter org that is relatively inclusive but does not count everything (we have a lot of historical repositories and so forth). This finds about 94,357 people. (So there you go. The Flutter team is about a hundred thousand people!) To avoid padding the numbers with people who left the project long ago, and to avoid counting "drive-by" contributors who came, did a bunch of work, and then left, I then limited the data set to people who contributed over a period of more than 180 days, and who last contributed sometime in 2024. Because of the definition of "contributed" described above, that means that someone who added a thumbs-up to an issue in December 2020 and then filed an issue in January 2024, and did nothing else, is included, but someone who submitted two PRs in March 2024 is not. Like I said, this is a bit arbitrary. Anyway, that leaves 3,839 people, of which 182 currently have commit access, 27 once had commit access but don't currently (these are mainly people who either got laid off recently and had their commit access revoked by an automated process, or people who were once team members, left, lost access from inactivity long ago, and then later came to comment on issues or file new issues — it's surprisingly common for people who once worked on Flutter full time to stick around even when their employment changes), and about 3,627 people who have never had commit access. Of those who have never had commit access, 2,407 have filed at least one issue or submitted at least one PR (accounting for a total of 12,383 issues and 2,613 PRs). Of those, 341 have filed 5 to 9 issues (2,242 issues total), and 296 have filed 10 or more issues in their lifetime (7,021 total issues). Similarly, of the "never had commit access" cohort, 73 people have sent 5 to 9 pull requests in their lifetime (458 total PRs) and 47 have sent 10 or more (1,321 PRs total). (For context, 4,663 people have ever submitted a pull request, and 429 have ever submitted more than 10 PRs.) Of the people who currently have commit access, 98 people have submitted more than one PR every 3 weeks on average since they first got involved (accounting for 49,173 PRs), 75 people have closed at least one issue every 3 weeks (accounting for 48,490 total issue closures), of which 10 are not in the first group (mostly that's our triage team), and 150 people have commented at least once every 3 weeks. A follow-up question a lot of people ask is "do they all work for Google?". This is a surprisingly hard question to answer. There are a lot of weird edge cases. For example, one person worked on Flutter for a company that Google hired to work on Flutter, but then quit that company, asked for their commit privileges to be removed, but continued to be active in the community. Several people who have quit Google (such as myself), or been laid off by Google, have continued to be active in one sense or another (I think I submit more code to Flutter now than I did in my last year at Google). It's also hard to answer because a lot more people at Google contribute to Flutter than just those on Google's Flutter team, and a lot of people on Google's Flutter team contribute in ways that don't show up on GitHub (e.g. product management, marketing, developer relations, internal tooling). Of the 98 people who have commit access, have been active for more than 180 days, have contributed at least once this year, and have submitted more than one PR every 3 weeks on average for the entire time they've been contributing, I estimate (based on what I know of people's employment and so forth) that about 85% are Googlers or somehow get their funding from Google, and about 15% are currently independent of Google. (This is by no means the entirety of the Google team contributing to Flutter; as I mentioned earlier, many folks at Google working on Flutter don't appear in these statistics.) I'm not sure what conclusion to draw from this; it's both more people than I expected to see funded by Google, which is great, and fewer people that aren't funded by Google, which is less great. On the other hand, it's still a significant number of non-Google-funded people. Is it enough? I think that really depends on what your goals are. I think if your goal is for Flutter to be an order of magnitude better than other UI frameworks, then frankly no, it's not enough. There is a ton of work to be done to get there. We know what it would take, but we don't have the people to do it today. On the other hand if your goal is to be a great framework, on par with others, then it's probably adequate. It would certainly be difficult to continue to be great with fewer people today. Of course, that may change as we complete big efforts, or as we take on new ones, or as the landscape changes, it's all hard to predict. That said, I would love to see more direct contributions from non-Google sources, if for no other reason but to end this silly "will Google cancel Flutter" line of questioning that has followed the project since its inception. It's a dumb question. Flutter's an open source UI framework. It will never die. It will become old and something else will shine brighter one day, just as happens with literally every other UI framework ever. That's just how our industry works. There's no reason to believe that'll happen any time soon though, and certainly no reason for it to happen earlier for Flutter than any other modern UI framework.
I joined Google in October 2005, and handed in my resignation 18 years later. Last week was my last week at Google. I feel very lucky to have experienced the early post-IPO Google; unlike most companies, and contrary to the popular narrative, Googlers, from the junior engineer all the way to the C-suite, were genuinely good people who cared very much about doing the right thing. The oft-mocked "don't be evil" truly was the guiding principle of the company at the time (largely a reaction to contemporaries like Microsoft whose operating procedures put profits far above the best interests of customers and humanity as a whole). Many times I saw Google criticised for actions that were sincerely intended to be good for society. Google Books, for example. Much of the criticism Google received around Chrome and Search, especially around supposed conflicts of interest with Ads, was way off base (it's surprising how often coincidences and mistakes can appear malicious). I often saw privacy advocates argue against Google proposals in ways that were net harmful to users. Some of these fights have had lasting effects on the world at large; one of the most annoying is the prevalence of pointless cookie warnings we have to wade through today. I found it quite frustrating how teams would be legitimately actively pursuing ideas that would be good for the world, without prioritising short-term Google interests, only to be met with cynicism in the court of public opinion. Charlie's patio at Google, 2011. Image has been manipulated to remove individuals. Early Google was also an excellent place to work. Executives gave frank answers on a weekly basis, or were candid about their inability to do so (e.g. for legal reasons or because some topic was too sensitive to discuss broadly). Eric Schmidt regularly walked the whole company through the discussions of the board. The successes and failures of various products were presented more or less objectively, with successes celebrated and failures examined critically with an eye to learning lessons rather than assigning blame. The company had a vision, and deviations from that vision were explained. Having experienced Dilbert-level management during my internship at Netscape five years earlier, the uniform competence of people at Google was very refreshing. For my first nine years at Google I worked on HTML and related standards. My mandate was to do the best thing for the web, as whatever was good for the web would be good for Google (I was explicitly told to ignore Google's interests). This was a continuation of the work I started while at Opera Software. Google was an excellent host for this effort. My team was nominally the open source team at Google, but I was entirely autonomous (for which I owe thanks to Chris DiBona). Most of my work was done on a laptop from random buildings on Google's campus; entire years went by where I didn't use my assigned desk. In time, exceptions to Google's cultural strengths developed. For example, as much as I enjoyed Vic Gundotra's enthusiasm (and his initial vision for Google+, which again was quite well defined and, if not necessarily uniformly appreciated, at least unambiguous), I felt less confident in his ability to give clear answers when things were not going as well as hoped. He also started introducing silos to Google (e.g. locking down certain buildings to just the Google+ team), a distinct departure from the complete internal transparency of early Google. Another example is the Android team (originally an acquisition), who never really fully acclimated to Google's culture. Android's work/life balance was unhealthy, the team was not as transparent as older parts of Google, and the team focused on chasing the competition more than solving real problems for users. My last nine years were spent on Flutter. Some of my fondest memories of my time at Google are of the early days of this effort. Flutter was one of the last projects to come out of the old Google, part of a stable of ambitious experiments started by Larry Page shortly before the creation of Alphabet. We essentially operated like a startup, discovering what we were building more than designing it. The Flutter team was very much built out of the culture of young Google; for example we prioritised internal transparency, work/life balance, and data-driven decision making (greatly helped by Tao Dong and his UXR team). We were radically open from the beginning, which made it easy for us to build a healthy open source project around the effort as well. Flutter was also very lucky to have excellent leadership throughout the years, such as Adam Barth as founding tech lead, Tim Sneath as PM, and Todd Volkert as engineering manager. We also didn't follow engineering best practices for the first few years. For example we wrote no tests and had precious little documentation. This whiteboard is what passed for a design doc for the core Widget, RenderObject, and dart:ui layers. This allowed us to move fast at first, but we paid for it later. Flutter grew in a bubble, largely insulated from the changes Google was experiencing at the same time. Google's culture eroded. Decisions went from being made for the benefit of users, to the benefit of Google, to the benefit of whoever was making the decision. Transparency evaporated. Where previously I would eagerly attend every company-wide meeting to learn what was happening, I found myself now able to predict the answers executives would give word for word. Today, I don't know anyone at Google who could explain what Google's vision is. Morale is at an all-time low. If you talk to therapists in the bay area, they will tell you all their Google clients are unhappy with Google. Then Google had layoffs. The layoffs were an unforced error driven by a short-sighted drive to ensure the stock price would keep growing quarter-to-quarter, instead of following Google's erstwhile strategy of prioritising long-term success even if that led to short-term losses (the very essence of "don't be evil"). The effects of layoffs are insidious. Whereas before people might focus on the user, or at least their company, trusting that doing the right thing will eventually be rewarded even if it's not strictly part of their assigned duties, after a layoff people can no longer trust that their company has their back, and they dramatically dial back any risk-taking. Responsibilities are guarded jealously. Knowledge is hoarded, because making oneself irreplaceable is the only lever one has to protect oneself from future layoffs. I see all of this at Google now. The lack of trust in management is reflected by management no longer showing trust in the employees either, in the form of inane corporate policies. In 2004, Google's founders famously told Wall Street "Google is not a conventional company. We do not intend to become one." but that Google is no more. Much of these problems with Google today stem from a lack of visionary leadership from Sundar Pichai, and his clear lack of interest in maintaining the cultural norms of early Google. A symptom of this is the spreading contingent of inept middle management. Take Jeanine Banks, for example, who manages the department that somewhat arbitrarily contains (among other things) Flutter, Dart, Go, and Firebase. Her department nominally has a strategy, but I couldn't leak it if I wanted to; I literally could never figure out what any part of it meant, even after years of hearing her describe it. Her understanding of what her teams are doing is minimal at best; she frequently makes requests that are completely incoherent and inapplicable. She treats engineers as commodities in a way that is dehumanising, reassigning people against their will in ways that have no relationship to their skill set. She is completely unable to receive constructive feedback (as in, she literally doesn't even acknowledge it). I hear other teams (who have leaders more politically savvy than I) have learned how to "handle" her to keep her off their backs, feeding her just the right information at the right time. Having seen Google at its best, I find this new reality depressing. There are still great people at Google. I've had the privilege to work with amazing people on the Flutter team such as JaYoung Lee, Kate Lovett, Kevin Chisholm, Zoey Fan, Dan Field, and dozens more (sorry folks, I know I should just name all of you but there's too many!). In recent years I started offering career advice to anyone at Google and through that met many great folks from around the company. It's definitely not too late to heal Google. It would require some shake-up at the top of the company, moving the centre of power from the CFO's office back to someone with a clear long-term vision for how to use Google's extensive resources to deliver value to users. I still believe there's lots of mileage to be had from Google's mission statement (to organize the world’s information and make it universally accessible and useful). Someone who wanted to lead Google into the next twenty years, maximising the good to humanity and disregarding the short-term fluctuations in stock price, could channel the skills and passion of Google into truly great achievements. I do think the clock is ticking, though. The deterioration of Google's culture will eventually become irreversible, because the kinds of people whom you need to act as moral compass are the same kinds of people who don't join an organisation without a moral compass.
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Once you’ve written your strategy’s exploration, the next step is working on its diagnosis. Diagnosis is understanding the constraints and challenges your strategy needs to address. In particular, it’s about doing that understanding while slowing yourself down from deciding how to solve the problem at hand before you know the problem’s nuances and constraints. If you ever find yourself wanting to skip the diagnosis phase–let’s get to the solution already!–then maybe it’s worth acknowledging that every strategy that I’ve seen fail, did so due to a lazy or inaccurate diagnosis. It’s very challenging to fail with a proper diagnosis, and almost impossible to succeed without one. The topics this chapter will cover are: Why diagnosis is the foundation of effective strategy, on which effective policy depends. Conversely, how skipping the diagnosis phase consistently ruins strategies A step-by-step approach to diagnosing your strategy’s circumstances How to incorporate data into your diagnosis effectively, and where to focus on adding data Dealing with controversial elements of your diagnosis, such as pointing out that your own executive is one of the challenges to solve Why it’s more effective to view difficulties as part of the problem to be solved, rather than a blocking issue that prevents making forward progress The near impossibility of an effective diagnosis if you don’t bring humility and self-awareness to the process Into the details we go! This is an exploratory, draft chapter for a book on engineering strategy that I’m brainstorming in #eng-strategy-book. As such, some of the links go to other draft chapters, both published drafts and very early, unpublished drafts. Diagnosis is strategy’s foundation One of the challenges in evaluating strategy is that, after the fact, many effective strategies are so obvious that they’re pretty boring. Similarly, most ineffective strategies are so clearly flawed that their authors look lazy. That’s because, as a strategy is operated, the reality around it becomes clear. When you’re writing your strategy, you don’t know if you can convince your colleagues to adopt a new approach to specifying APIs, but a year later you know very definitively whether it’s possible. Building your strategy’s diagnosis is your attempt to correctly recognize the context that the strategy needs to solve before deciding on the policies to address that context. Done well, the subsequent steps of writing strategy often feel like an afterthought, which is why I think of diagnosis as strategy’s foundation. Where exploration was an evaluation-free activity, diagnosis is all about evaluation. How do teams feel today? Why did that project fail? Why did the last strategy go poorly? What will be the distractions to overcome to make this new strategy successful? That said, not all evaluation is equal. If you state your judgment directly, it’s easy to dispute. An effective diagnosis is hard to argue against, because it’s a web of interconnected observations, facts, and data. Even for folks who dislike your conclusions, the weight of evidence should be hard to shift. Strategy testing, explored in the Refinement section, takes advantage of the reality that it’s easier to diagnose by doing than by speculating. It proposes a recursive diagnosis process until you have real-world evidence that the strategy is working. How to develop your diagnosis Your strategy is almost certain to fail unless you start from an effective diagnosis, but how to build a diagnosis is often left unspecified. That’s because, for most folks, building the diagnosis is indeed a dark art: unspecified, undiscussion, and uncontrollable. I’ve been guilty of this as well, with The Engineering Executive’s Primer’s chapter on strategy staying silent on the details of how to diagnose for your strategy. So, yes, there is some truth to the idea that forming your diagnosis is an emergent, organic process rather than a structured, mechanical one. However, over time I’ve come to adopt a fairly structured approach: Braindump, starting from a blank sheet of paper, write down your best understanding of the circumstances that inform your current strategy. Then set that piece of paper aside for the moment. Summarize exploration on a new piece of paper, review the contents of your exploration. Pull in every piece of diagnosis from similar situations that resonates with you. This is true for both internal and external works! For each diagnosis, tag whether it fits perfectly, or needs to be adjusted for your current circumstances. Then, once again, set the piece of paper aside. Mine for distinct perspectives on yet another blank page, talking to different stakeholders and colleagues who you know are likely to disagree with your early thinking. Your goal is not to agree with this feedback. Instead, it’s to understand their view. The Crux by Richard Rumelt anchors diagnosis in this approach, emphasizing the importance of “testing, adjusting, and changing the frame, or point of view.” Synthesize views into one internally consistent perspective. Sometimes the different perspectives you’ve gathered don’t mesh well. They might well explicitly differ in what they believe the underlying problem is, as is typical in tension between platform and product engineering teams. The goal is to competently represent each of these perspectives in the diagnosis, even the ones you disagree with, so that later on you can evaluate your proposed approach against each of them. When synthesizing feedback goes poorly, it tends to fail in one of two ways. First, the author’s opinion shines through so strongly that it renders the author suspect. Your goal is never to agree with every team’s perspective, just as your diagnosis should typically avoid crowning any perspective as correct: a reader should generally be appraised of the details and unaware of the author. The second common issue is when a group tries to jointly own the synthesis, but create a fractured perspective rather than a unified one. I generally find that having one author who is accountable for representing all views works best to address both of these issues. Test drafts across perspectives. Once you’ve written your initial diagnosis, you want to sit down with the people who you expect to disagree most fervently. Iterate with them until they agree that you’ve accurately captured their perspective. It might be that they disagree with some other view points, but they should be able to agree that others hold those views. They might argue that the data you’ve included doesn’t capture their full reality, in which case you can caveat the data by saying that their team disagrees that it’s a comprehensive lens. Don’t worry about getting the details perfectly right in your initial diagnosis. You’re trying to get the right crumbs to feed into the next phase, strategy refinement. Allowing yourself to be directionally correct, rather than perfectly correct, makes it possible to cover a broad territory quickly. Getting caught up in perfecting details is an easy way to anchor yourself into one perspective prematurely. At this point, I hope you’re starting to predict how I’ll conclude any recipe for strategy creation: if these steps feel overly mechanical to you, adjust them to something that feels more natural and authentic. There’s no perfect way to understand complex problems. That said, if you feel uncertain, or are skeptical of your own track record, I do encourage you to start with the above approach as a launching point. Incorporating data into your diagnosis The strategy for Navigating Private Equity ownership’s diagnosis includes a number of details to help readers understand the status quo. For example the section on headcount growth explains headcount growth, how it compares to the prior year, and providing a mental model for readers to translate engineering headcount into engineering headcount costs: Our Engineering headcount costs have grown by 15% YoY this year, and 18% YoY the prior year. Headcount grew 7% and 9% respectively, with the difference between headcount and headcount costs explained by salary band adjustments (4%), a focus on hiring senior roles (3%), and increased hiring in higher cost geographic regions (1%). If everyone evaluating a strategy shares the same foundational data, then evaluating the strategy becomes vastly simpler. Data is also your mechanism for supporting or critiquing the various views that you’ve gathered when drafting your diagnosis; to an impartial reader, data will speak louder than passion. If you’re confident that a perspective is true, then include a data narrative that supports it. If you believe another perspective is overstated, then include data that the reader will require to come to the same conclusion. Do your best to include data analysis with a link out to the full data, rather than requiring readers to interpret the data themselves while they are reading. As your strategy document travels further, there will be inevitable requests for different cuts of data to help readers understand your thinking, and this is somewhat preventable by linking to your original sources. If much of the data you want doesn’t exist today, that’s a fairly common scenario for strategy work: if the data to make the decision easy already existed, you probably would have already made a decision rather than needing to run a structured thinking process. The next chapter on refining strategy covers a number of tools that are useful for building confidence in low-data environments. Whisper the controversial parts At one time, the company I worked at rolled out a bar raiser program styled after Amazon’s, where there was an interviewer from outside the team that had to approve every hire. I spent some time arguing against adding this additional step as I didn’t understand what we were solving for, and I was surprised at how disinterested management was about knowing if the new process actually improved outcomes. What I didn’t realize until much later was that most of the senior leadership distrusted one of their peers, and had rolled out the bar raiser program solely to create a mechanism to control that manager’s hiring bar when the CTO was disinterested holding that leader accountable. (I also learned that these leaders didn’t care much about implementing this policy, resulting in bar raiser rejections being frequently ignored, but that’s a discussion for the Operations for strategy chapter.) This is a good example of a strategy that does make sense with the full diagnosis, but makes little sense without it, and where stating part of the diagnosis out loud is nearly impossible. Even senior leaders are not generally allowed to write a document that says, “The Director of Product Engineering is a bad hiring manager.” When you’re writing a strategy, you’ll often find yourself trying to choose between two awkward options: Say something awkward or uncomfortable about your company or someone working within it Omit a critical piece of your diagnosis that’s necessary to understand the wider thinking Whenever you encounter this sort of debate, my advice is to find a way to include the diagnosis, but to reframe it into a palatable statement that avoids casting blame too narrowly. I think it’s helpful to discuss a few concrete examples of this, starting with the strategy for navigating private equity, whose diagnosis includes: Based on general practice, it seems likely that our new Private Equity ownership will expect us to reduce R&D headcount costs through a reduction. However, we don’t have any concrete details to make a structured decision on this, and our approach would vary significantly depending on the size of the reduction. There are many things the authors of this strategy likely feel about their state of reality. First, they are probably upset about the fact that their new private equity ownership is likely to eliminate colleagues. Second, they are likely upset that there is no clear plan around what they need to do, so they are stuck preparing for a wide range of potential outcomes. However they feel, they don’t say any of that, they stick to precise, factual statements. For a second example, we can look to the Uber service migration strategy: Within infrastructure engineering, there is a team of four engineers responsible for service provisioning today. While our organization is growing at a similar rate as product engineering, none of that additional headcount is being allocated directly to the team working on service provisioning. We do not anticipate this changing. The team didn’t agree that their headcount should not be growing, but it was the reality they were operating in. They acknowledged their reality as a factual statement, without any additional commentary about that statement. In both of these examples, they found a professional, non-judgmental way to acknowledge the circumstances they were solving. The authors would have preferred that the leaders behind those decisions take explicit accountability for them, but it would have undermined the strategy work had they attempted to do it within their strategy writeup. Excluding critical parts of your diagnosis makes your strategies particularly hard to evaluate, copy or recreate. Find a way to say things politely to make the strategy effective. As always, strategies are much more about realities than ideals. Reframe blockers as part of diagnosis When I work on strategy with early-career leaders, an idea that comes up a lot is that an identified problem means that strategy is not possible. For example, they might argue that doing strategy work is impossible at their current company because the executive team changes their mind too often. That core insight is almost certainly true, but it’s much more powerful to reframe that as a diagnosis: if we don’t find a way to show concrete progress quickly, and use that to excite the executive team, our strategy is likely to fail. This transforms the thing preventing your strategy into a condition your strategy needs to address. Whenever you run into a reason why your strategy seems unlikely to work, or why strategy overall seems difficult, you’ve found an important piece of your diagnosis to include. There are never reasons why strategy simply cannot succeed, only diagnoses you’ve failed to recognize. For example, we knew in our work on Uber’s service provisioning strategy that we weren’t getting more headcount for the team, the product engineering team was going to continue growing rapidly, and that engineering leadership was unwilling to constrain how product engineering worked. Rather than preventing us from implementing a strategy, those components clarified what sort of approach could actually succeed. The role of self-awareness Every problem of today is partially rooted in the decisions of yesterday. If you’ve been with your organization for any duration at all, this means that you are directly or indirectly responsible for a portion of the problems that your diagnosis ought to recognize. This means that recognizing the impact of your prior actions in your diagnosis is a powerful demonstration of self-awareness. It also suggests that your next strategy’s success is rooted in your self-awareness about your prior choices. Don’t be afraid to recognize the failures in your past work. While changing your mind without new data is a sign of chaotic leadership, changing your mind with new data is a sign of thoughtful leadership. Summary Because diagnosis is the foundation of effective strategy, I’ve always found it the most intimidating phase of strategy work. While I think that’s a somewhat unavoidable reality, my hope is that this chapter has somewhat prepared you for that challenge. The four most important things to remember are simply: form your diagnosis before deciding how to solve it, try especially hard to capture perspectives you initially disagree with, supplement intuition with data where you can, and accept that sometimes you’re missing the data you need to fully understand. The last piece in particular, is why many good strategies never get shared, and the topic we’ll address in the next chapter on strategy refinement.
A Live, Interactive Course for Systems Engineers
I’m sitting in a small coffee shop in Brooklyn. I have a warm drink, and it’s just started to snow outside. I’m visiting New York to see Operation Mincemeat on Broadway – I was at the dress rehearsal yesterday, and I’ll be at the opening preview tonight. I’ve seen this show more times than I care to count, and I hope US theater-goers love it as much as Brits. The people who make the show will tell you that it’s about a bunch of misfits who thought they could do something ridiculous, who had the audacity to believe in something unlikely. That’s certainly one way to see it. The musical tells the true story of a group of British spies who tried to fool Hitler with a dead body, fake papers, and an outrageous plan that could easily have failed. Decades later, the show’s creators would mirror that same spirit of unlikely ambition. Four friends, armed with their creativity, determination, and a wardrobe full of hats, created a new musical in a small London theatre. And after a series of transfers, they’re about to open the show under the bright lights of Broadway. But when I watch the show, I see a story about friendship. It’s about how we need our friends to help us, to inspire us, to push us to be the best versions of ourselves. I see the swaggering leader who needs a team to help him truly achieve. The nervous scientist who stands up for himself with the support of his friends. The enthusiastic secretary who learns wisdom and resilience from her elder. And so, I suppose, it’s fitting that I’m not in New York on my own. I’m here with friends – dozens of wonderful people who I met through this ridiculous show. At first, I was just an audience member. I sat in my seat, I watched the show, and I laughed and cried with equal measure. After the show, I waited at stage door to thank the cast. Then I came to see the show a second time. And a third. And a fourth. After a few trips, I started to see familiar faces waiting with me at stage door. So before the cast came out, we started chatting. Those conversations became a Twitter community, then a Discord, then a WhatsApp. We swapped fan art, merch, and stories of our favourite moments. We went to other shows together, and we hung out outside the theatre. I spent New Year’s Eve with a few of these friends, sitting on somebody’s floor and laughing about a bowl of limes like it was the funniest thing in the world. And now we’re together in New York. Meeting this kind, funny, and creative group of people might seem as unlikely as the premise of Mincemeat itself. But I believed it was possible, and here we are. I feel so lucky to have met these people, to take this ridiculous trip, to share these precious days with them. I know what a privilege this is – the time, the money, the ability to say let’s do this and make it happen. How many people can gather a dozen friends for even a single evening, let alone a trip halfway round the world? You might think it’s silly to travel this far for a theatre show, especially one we’ve seen plenty of times in London. Some people would never see the same show twice, and most of us are comfortably into double or triple-figures. Whenever somebody asks why, I don’t have a good answer. Because it’s fun? Because it’s moving? Because I enjoy it? I feel the need to justify it, as if there’s some logical reason that will make all of this okay. But maybe I don’t have to. Maybe joy doesn’t need justification. A theatre show doesn’t happen without people who care. Neither does a friendship. So much of our culture tells us that it’s not cool to care. It’s better to be detached, dismissive, disinterested. Enthusiasm is cringe. Sincerity is weakness. I’ve certainly felt that pressure – the urge to play it cool, to pretend I’m above it all. To act as if I only enjoy something a “normal” amount. Well, fuck that. I don’t know where the drive to be detached comes from. Maybe it’s to protect ourselves, a way to guard against disappointment. Maybe it’s to seem sophisticated, as if having passions makes us childish or less mature. Or perhaps it’s about control – if we stay detached, we never have to depend on others, we never have to trust in something bigger than ourselves. Being detached means you can’t get hurt – but you’ll also miss out on so much joy. I’m a big fan of being a big fan of things. So many of the best things in my life have come from caring, from letting myself be involved, from finding people who are a big fan of the same things as me. If I pretended not to care, I wouldn’t have any of that. Caring – deeply, foolishly, vulnerably – is how I connect with people. My friends and I care about this show, we care about each other, and we care about our joy. That care and love for each other is what brought us together, and without it we wouldn’t be here in this city. I know this is a once-in-a-lifetime trip. So many stars had to align – for us to meet, for the show we love to be successful, for us to be able to travel together. But if we didn’t care, none of those stars would have aligned. I know so many other friends who would have loved to be here but can’t be, for all kinds of reasons. Their absence isn’t for lack of caring, and they want the show to do well whether or not they’re here. I know they care, and that’s the important thing. To butcher Tennyson: I think it’s better to care about something you cannot affect, than to care about nothing at all. In a world that’s full of cynicism and spite and hatred, I feel that now more than ever. I’d recommend you go to the show if you haven’t already, but that’s not really the point of this post. Maybe you’ve already seen Operation Mincemeat, and it wasn’t for you. Maybe you’re not a theatre kid. Maybe you aren’t into musicals, or history, or war stories. That’s okay. I don’t mind if you care about different things to me. (Imagine how boring the world would be if we all cared about the same things!) But I want you to care about something. I want you to find it, find people who care about it too, and hold on to them. Because right now, in this city, with these people, at this show? I’m so glad I did. And I hope you find that sort of happiness too. Some of the people who made this trip special. Photo by Chloe, and taken from her Twitter. Timing note: I wrote this on February 15th, but I delayed posting it because I didn’t want to highlight the fact I was away from home. [If the formatting of this post looks odd in your feed reader, visit the original article]
One of the biggest mistakes that new startup founders make is trying to get away from the customer-facing roles too early. Whether it's customer support or it's sales, it's an incredible advantage to have the founders doing that work directly, and for much longer than they find comfortable. The absolute worst thing you can do is hire a sales person or a customer service agent too early. You'll miss all the golden nuggets that customers throw at you for free when they're rejecting your pitch or complaining about the product. Seeing these reasons paraphrased or summarized destroy all the nutrients in their insights. You want that whole-grain feedback straight from the customers' mouth! When we launched Basecamp in 2004, Jason was doing all the customer service himself. And he kept doing it like that for three years!! By the time we hired our first customer service agent, Jason was doing 150 emails/day. The business was doing millions of dollars in ARR. And Basecamp got infinitely, better both as a market proposition and as a product, because Jason could funnel all that feedback into decisions and positioning. For a long time after that, we did "Everyone on Support". Frequently rotating programmers, designers, and founders through a day of answering emails directly to customers. The dividends of doing this were almost as high as having Jason run it all in the early years. We fixed an incredible number of minor niggles and annoying bugs because programmers found it easier to solve the problem than to apologize for why it was there. It's not easy doing this! Customers often offer their valuable insights wrapped in rude language, unreasonable demands, and bad suggestions. That's why many founders quit the business of dealing with them at the first opportunity. That's why few companies ever do "Everyone On Support". That's why there's such eagerness to reduce support to an AI-only interaction. But quitting dealing with customers early, not just in support but also in sales, is an incredible handicap for any startup. You don't have to do everything that every customer demands of you, but you should certainly listen to them. And you can't listen well if the sound is being muffled by early layers of indirection.