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Let’s talk about risk

December 18, 2020 by Luke Szyrmer Leave a Comment

Earlier this week, I was on the Yeukai Business Show talking about risk management in the context of startups. Yeukai was a great discussion partner, and pulled a lot of stories out of me. This is probably the more “storified” version of my work on risk management and experiments. As someone who spent 15+ years in financial markets and now almost 10 on innovation, I wanted to share the key learnings.

So if you want to learn how the foundations of identifying your biggest risks and being able to predict profitability and increase your confidence levels, pop over there and have a listen.

You'll discover:

  • The process of mitigating risk and cutting losses
  • The common reasons for loss and bankruptcy among tech startups
  • The impact of proper risk management, as well as 3 different ways to mitigate risk

If you want to find out more, check out Your First Startup Experiment to get even more tools and techniques on this topic.

<< Help Yo' Friends

Filed Under: assumptions, Estimation, podcasts, unknown unknowns Tagged With: existential risk, market risk, process risk

How to budget for innovation

October 16, 2020 by Luke Szyrmer Leave a Comment

This week I just wanted to draw your attention to an old article on Harvard Business Review about budgeting in established companies for innovation.

Here, on average, is what they estimated they were currently spending: 85% of their resources on day-to-day operations 5% on incremental improvements that produced faster, cheaper, better sameness 5% on small sustaining innovations 5% on big, disruptive innovations When we asked the managers what a better proportion might be, their answers were: 75% on day-to-day operations 5% on incremental improvements 10% on sustaining innovations 10% on big, disruptive innovations.

Personally, I find this intuitive, because of asset allocation is part of my background in finance. In situations of partial randomness, like in the financial markets, the amount you allocate defines your expose to particular risks and profit drivers.

relative and absolute allocation matters when deciding a budget

You can’t control in advance whether an investment will go up, down, or sideways in value. But you can choose how much you allocate, both in relative and in absolute terms:

  • Relative: Relative to the budget as a whole, what % is allocated to each innovation initiative? Also, what is the relative pool of money allocated to each type of innovation?
  • Absolute: How much money are you putting in? In other words, are you ok if you lose 100% of it?

The big challenge really, with budgeting for innovation in established companies, is that it’s typically done on an annual basis. Whereas new product development occurs on a much shorter cycle time. That way you are making big decisions about funding without the benefit of market feedback and other considerations which are critical tactically.

<< Help Yo' Friends

Filed Under: assumptions, innovation, release planning, Risk Tagged With: market risk, process risk

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!”

Your riskiest assumptions are probably related to your prospects and customers. Establish empathy quickly with your target prospect, figure out what's valuable, and get your innovation into the market.

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!

Launch Tomorrow

Landing Pages for your Lean Startup

  • Free Tools
  • About
  • Members
  • Corporate Innovation
  • Blog

Let’s talk about risk

December 18, 2020 by Luke Szyrmer Leave a Comment

Earlier this week, I was on the Yeukai Business Show talking about risk management in the context of startups. Yeukai was a great discussion partner, and pulled a lot of stories out of me. This is probably the more “storified” version of my work on risk management and experiments. As someone who spent 15+ years in financial markets and now almost 10 on innovation, I wanted to share the key learnings.

So if you want to learn how the foundations of identifying your biggest risks and being able to predict profitability and increase your confidence levels, pop over there and have a listen.

You'll discover:

  • The process of mitigating risk and cutting losses
  • The common reasons for loss and bankruptcy among tech startups
  • The impact of proper risk management, as well as 3 different ways to mitigate risk

If you want to find out more, check out Your First Startup Experiment to get even more tools and techniques on this topic.

<< Help Yo' Friends

Filed Under: assumptions, Estimation, podcasts, unknown unknowns Tagged With: existential risk, market risk, process risk

How to budget for innovation

October 16, 2020 by Luke Szyrmer Leave a Comment

This week I just wanted to draw your attention to an old article on Harvard Business Review about budgeting in established companies for innovation.

Here, on average, is what they estimated they were currently spending: 85% of their resources on day-to-day operations 5% on incremental improvements that produced faster, cheaper, better sameness 5% on small sustaining innovations 5% on big, disruptive innovations When we asked the managers what a better proportion might be, their answers were: 75% on day-to-day operations 5% on incremental improvements 10% on sustaining innovations 10% on big, disruptive innovations.

Personally, I find this intuitive, because of asset allocation is part of my background in finance. In situations of partial randomness, like in the financial markets, the amount you allocate defines your expose to particular risks and profit drivers.

relative and absolute allocation matters when deciding a budget

You can’t control in advance whether an investment will go up, down, or sideways in value. But you can choose how much you allocate, both in relative and in absolute terms:

  • Relative: Relative to the budget as a whole, what % is allocated to each innovation initiative? Also, what is the relative pool of money allocated to each type of innovation?
  • Absolute: How much money are you putting in? In other words, are you ok if you lose 100% of it?

The big challenge really, with budgeting for innovation in established companies, is that it’s typically done on an annual basis. Whereas new product development occurs on a much shorter cycle time. That way you are making big decisions about funding without the benefit of market feedback and other considerations which are critical tactically.

<< Help Yo' Friends

Filed Under: assumptions, innovation, release planning, Risk Tagged With: market risk, process risk

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!”

Your riskiest assumptions are probably related to your prospects and customers. Establish empathy quickly with your target prospect, figure out what's valuable, and get your innovation into the market.

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

<< Help Yo' Friends

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

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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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