News on our book

There’s news on the book!

Refresher: a few months ago, O’Reilly asked to publish the book that Ben Gaines and I co-wrote this year on product management in enterprise software. We’ve been in editing cycles since then, getting feedback and some really awesome reviews from some big names. I’m super excited for y’all to see the final product.

Based on the feedback we received, we’ve decided to change the name – Make It So is no more. Our new title is Building for Business: Product Management in Enterprise Software. While I loved the Trek reference, I have to concede that it’s a little niche. “Building for Business” is catchier, I think (I mean, for product management – let’s not get carried away), and more germane.

You can learn all about the book at the (new) website: BuildingForBusiness.com. The old site will now redirect there, too. At the site, you can also read a sample chapter and get a heads-up when the book is released. Signups, I’m happy to say, have been brisk.

The book is also now up on O’Reilly’s website, though not available for preorders yet. I’m told that pre-orders will be available prior to publication. Go check it out!

How highly productive companies and nations are alike

I’ve been thinking a lot lately about the origins of productivity. Specifically, how many of the factors that contribute to it are similar between nations and companies.

The big governance factors behind national productivity are pretty well-understood: the rule of law, contract enforcement, private & intellectual property, investment in human capital, political stability. Big-D Democracy is not necessarily on that list (though hugely important for other reasons), but there are certain cultural factors that are often related as well: social trust, egalitarianism, the free flow of information, and openness to new ideas. More generally, there is a sense that as an individual, it’s in my interest to “follow the rules,” because that’s how I will get ahead.

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The Distributed Company

I’ve said before that distributed working models – which I prefer to the term “remote working” but whatever – are a disruptive organizational technology cycle that is already well underway. The number of salaried, professional workers who work remotely at least part-time has been growing slowly, but steadily, for two decades.

 

In some professions, this trend is more pronounced than in others. Even in tech, I personally find that remote working is actually much more common than many people seem to think. Remote arrangements, whether just working from home or from another city/state, are frequently granted on the basis of political weight (eg. longtime employees or executives) and/or without labeling them as such. So-and-so employee simply lives elsewhere, but isn’t called a “remote employee” per se.

Like any disruptive technology, distributed working has its critics who dismiss it as infeasible and unrealistic. And to be sure, it’s still improving (albeit steadily). But when I look at the broadening set of tools available to collapse the productive distance between professionals, as well as remote collaboration habits from other fields like gaming, the more convinced I am that this model is going to eat “the office.” One model of a high-productivity firm of the future will be a distributed one, where many or nearly all employees are based in separate towns, cities, states and even countries. This type of firm is able to use technology to most efficiently source talent regardless of location and route tasks throughout the organization, leaving geo-constrained firms at a permanent competitive disadvantage.

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Learning by doing

Recently, I took on a new challenge that has stretched my boundaries a bit. If you’re into product management, I recommend it to you, too. I opened a store.

Product management is one of those gigs where it just takes time and experience to build your skills. But like a lot of things in life, I’ve found that I’ve improved and gotten better not when times were easy and good, but rather when I’ve struggled. I’ve long said that the best training ground for becoming a product manager is not to hop right into working with a first-class, dominant product, but instead, to start in the bottom/middle of the pack, where you have to fight and scramble. My first PM gig was perfect in this way: we were fighting tooth and nail against a much larger, aggressive competitor on one end, and commoditizing, “free” solutions on the other. Interesting times.

Any product manager, but especially in enterprise software, has to try to build empathy with their users. We usually do this through tried-and-true methods like customer interviews, job shadowing, questionnaires, and many other forms of research. These are all effective when done well, but they’re really attempts to make up for the fact that most of us just don’t have the same experiential background that our users do. The career paths that lead into a software vendor’s product team and a retail brand’s digital marketing group are usually quite different. I’ve never run a digital analytics group for a major corporation, or a brand’s data science center, or a company’s digital marketing division, and nor have the vast majority of my peers. I know most of these folks’ pain points pretty well… but do I really get it? That’s been a nagging doubt that has always bugged me.

I was pondering this not long ago when an idea struck me. Why not open my own ecommerce store and give it a go myself?

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What I would do to fix Twitter

Twitter has had a spate of very bad press recently, mostly for good reasons that I don’t need to rehash here. Lots of ink has been spilled about what ails the company, but suffice to say, Twitter’s lack of high-quality, professional, and most importantly, full-time management is obviously its biggest single issue. Until that is fixed, nothing else probably matters.

Nevertheless, Twitter’s much-beleaguered product team has had a lot of turnover, and it shows in their paucity of product evolution. Twitter has crowed loudly about such new enhancements as 280 characters, Moments and “Twitter Lite,” among other things you probably don’t care about, as if small-ball like this actually matters, while ignoring the burning, revenue-stagnant ship they’re on.

So, as a product manager who works on products designed to make money, I have some suggestions. I’m not talking to Twitter’s product team here – they’re smart people, and I no doubt have had blueprints for many of these ideas ready for some time. Twitter’s executive management and board, on the other hand, need to listen, or get out of the way. Twitter’s window of opportunity for becoming a first-tier social platform has likely already closed – that race with Facebook was lost long ago.

Twitter can be something else entirely, though, which is still both valuable and inimitable, while its core network of high-value users contributing real-time content still exists. That network is undeniably slipping away, though. Battered by abuse, choked with spam and drowned out by bots, what makes Twitter great is dying. Here are some ways to save it.

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The three types of enterprise software

“Enterprise software” can obviously encompass a ton of different products and services, but I find it useful to break down our market into three broad categories that help inform product managers’ vision for their product:

  • Back-office products
  • Iterative products
  • Transformative solutions

One thing about enterprise software that makes it unique from consumer-facing is that its path to market and selling strategy is usually a fundamental part of the product itself. Businesses, especially in the “enterprise tier” (however you care to classify that), do not often buy, adopt or test out lots of software products on a whim; there are just too many legitimate concerns around risk, security, control, etc. Each of these categories has a meaningfully different path to market that product managers have to design for and build a product strategy around, even (or especially) if the ultimate goal is to go up-market (which – spoiler alert! – it usually is).

I’m going to talk a little about each category, how they’re interrelated, and how enterprise products can (sometimes) move between them.

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When lies aren’t lies

Note: this was originally a digression in my last post, Relevancy and Truth, but I decided it worked better as a standalone piece.


When someone asks your opinion about a topic, do you always answer with completely unvarnished honesty? Do you always give the answer you know or believe to be true?

The answer is no, of course you don’t. We all filter our self-expression through the lenses of what we believe others expect from us and how we think our responses will be received. This distorting effect is widely understood, from research psychology and behavioral economics to opinion polling. In short, people routinely voice opinions they know to be either false, or at least uncertain.

This is not exactly “lying.” It’s not deception; if anything, it’s more like self-deception. It gets to the core of how humans think and present themselves, and I think it’s more important than ever in understanding the mass psychology of the social web.

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Relevancy and Truth

One of the more non-consensus views I hold is that the most venerable institutions of journalism – eg. The New York Times and Washington Post – are more likely to exist in something approximating their existing form in 50 or 100 years than are the big eyeball platforms like Google and Facebook. The recent controversy over “fake news” on both platforms demonstrates why.

The big criticism of these platforms today boils down to their respective services being increasingly gamed to deliver inaccurate, misleading or offensive content. For Google’s part, fraudulent information will occasionally appear at the top of search results for certain queries, serving up content on how Donald Trump really won the popular vote, or Holocaust denial, or crystals that cure cancer or something. At Facebook, fake news spreads like kudzu among and between communities primed to click on the agitprop of the day. In short, the two companies that organized the world’s information and social graph are grappling with how to handle a fundamental dilemma between relevancy and truth, which strikes to the heart of the advertising model that underlies their respective empires.

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There are no GAFAs in enterprise

Many of us who run in software/tech circles tend to form exaggerated notions of just how dominant particularly popular vendors are. I ran across some enterprise software market share numbers recently that I think are pretty interesting to illustrate how our perceptions match up to reality.

Salesforce is currently the leading CRM vendor in the world. Yet that market-leading share is only about 18% of their total market:

Of course, this is a particularly Salesforce-friendly report from IDC. Personally, I think it’s exaggerated – I’m not sure I believe Salesforce has literally double the market presence of Oracle or SAP. Gartner put out a report just last year whose extrapolations wouldn’t match this. Different firms, different methodologies, etc etc.

Don’t misunderstand me – Salesforce is an absolutely tremendous company, and their share is growing fast. Yet for all you hear about Salesforce CRM, would you have guessed that, at most, maybe 1 in 6 enterprise CRM customers use them?

Next, consider Slack. Lots of people, especially in tech and media (two industries whose lanes tend to cross a lot), think Slack is utterly ubiquitous. But it is not. Anecdotally, I know swaths of people outside of tech/media who’ve never heard of it. But more interestingly, IDC also says that in the workplace collaboration software market, Slack only commands about 5% of the market. Compare that with 37% for Microsoft, with their Skype for Business and now Teams products.

Again – Slack is a truly tremendous product, and company. (I’ve personally built a game bot on their platform, which was surprisingly cool!) But I suspect that a lot of tech people hold vastly exaggerated ideas about either how widespread they are in their market, or how easy it will be to displace well-entrenched incumbents in a product space that many customers don’t perceive as critical. (I have a different blog post brewing about that last part.)

Personally, I come from the Marketing Clouds world. Market share numbers there are highly unreliable, closely questioned and never really a good apples-to-apples comparison. Nevertheless, the big three – Adobe, Salesforce and Oracle – constitute the biggest part of the market. IBM still owns a surprisingly large chunk of it, too (again, depending on how you slice the numbers).

As I’ve said before, there are no GAFAs in enterprise. There are no monopolists – just some major players who own big slices of the market, and then dozens or hundreds of others behind. Nor do I see this changing anytime soon. This is great news for innovators. Selling in enterprise is difficult, but for the most part, we do not encounter the same kinds of insurmountable obstacles to adoption that most consumer web products do today. That’s cool.

More on this to come.

Smart and Dumb

About ten years ago, I realized something significant: there really are no innately “smart” and “dumb” people. Or, at least, there are so few of them as to make those labels, at a minimum, inadequate. Realizing this had far-reaching implications for how I understood others that I continue to process.

There are at least two major problems with the concept of “smart/dumb” humans. The first is the idea of intelligence itself. Namely, no one can tell you what it means. Is being smart being able to sound glib, deploying just the right bon mots and being charming? Maybe… but a lot of people mask profound ignorance by being glib. Surely a brilliant engineer or poet or quant or essayist could qualify as “smart” too. There’s nothing natural about any of these skills; they’re simply activities that humans have found a way to direct their mental energies into in a way others find interesting and recognizable.

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