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Just how expensive are all these online meetings?

July 23, 2020 by Luke Szyrmer 2 Comments

If you want a high-leverage way to improve your company’s culture, one of the highest leverage (even financially) ways to do so, is to take a close look at your meetings. This includes your regularly re-occurring ones, as well as big long ones when kicking off or closing an initiative.

sunk cost: watching a bad Netflix series to the end, even though you didn’t like season 2

Meetings are extraordinarily expensive, although they aren’t explicitly budgeted for because everyone is on a salary. It’s a “sunk cost”. It's relatively easy to calculate the cost of any regular meeting you hold using meeting cost calculators like this one. Just running it through for a small software development team I ran, it turned out that the daily standup of 14 people cost $100 per instance, multiplied by the number of days in the year, so around $22,000 per year.

The financial cost of organizing meetings can significantly exceed the budget authority of the meeting organizer, like at one mid-market manufacturer, where a junior assistant convened a 90 minute weekly meeting among middle managers that cost $15 mln/year:

For example, leaders at one large manufacturing company recently discovered that a regularly scheduled 90-minute meeting of mid-level managers cost more than $15 million annually. When asked “Who is responsible for approving this meeting?” the managers were at a loss. “No one,” they replied. “Tom’s assistant just schedules it and the team attends.” In effect, a junior VP’s administrative assistant was permitted to invest $15 million without supervisor approval. No such thing would ever happen with the company’s financial capital.

The cost aspect flies under the radar, because it's money the company was already expecting to spend. But this is a good example of confusing the expected outcomes with the underlying drivers of success. Just spending the time in meetings will not help you achieve your company's goals faster. It's spending time in high quality meetings that makes a difference.

And to do that, you need to design your meetings around the outcomes they help you achieve. If you don’t have a clear outcome in mind, then why keep meeting? Especially if you’ve already achieved that outcome?

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Filed Under: assumptions, metrics

Win the fight for attention by communicating with relevance

July 16, 2020 by Luke Szyrmer Leave a Comment

The biggest challenge when introducing a new product is establishing a connection with your audience. Often, this is because you can’t do anything else until this is in place. This detail really hit home for me, when I went to an accelerator event in Mexico.

In this 2006 photograph, a man was receiving an intramuscular injection in his left shoulder muscle from a trained, registered nurse (RN), while his family was observing from over the nurse's shoulder.
Photographer: CDC | Source: Unsplash

One of the speakers was an immunobiologist client of mine, who’d developed a unique salmonella vaccine that could be combined with other vaccines. And it looks as though his vaccine is the only salmonella one which can do that.

I’d worked with him briefly as an innovation expert, and had a discussion about commercialization options as well as some pitch training. At the time he was struggling to see entrepreneurship as a viable route to greater impact. He felt comfortable as an inventor, and wanted to do more of that, not become a businessman.

It turned out I had unleashed a force of nature. Also drilling him in giving pithy explanations helped him hone down his message to something much more concrete for anyone who wasn’t already a fellow immunobiologist, or even a scientist. This one insight allowed him to communicate the relevance of his work to the wider public.

But more importantly, he started to believe that entrepreneurship was a viable route to greater impact. As it would force him to confront institutions that held him and other scientists back domestically.

As a result of both, he’s pretty much gone from a booksy academic researcher to a serious contender in getting funding to help spread the use of his product vaccine. This is the power of relevance and empathy in an age of dwindling attention.

One of the best ways to get (and stay) relevant is to focus all of your marketing and product efforts around a client profile. In theory there are millions of ways to reach an audience; in practice, you only need to reach a specific group of people. So figure out who they are, and then just focus on them. The best way to do this is the Hero Canvas tool. Grab a copy and get a quick intro for free with my Hero Canvas course.

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Filed Under: assumptions, case study, find people, innovation, startup, stories Tagged With: attention, relevance

Why addressing errors effectively lies at the heart of team performance

July 2, 2020 by Luke Szyrmer Leave a Comment

No one wakes up in the morning excited to go to work and look ignorant, incompetent, or disruptive. While it’s not true of everyone, I think it’s fair to say that anyone who gets a job wants to be there and usually wants to do well–for the purpose of self-respect. Look at how elated most people are when they accept a job after getting an offer. It’s when they enter into the “systems” at a particular company, that everything usually takes a left turn.

Modern Times (1936) trailer: capturing the essence of managing

In established companies, it’s sadly common for employees to be habituated in a context of fear of failure. Especially if there is a lot of pressure from management to perform at a high level. There are ambitious goals, often coupled with a lack of clarity on how they will be achieved. In practice, employees focus on looking busy (however that is defined). They end up fearing failure, of not living up to expectations.

As a manager, there is a fine line to draw here. You don’t want to set the bar too low and cause everyone to just slack off. The starting point here is one of psychological safety; according to the research, this is one of the main factors driving high performance in teams. In particular, how you handle errors, failures, or surprises in a way that keeps the team accountable while enabling them to believe that they will be listened to–if they speak up.

Common error types

According to Amy Edmondson in The Fearless Organization, there are 3 different types of errors which happen professionally, and their meaning is largely driven by context:

  1. mechanical errors in a highly repeated process that just need to be minimized in frequency: this is what Modern Times parodied
  2. interaction errors which result from highly complicated relationships, especially in a larger company
  3. thwarted expectations around a goal in the context of experimentation, often a surprising result of an experiment

A large part of the challenge of large companies is that they treat all errors as if they were all #1 by default. This approach may be tied to political gamesmanship. But not everything is just a deviation from a standard (regardless of who actually decides and imposes that standard). Especially in knowledge work like software, where completing something requires you to learn something you don’t know up front. Edmondson quips, “For knowledge work to flourish, the workplace must be one where people feel able to share their knowledge!”

I don’t know who dropped this in Leeds city centre but I feel their disappointment.
Photographer: Sarah Kilian | Source: Unsplash

In my software experience, most of the problems encountered, especially around people and process, were due to #2. Company systems were wrong, inadequate or just misaligned. Unfortunately, this typically meant that a person or department was singled out and blamed. I tried hard to bring the discussion back into a discussion around how the work was done, and if something could be done to prevent a similar problem from re-occurring.

The last type (#3) is essentially an opportunity to improve the company, the product, or the workflow, packaged as an intellectual surprise. Sometimes, the team would come across a much better way to solve or define a technical problem than they had originally wanted to do otherwise. This was particularly common in the early days of designing a large system. The same can be true on the business side, if the company is open to experimentation on that end. These are so valuable, that most innovation circles try to maximize the number of these errors through structured experimentation and record-keeping, in order to speed up overall progress.

Be open to taking ownership and admitting mistakes

From the perspective of psychological safety, it’s critical to start with assuming any error is a #2. This includes assuming that the leader in the system is responsible for the system. More importantly, he is also part of the system. Which means that the manager needs to be open to letting their ego bruised, and be willing to admit mistakes in front of their fellow team members, in the service of improving life for everyone. Once I did this enough times with my team, they realized and eventually believed that I was genuinely interested in optimizing how the team worked.

Set of four brass vintage skeleton keys on neutral background. Very steampunk look!
Photographer: Jen Theodore | Source: Unsplash

Essentially the way to solve the misaligned expectations problem (bar too high vs too low) is to view the work as a system. And that way, you depersonalize the work enough, that fears become less of a driver for action. Instead, employees follow their genuine interest in improving their own work life. This allays fears of failure. And gets everyone more involved and excited.

Ultimately, you care about the output your team produces, so focus your management on that, rather than on policing individual effectiveness. Paradoxically it produces better results.

Key Takeaways

  • Psychological safety lies at the heart of high performing teams
  • Most commonly errors are assumed to be individual mistakes, rather than the result of complicated interactions gone wrong.
  • Get the team excited about improving the workflow

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Filed Under: alignment, assumptions, metrics Tagged With: digital taylorism, output, principles, process risk, throughput

Why early stage virality can indicate product readiness

June 26, 2020 by Luke Szyrmer Leave a Comment

In the early days, when I was just polishing off the manuscript of Launch Tomorrow, I gave it to a friend who also lived and breathed startups. I specifically requested that he keep it quiet and just asked for feedback. Professionally, he was a marketer but in this case I was hoping to get some honest “tough love” from him. To make sure the book would be good.

After speaking with him in person, I dropped a pdf into gmail, and forwarded it on to him. Coincidentally, I also happened to have an early trial version of Streak installed on my gmail account, which is an app which measures email opens, now primarily used by salespeople.

Over the next week or so, it turned out 37 people had opened that email 56 times in different locations around London and Europe. This simple indicator was enough to convince me that the manuscript is definitely at least a minimum viable product. If not a bit more. There were a lot of tweaks I wanted to make, but clearly my idea audience was enjoying and using it. Even though this viral spread was accidental, ultimately I was pleased that my friend had effectively proven to me that my product was ready.

This was a special case of someone who knew me well, the fact that he forwarded it without my consent and that it was re-forwarded so many times implied that my soon-to-be released product will be able to generate word of mouth referrals when I do launch. This was particularly poignant, given that this was a B2C product. Like most impulse buys, books (on their own) tend to be low $ value products. There is little margin for error with a high customer acquisition cost, yet you need to be great at generating awareness and discoverability. So you can only use channels that have a fixed cost up front but little additional variable cost of reaching another person.

Going Viral

While virality seems “free” from a financial point of view, it’s expensive in terms of your time. The idea is to create enough product (content in my case) which people naturally want to share. Once you have their attention, you include some kind of call to action which then turns into a conversion , like a sale. Or at least a micro conversion, like getting an email subscriber.

Once people hear about your idea or your product, then they decide whether to buy it or not, and also whether to share it or not. Nowadays, it paradoxically seems easier to convince people to buy an inexpensive product than it does to get them to share it (at least for me). ????

Why virality can be an engine of growth

Matthew Lieberman, author of “Social: Why Our Brains Are Wired to Connect” and professor of psychology says:

We always seem to be on the lookout for who else will find this helpful, amusing or interesting, and our brain data are showing evidence of that. At the first encounter with information, people are already using the brain network involved in thinking about how this can be interesting to other people. We’re wired to want to share information with other people. I think that is a profound statement about the social nature of our minds.

The main reason viral growth can be a massive growth engine is the fact that once you get beyond a certain tipping point, the sharing be comes so extreme that it reaches disproportionately many people. Numerically, if you see it as a coefficient, it will be multiplied with each person (or step), and that number can quickly get disproportionately large.

My high school math teacher had a good example of this compounding effect. Would you prefer to get $1 mln today, or one penny today, two pennies tomorrow, continuing to double that amount for the entire month? This is, of course a trick question, designed to put teenagers in their place. The compounding penny option ends up being a much larger amount than the initial million.

This metric of 37:1 was my viral transmission ratio on this particular event. Basically anything above 1:1 will lead to geometric growth, if it sustains at that rate. At a rate of 2:1 on a daily basis, you’d be at 2147483648 within 31 days. It’s just raw arithmetic: 2^31. So if the true long term viral transmission rate settled at 2:1 that would still mean the book had a captive audience with high latent demand-and that I needed to get it out there.

The good thing about a viral growth engine is that it’s costless growth. As you don’t spend any money on building initial awareness, any revenues you do make are fully yours. If you do have financial constraints initially this can be a good place to start.

The main drawback of viral growth is that results tend to be highly unpredictable and difficult to manufacture deliberately. Depending on how effectively you make your content unique and engaging, people will be more or less willing to share it. More often than not, all it takes is one share from someone with a large audience, and it will give you a big spike in traffic. It’s just that it’s difficult to get those initial share, particularly if no one knows who you are.

Manufacturing Engagement

The hard part is writing content good enough that people want to share it with their friends. To some extent, you can pre-test this by using what Andrew Chen’s twitter technique. He writes potential headlines as tweets, and then sees if anyone interacts with it. Once the idea is proven, via a favorite or a retweet, he uses that as a basis to write a longer piece on that topic. As a result, his growth hacking essays tend be highly focussed on his target audience’s needs. As a result of forwards, he effectively “clones” his existing audience. The content people forward tends to attract other interested in the same type of content.

Another approach is to repurpose a backlog management service like uservoice or a kanban tool like trello combined with audience interaction. You can create a backlog of writing ideas, and then have your existing audience vote on them. This way you are naturally spending your time writing things which is attractive for them. It’s effectively a vetting and prioritization system for content, similar to prioritizing features in agile software development.

If you’d like more ideas of how to experiment with growth, take a look at Your First startup experiment my book on getting you to that first experiment. De-risk your startup idea and figure out how to grow, grow, grow with Your First Startup Experiment.

Key Takeaways

  • Virality can be an engine of growth because it rapidly raises awareness at a low per-user cost
  • The key is that you have each person refer more than one person to your product
  • While the best way to get and keep this effect is to build a great product that addresses a market need, you can experiment with some tools to help engineer in virality

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Filed Under: assumptions, metrics, modelling Tagged With: faster time to market, growth, launch

Kinda Disproved: the myth of the startup garage

June 10, 2020 by Luke Szyrmer Leave a Comment

Going back to revisit my old post The Myth of the Startup Garage, I wanted to verify my statements quantitatively. In that post, I argue against garages as this magic place where entrepreneurship starts.

Vivint Solar - Solar Panels on small home with driveway from street.
Photographer: Vivint Solar | Source: Unsplash

Well, turns out I was wrong and right.

It’s true that the majority of new businesses do start in the founders’ home. Scott Shane cites that a residence, such as the home or garage is the most common place a new business is started (48% of new businesses start there). However, when measured over a 5 year period, less than 5 percent of home-based businesses move out of the founders’ home. So while the garage is a common starting place, it’s sadly a common resting place for new businesses.

Also, I argued against the idea that founders are these young whiz kids, as portrayed in the startup glossies. Depending on the actual study, the average age of successful tech startup founders is 35-42 according to the Startup Compass report, not the typical college dropout narrative in the media. If you look outside tech startups, the picture is even more stark. Founders in their 50s are 3x more likely to start a successful business.

As for coming up with the idea, reality is also a bit nuanced; startups start with what and how they know, but are open to searching for opportunities:

  • The National Federation of Independent Business (NFIB) showed that 61% of new businesses serve the same or similar customers as their founders’ previous employers
  • 66% were in a similar product line. (source: also NFIB)
  • 70.9% indicated that the identification of their business opportunities wasn’t a “one-time thing” but instead unfolded over time. (source: Hills and Singh)
  • 46.9 % of new firm founders indicated their business ideas changed between the time they first identified them and the time when they were surveyed about them. (source: Panel Study of Entrepreneurial Dynamics)

Looking at the actual data is the basis for getting a good grip on what is actually happening. So there is your weekly dose of reality.

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Filed Under: assumptions, innovation Tagged With: market risk

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    Luke Szyrmer is an innovation and remote work expert. He’s the bestselling author of #1 bestseller Launch Tomorrow. He mentors early stage tech founders and innovators in established companies. Read More…

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