Wednesday, July 1, 2020

Sunday, March 22, 2020

Remote culture


Fully remote is a culture, not a technique — a company that is not already equipped for it can handle individual contributors working from home temporarily but will struggle to let anyone go completely remote. Tellingly, these organizations almost never support home office work for managers or executives, because their decision making processes rely on face to face.

Those managers and executives certainly do whip out their laptops and iPads at home and on planes, and it’s rare not to find some weekend hours in this class of people. But the work that they do at home is solo work: asynchronous communication is the majority, and synchronous communications are used to set up a meeting at an office. Organizations have to have processes to communicate information up and down, and to make decisions based on that information. If those processes are built around office meetings, they stop working properly when important team members aren’t present, because remote meetings suck.

I think there’s lot of remote-oriented folks posting about their tools out of a genuine sense of helpfulness, and just as many blank stares on the receiving end. Instead, it would be more helpful to repost Chelsea Troy’s blog. Tools don’t fix people and process problems: the first corporations made do with quill and parchment and sailing ships, while modern corporations fail in the midst of plenty every day (never mind hard times). Extolling different collaboration tools misses the point because it doesn’t address the cultural differences between remote-rare and colocation-rare teams.

Because it is a cultural shift, going from a fully on-prem culture to a fully remote culture over the weekend is not going to just happen without some active and intent work. The good news is that there is now ample incentive to put that work in, because the alternative is to stop communicating or making decisions. Going all the way remote as Coronavirus-driven shelter-in-place orders are demanding is better than the hybrid that is tried in better times, even though it is under duress.

To be clear, I’ve worked equal amounts in remote-first and colocation-first companies, and I think that remote-first companies have a distinct advantage in the marketplace. The advantage is because there’s often more thoughtfulness and discipline devoted to communication practices. Communication processes are clearer, because chance encounters and overheard conversations aren’t a thing. A manager that is used to getting their 1:1s done by dropping by desks or taking a coffee walk will have to pay atttention and think about how to maintain communication with their team.

Decision-making processes are also clearer in remote-first, because osmosis towards a shared consensus is nearly impossible. Executives should take this time to consider how decisions are made; if the final word only happens in a room full of people, that’s going to need to change.

Unfortunately, remote-first is not a panacea, and a fully remote organization can still squander their opportunity. Anti-patterns such as closed-loop communication cells, HIPPO decisions, and analysis paralysis absolutely can and do happen.

Saturday, March 21, 2020

Engines and Fuel part two


Why don’t companies make content?

The best answer is that they have decided not to invest (or similarly, have not decided to invest yet). Companies are often aware of the gaps their customers complain about, and yet choose to prioritize other things.

A less good answer: they are not hiring the right people or incentivizing the right behavior, but still hoping or expecting that the content will magically appear. This company may still get lucky if their product is well aligned as a place for partners to work. A vendor with the perfect match of demand and platform can attract and support ecosystem with little effort, much as a flipped coin could land on its edge and balance there.

Next, the company that has hired and incentivized for content creation, but is still unsuccessful because the platform is lacking. Customers and field tech/service partners will use the tools to solve problems, more or less happily, but those solutions are on a black market for the company. Because there’s no official path to share, validate, or optionally monetize, the company is disconnected from its own content. At worst, it can find itself in the terrible position of trying to suppress content built by its own employees. Good news: these are simply product problems, fixable by a product team. Build a safe content development and execution chain and you’ve got an answer.

Finally, the company that has built tools, but cannot find people to use them: I don’t have a lot to say here, because it’s a basic product management problem. The product exists but does not fit the market, so it needs to be changed to do so.

Sunday, March 1, 2020

Finding the Price

Let’s dive once more into the licensing breach! Here’s the background:

What’s not covered? Well, when I wrote this post about evaluating a side business, it came close to the process for defining the price of a cost-plus service or product. That’s not a particularly hard task in theory:

  1. Find the cost
  2. Add a margin
  3. Adjust as needed per your favorite Economics 101 textbook

Of course, this simple approach will provoke sniffs of disdain in most software circles, where the dream is to write code once and deliver it forever. In software, the task is supposed to go like this:

  1. Find the value
  2. Subtract a discount
  3. Adjust as needed per textbook

If your software solves a million dollar a year problem and costs you $5,000 to write, you’ve got a lot of room to negotiate a price in.

Running a successful enterprise of course requires you to think about both approaches, because if you find yourself negotiating prices that are below your cost, that won’t end well.

Furthermore, the Platonic ideal of writing software once and never touching it again is pretty rare; most complex software needs to be continually maintained in order to fix bugs and keep up with changing fashions. This makes cost a little more challenging to determine, as it’s an ongoing function of R&D team size (not to mention support functions, cost of sales, &c).

Even worse, Software as a Service and other, simpler forms of term licensing require you to predict costs and values into the future and spread them out, probably in a way that front-loads your costs and back-loads your profits. In some ways this matches the realities of software development more accurately since it allows for ongoing cost and value increases, but it can also set off a treadmill of expectation increases. That is to say, a SaaS which does not continually improve will not compare well with one that gets gradually more feature-rich and nicer to use. As discussed before you could also use bands or freemium models to disproportionately allocate costs and profits across different classes of users. Or you could aggregate one class of customers into a service that you sell to another class of customers, if you’re feeling particularly Silicon Valley. All of these approaches are just abstractions over the core problem of pulling in more money than you pay out, don’t let them distract you.

So, just like license models, price is deceptively simple:

  1. More expensive than your costs
  2. Less expensive than non-consumption
  3. If you’re going to spread the cost out, make sure that you don’t drop average prices below average costs. 

Glad I could help.

Friday, February 28, 2020

Metaphors

I love words. I love to read and write. I was an English major for a reason.

As I implied in that post, it’s important to know how to use language to engage emotion. However, you also need to know when to use a particular tool and when to leave it in the box.

I used to work with a very successful CEO and CMO who would both, when feeling feisty, smack down any use of metaphor or simile  in a presentation.
  • “We’re trying to put ten pounds in a five pound bag”
  • “Support is drowning in priority one issues”
  • “Everything is coming up roses and these are our salad days”

I can still hear “just say what you mean!” in the back of my head.

  1. It is incredibly disconcerting to be forced out of flow and into analyzing your own sentences while you deliver them, so the lesson sticks
  2. The English language is just dripping in simile and metaphor (see what I did there)
  3. It’s good advice. A metaphor is assuming that your entire audience shares your level of knowledge and your set of opinions
Say you want to distinguish the capabilities of two teams. You might use a metaphor like medical specialists or sports positions. Is it truly going to land? Or are you just trying to find a way to soften a message that you’re afraid to say?

Sunday, February 16, 2020

Product Management Reading List


Inspired by Andy Nortrup’s thorough posting, I’ve dusted off my own recommended reading list. It doesn’t have reviews or feedback, just raw links. An interesting attribute of the times is that product management is recognized as an important function, but it’s not narrowly defined. That leaves a lot of latitude for recommending preparatory materials, and different lists have very different mental models of what a PM is going to do.

My approach to this has altered over the years as I’ve run more PM internships and mentored line PMs to avoid my mistakes and make their own. Specifically, I like to provide research pointers like this instead of prescriptive shortcuts; nothing kills the joy of discovery like forced march reading. While there’s a lot of interesting material here, it’s not all going to work for a given reader at the time they first see it. So poke around, find what works for you. If you’re coming from a STEM background, you may not need as much math and finance grounding as I have needed.

Product Manager Reading List

Specific to the discipline of product management

Marty Cagan, SVPG


Rob Fitzpatrick

Michael Mace


Ben Thompson, Stratechery


Eric Ries

Specific to leadership and teamwork

Kim Scott

Michael Lopp (Rands)


Passing knowledge of domains we influence and are influenced by

Thomas Freese


Seth Godin


Don Norman


Neal Stephenson


Alex Reinhart


Karen Berman


Dana Keller


Kieran Healy

Phil Simon

Sunday, January 26, 2020

Do I have a product here?


Sometimes I chat with people who are interested in starting a side business, or even leaving their $dayjob. That can be a really rewarding option if you’ve got the opportunity. Of course, there’s nothing wrong with not doing it! Some people simply don’t want to run a small business along with doing the value-adding work which brings in the money.

But if you’re willing to take on being your own boss, how should you evaluate if you’ve got a product that can float that business? Let’s work through a system for finding that answer.

Step one: Give yourself an hour per day over a week or two to do some research. You’ve got a blank sheet of paper and an idea, so let’s do some calculations and see if they can pencil out.

  • What would it cost to pursue the idea?  Do you need tools? material? People? Do you have to get certifications or build up a reputation before you can get those things? What does it cost in money and time to get to the point where you can start? What does it cost to continue operating once you start?
  • How much money must you make by what time to make it worth pursuing? Do you understand your budget? Have you considered what could be reduced and what is non-negotiable? Be honest here, if your minimum bar for quality of life requires excellent espresso every day, don’t budget for a can of Medaglia d’Oro.
  • Can you identify champions who will use your idea, gatekeepers who will allow it, buyers who will pay for it, and budget that exists today? This model is commonly used in business-to-business enterprise sales, but it’s not bad for considering any product transaction. Even if these roles are only different voices in a single consumer’s head, they will absolutely play out their functions. Consider your own purchase of a game: does your internal champion want the experience of playing it, does your internal gatekeeper approve (“what would my friends and family say”), and can you afford to buy it?


Step two: Assuming all of that pencil work comes out with a positive answer, you’re looking at refinements. Now it’s most interesting to consider: how much time will it take to prove or disprove that back-of-envelope estimate? Can you take a vacation from $dayjob and spend it on this idea? Hint: if that sounds terrible, you’re probably not going to like being your own boss. This part may be really tough because you’re going to need to validate your assumptions: talking to salespeople for quotes, talking to prospects, perhaps even asking your friends and relatives to invest. If you haven’t sold before, this is where you start learning, because if you can’t sell your idea to a friendly audience you’re certainly going to face some struggles with the outside world. In some software opportunities, it’s also necessary to ask: do you truly understand the technology that you intend to use? Do you need to spend part of this time learning to prototype your solution? Some people do very well in classes or seminars. Personally, I’d buy a stack of books and disconnect for a couple of weeks. Either is more weekends or PTO time from $dayjob.

Step three: If you’re now properly convinced you’ve got a product opportunity... how do you get from where you are now to where you want to be? How much money do you need to save? Are there trigger events or red flags you’re watching for? Now that you’re looking for the moment where you can commit to your new venture, you’re going to face additional stress from $dayjob, so keep an eye on mental and physical health.

Tuesday, January 14, 2020

Product Management Internships


An engineering internship program typically runs 6 to 12 weeks, often as a group exercise. Interns join scrums, 2-5 interns (generally 3), where there was a known deliverable on a topic of interest. They would experience the corporate version of their classes: understanding problems, sprinting to solutions, and presenting to the team on progress.

Problems to tackle will usually be areas needing investigation but not yet critical path for the business. Guidance comes from a team lead or senior individual contributor, who advises and runs a daily intern standup in addition to their team standup.

I’ve seen that program a few times. I don’t really like it... the projects can be poorly considered and don’t go anywhere, and the interns don’t end up understanding why the projects would or wouldn’t work in the real world. So it’s a lot like hackathons, only stretched over a summer instead of a week.

I’ve probably seen half a dozen force-directed graphs of data sets that could never scale at a real customer, along with a bunch of pointless dashboard re-skins. Not to mention solutions that could technically work but are not feasible in the company’s licensing model or data system.

What the interns do learn is process and culture fit. That’s not terrible, but a lot of it can frankly be taught in school instead. It’s totally wrong for product management. So how should our internships go instead?

Maybe this is regional, but in the SF Bay Area tech companies are competing for interns. You can win excellent candidates by showing why they’ll do real work which will ship. Intern wants to get a job. “Got to prove culture fit at $HouseholdBrand” is one path to that. “I shipped a feature at $Elsewhere and here it is” is another one. “Proved culture fit at $Elsewhere” is not so good.

Set that as table stakes and you’ve got a good base. Next, focus on how to teach product management. There are different philosophies for that, which I’ll touch on in another post.

Know everything, then automate!


The concept of virtual patching has set me off on a small rant.

If you’re not familiar, the concept is something like this: vulnerability scanners determine that PC42 in the CritStuff system has a nasty problem, but you can’t patch it for reasons. So instead, software magically figures out that exploiting this vulnerability requires access to port 80, and tells the nearest firewalls to drop anything headed to PC42’s port 80.

I’m down on two concepts here: the first is high risk automation. I have scars from network admission control. I’ve seen SEC filings delayed because of a properly quarantined laptop, never mind the attack ships on fire off the shoulder of Orion. Blindly implemented policy has high risk, and some knowledge of context is needed to make a proper risk-reward calculation. People aren’t perfect, but they’re better at this than software is.

The second concept I don’t trust is a requirement for pre-learning. Anything that requires the customer to learn in great detail how their systems work and what the dependencies are before they can safely act has put too much burden on the customer. Anyone remember host-based intrusion prevention systems? How about application virtualization? The environments that are simple enough to manage this way do not have sufficient resources attached to support a software vendor. Said differently, this approach has failed to find market traction enough times that it is now available as free open source.

One is supposed to argue that the virtual patching tool, like learning mode IPS before it, is able to save the customer the trouble of learning... except using those automatic tools just leads to learning about the dependency by accident instead, and therefore is still a market fail.

What about AI? What about it? A perfect robot would be more patient than a human but just as capable of learning the entire system, automating it, and maintaining the automation. But using that system would require the humans around it to either understand as well, or take a leap of faith. People will totally take that leap in order to gratify our laziness, but two or three failures will mean the system is rejected.  Can the robot be perfect? If not, can it be cheaper than a human? And is any of this conversation relevant to the far-from-perfect robots we can actually build today? Sometimes.