Michael Fichter 🚢

I help to create digital transformation winners | Digital strategist, MBA, optimist | Obsessed with creating strategic advantages in digital transformations.

[Michael Fichter 🚢 @_MichaelFichter]

https://t.co/4H4ChkMlp4

[Michael Fichter 🚢 @_MichaelFichter]

Wouldn’t it be great to pursue all the opportunities we come across?

There is only a problem with that.

Just think about opportunities as cars in a city.

The more you have of them, the slower they will move forward.

Every car will reach its destination eventually. But it might take a long time depending on the traffic.

But wouldn’t it be great to move faster?

For this, some cities build priority lanes, for example, for taxis and buses.

This is precisely what OKRs are for. They are the priority lane for your goals, moving them faster from A to B.

While this is clear, it is also essential to understand what happens to the rest of the “traffic”:

1/ They will still reach their destination, just slower. So just because something isn’t an OKR doesn’t mean nobody will progress it.

2/ If everyone uses the priority lane, it will be crowded and not fulfill its purpose anymore. OKRs only work if you limit them to a few priority topics.

[Michael Fichter 🚢 @_MichaelFichter]

Link to the report: https://t.co/6KRzrzaI3h

[Michael Fichter 🚢 @_MichaelFichter]

How not to miss the next big tech wave (despite rapid technological changes and uncertainty):

Do you remember some quotes like:

‣ "iPhone is a niche product."
(Nokia CEO Olli-Pekka Kallasvuo, in 2007)

‣  "I think there is a world market for maybe five computers."
(Thomas Watson, chairman of IBM, in 1943)

‣ "The Americans have need of the telephone, but we do not.
We have plenty of messenger boys."
(Sir William Preece, chief engineer of the British Post Office, 1876)

They all have in common that they fail to understand a technology trend.

In the past, new trends occurred every few years or even decades, so it is no wonder that companies were slow to recognize them.

However, in today's rapidly changing world, the pace of innovation has accelerated dramatically. And this requires different approaches.

One of them is Strategic Foresighting.

My weekend read has been about a foresighting study on the Future of Generative AI (link in comments).

The study identifies several Generative AI trends in healthcare innovation, educational tools, creative arts, and business automation.

The 3 most interesting ones I found were:

‣  Increasing Edge Computing.
‣  Rise of Web3-Enabled Generative AI.
‣  Advancing Blockchain-Based Decentralized AI Marketplaces.

While these trends are fascinating, the actual value of the study lies not just in the 30 trends (and 40 more opportunities identified) but in the methodology itself.

The report outlines how to conduct strategic foresighting, taking Generative AI as an example.

Strategic foresighting is a process of anticipating and planning for future changes. It involves understanding potential futures and preparing strategies to navigate them effectively.

Let's explore the 3-step process of Strategic Foresighting:

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Step #1: Scan for Trends.

You continuously monitor emerging technologies, market shifts, and societal changes here.

This reduces the time to spot changes, giving companies more time to prepare and adapt.

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Step #2: Build Scenarios and Identify Opportunities.

Create possible future scenarios and identify opportunities or threats within them.

This helps in strategic planning and ensures your strategies are resilient under various future conditions.

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Step #3: Test the Solutions.

Implement pilot projects or simulations based on the identified opportunities.

This allows for real-world testing and adaptation, ensuring practical and effective strategies.

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While the study on Generative AI is insightful, the strategic foresighting methodology truly stands out as a tool for navigating our fast-paced, uncertain world.

What are your thoughts on strategic foresighting? Have you ever applied it in your professional life? Share your experiences in the comments below!

[Michael Fichter 🚢 @_MichaelFichter]

https://t.co/f8SNMOsN3j

[Michael Fichter 🚢 @_MichaelFichter]

How does Generative AI affect the job pyramid?

GenAI fundamentally changes the way we work:

‣ Everyone will become a manager (whether you manage humans or AI models).
‣ Even whole teams could become teams of 1 (outsourcing all the operational work to AI).

This has implications for the job pyramid.

My weekend read has been a super interesting paper from Oliver Wyman that discusses how GenAI is transforming business and society (link in the comments below).

Much has been written on what type of jobs and industries are affected most by Generative AI, but how does it change the job pyramid?

According to Oliver Wyman, it comes down to 2 trends:

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Trend #1: Automation of entry-level roles.

Roles like analysts in consulting might be removed entirely from the job pyramid.

As hard as it sounds in a futuristic AI world, those roles could be automated. However, that doesn't mean there are no jobs anymore for career entrants.

In fact, it could present an excellent opportunity for them, which leads us to the next trend.

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Trend #2: First-line managers are replaced by entry-level employees (with AI skills).

As AI automates routine work, there's still a need for someone to manage these processes. Entry-level employees equipped with AI skills can elevate their work by orchestrating AI operations.

This trend will likely replace middle management with a new class of technologically savvy, agile workers who understand AI.

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While this transformation might seem distant for some companies, it raises the need for reskilling and upskilling.

How can businesses and educational institutions adapt to prepare the workforce for this new landscape?

I'd love to hear your thoughts on this.

[Michael Fichter 🚢 @_MichaelFichter]

Is the Digital and AI "More Law" becoming more important than Moore's Law?

In 1968, Robert K. Merton published his works about the "Matthew effect".

Summarized in 2 words, it is about "Cumulative advantage":

‣ The rich get richer.
‣ Early investments turn into larger returns.
‣ Children with an early advantage increase it over time.
‣ Popular products or platforms tend to attract even more users.
‣ Skilled individuals gain more opportunities to further improve their skills.

In a report published this month, McKinsey Digital calls this concept applied to digital and AI the "More Law".

It states that companies at the forefront of Data and AI will widen the gap over their competition.

What is interesting are the factors driving this.

According to their research, these are the common elements:

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1/ Technical Skills:

Successful companies invest in continuous learning and skill development in technology and coding, which is crucial due to the rapid pace of change in these fields.

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2/ Product and Platform Model:

Moving from traditional models to a product and platform approach is essential for scaling digital and AI transformations. This model involves distributing operations around specific products and platforms, eliminating operational bottlenecks like approval processes and budget requests.

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3/ Distributed Engineering Excellence:

Leading companies systematically decompose IT into microservices and adopt modern cloud and machine learning operations (MLOps) practices for scalability. They enforce modularity and engineering standards to reduce dependencies between teams and ensure rapid, controlled development and deployment of code.

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4/ Data and Analytics Integration:

Data is embedded in every working team and process. These companies develop and manage a continuous flow of data products, often combining various relevant data elements into formats that are easy to consume for many use cases.

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5/ Leadership Commitment:

The commitment and alignment of leadership around the value at stake in a digital and AI transformation are essential. This involves securing investments of time and money and ensuring that digital and AI transformations improve operational KPIs and financial performance.

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While most of us can benefit from Moore's law, the "More law" requires a more active role. The earlier you implement it, the bigger the rewards.

Which of the 5 elements do you think is most crucial?

[Michael Fichter 🚢 @_MichaelFichter]

3 Things Every Creator Can Learn from Elon Musk

Hardly anyone has had more (business) success than Elon Musk.

He is the world’s wealthiest person, and besides founding companies such as Paypal, Tesla, and SpaceX, he is also shaping the platform you are reading this on (whether you like it or not).

A Harvard Business Review article dived deep into whether those successes are coincidental or if he has a strategy.

And indeed, there are some common themes among all his ventures.

The best thing is that you do not have to build the next spaceship to use those insights, but you can use them in creating.

Here’s how:

1/ Choose challenging problems:

‣ What Elon does: He chooses problems that are complex and hard to solve. There is no upfront quick fix to solve these problems, but the vision that they might be solved draws much attention, capital, and resources toward them.

‣ What you can do: You don’t have to save the world. But focus on relevant problems and break them down.

2/ Build close systems:

‣ What Elon does: He isn’t a friend of outsourcing. Most of what he does requires doing everything from scratch and doing it better than before. That means he isn’t only building Teslas but also setting up a charging network. Even for SpaceX, about 70% of the rockets are built in-house. This also helps him eliminate the supply chain.

‣What you can do: Don’t rely on a single platform; build a direct connection with your audience via an email list.

3/ Mobilize resources:

‣ What Elon does: He has raised an astonishing 34 billion dollars across his 8 companies. This requires a lot of persuasion. He does this by being credible, putting all of his wealth from one company (e.g., Paypal) into the next. He also has a clear vision, such as communicating his strategy.

‣ What you can do: Lead by example. Write about the challenges you face and solve them. And communicate what your vision and strategy are so others can join you on the way.

[Michael Fichter 🚢 @_MichaelFichter]

3 Tips On How (Not) To Fail With OKRs

OKRs are dangerous.

It is an incredible framework that has helped many organizations to thrive. But at the same time, it was applied by many organizations and phased out again after an unsuccessful attempt. If you don’t consider a few things, OKRs will fail.

And with that, any new attempt to revive them will be much more challenging.

Here are 3 tips to take into account before wasting this opportunity:

1/ OKRs look simple at first but are hard work.

When others tell about their OKR successes, it looks easy.

Just define a few Objectives and assign them 3 to 5 Key Results. And voila: All your strategy execution problems are magically fixed.

Unfortunately, OKRs are hard work. What you don’t see is that successful OKR adoption requires:

‣ Taking time to work out a strategy.
‣ Improving the OKR process over several cycles.
‣ Having a culture in place that supports the transparency OKRs require.

2/ OKRs are a framework, not a manual to success.

There is a lot of guidance about OKRs. But nothing that you read about it is set in stone.

OKRs need to be tailored to every organization. You need to understand what instruments are already in place. And you need to work out how OKRs can interact with existing frameworks, especially in established organizations.

3/ OKRs require change management, not a big-bang rollout.

OKRs can be rolled out at the company, department, and team levels.

But that doesn’t mean it should be rolled out in the whole organization in one go.

As with every change, you need to start slow. Start with the top level or with one supporting team. And build your “guiding coalition” as Kotter would say, before rolling it out to everyone.

If you have experience with OKRs, what else would you add?

[Michael Fichter 🚢 @_MichaelFichter]

Understand The Formula And Language Of Success (To Reach Your Goals 10x Faster)

To measure success (whether as a business or a person), there is a simple formula:

Success = Strategy x Acceptance x Execution

Let's dive into its 3 elements:
‣ Strategy: You need to have goals and prioritize what is essential.
‣ Acceptance: You need to convince your team or anyone important in your environment that it is worth pursuing the strategy and working towards it.
‣ Execution: You need to break down your strategy into a plan and execute it.

If you have all the 3 elements in place, no one can stop you.

Unfortunately, being successful is not as simple as this formula indicates.

What if there was a tool that helped you with all of these 3 things?

‣ Prioritizing and choosing your goals, making them so crisp and clear that you feel you have almost reached them.
‣ Communicating your goals with ease and getting buy in from everyone whose support you need.
‣ Following through with every goal, knowing how far you have progressed at any time, and getting back on track in case you leave the path to success.

This tool exists, and I call it the language of success.

Many businesses have already successfully used it to scale their business:

‣ Google used it to align the company's objectives and foster collaboration and innovation, leading to groundbreaking projects like Google Search, Maps, and Android.
‣ Intel used it to streamline its processes and enhance productivity, contributing significantly to its dominance in the microprocessor industry.
‣ LinkedIn used it to focus on strategic growth areas, significantly expanding its professional network and services and reinforcing its position as a leading platform for professional networking.

The language I am talking about is Objectives and Key Results (OKRs).

OKRs are a strategy execution framework that ticks all of the 3 above boxes:

‣ Strategy: It requires a strategy in place, as coming up with only a few ambitious Objectives will be challenging otherwise.
‣ Acceptance: The OKR process is both top-down and bottom-up, helping shape the goals and ensuring buy-in.
‣ Execution: Every Objective has 3 to 5 measurable Key Results that make clear what is needed to achieve a goal. And to measure along the way how far you have come.

Drop me a comment for the questions you have below.

[Michael Fichter 🚢 @_MichaelFichter]

@PanchaFrench Thank you for sharing! I didn't know it and my favourite one has been "The Formula: Unlocking the Secrets to Raising Highly Successful Children" so far. I would be curious if you have read it and have an opinion on it, too.

[Michael Fichter 🚢 @_MichaelFichter]

The MBA Framework Every Creator Must Know (But You Don't Have To Spend $100k To Master It)

Most creators say an MBA is a waste of money. Instead, you better spend your time building a business.

And they are right.

I spent $100k for an MBA at a top 10 business school.

But I don't regret it either:
‣ It opened my mind to see firsthand from successful business people that anything is possible.
‣ I built a fantastic network of people I can contact anytime.
‣ I learned a lot of highly relevant skills, such as negotiating, finance, and operations management.

Most importantly, I learned to learn very effectively. This helps me continue learning and growing even after the MBA.

However, I learned a few frameworks that everyone building a business or pursuing solopreneurship must know.

And this 1 framework's name is PESTEL.

The PESTEL framework is an analytical tool used in strategic management and marketing to identify and analyze the external macro-environmental factors that can impact an organization.

PESTEL stands for:
‣ Political
‣ Economic
‣ Social
‣ Technological
‣ Environmental
‣ Legal

It helps you become aware of the factors outside your control but is essential for strategic planning and decision-making.

But why is this important?

If those factors change, they can become risks or opportunities for your business.

Here are a few examples:
‣ Economic: High inflation affecting your customers' spending can put your business at risk.
‣ Technological: Exploiting new technologies, such as Generative AI, can give you a competitive edge.
‣ Legal: New regulatory requirements can put you out of business if you fail to comply.

Being aware of the factors in each of the 6 PESTEL dimensions helps you be proactive with the things you cannot influence.

And this helps you with what matters most: Focusing on what you can control and building the business.

[Michael Fichter 🚢 @_MichaelFichter]

@ProfNancyNelson Absolutely Nancy! But have a look at the HBR article and the worksheet they provide and it will get a bit easier.

[Michael Fichter 🚢 @_MichaelFichter]

Create The Life You Want: 7 Simple Questions
(According To Harvard Business Review)

Life is busy.

We often chase success and money. But, do we stop to think about what makes life good?

You can plan your life like a business plans its success.

This helps you find out what makes you happy.

Let's look at 7 simple questions to help you figure out a great life for you.

1. What Makes a Great Life for You?
‣ Think about what makes you really happy.
‣ A great life is different for everyone. It could be a good job, happy family, or helping others.

2. What's Your Life's Purpose?
‣ Find out what you are good at and what you love.
‣ Your life's purpose is what you are meant to do.

3. What Do You Want in the Future?
‣ Imagine your perfect life in 5 to 10 years.
‣ What would make you proud?

4. How Do You Spend Your Time and Energy?
‣ Look at how you use your time.
‣ Think about family, work, learning, and fun.

5. Who Inspires You?
‣ Find people who live in a way you admire.
‣ Learn from them.

6. What Changes Can You Make?
‣ Choose what to focus on to make your life better.
‣ Sometimes this means tough choices.

7. How to Keep Improving?
‣ Set small goals.
‣ Check how you are doing regularly.

Planning your life is important. It helps you find out what makes you happiest. By answering these questions, you can make a plan for a happier life.

Start now. Think about these questions. Write down your ideas.

Your life is important. Make the best of it!

[Michael Fichter 🚢 @_MichaelFichter]

This Concept from Software Development Everyone Must Know (To Save 10x Your Money and Time)

$500 Billion.

That is the cost of the most expensive software bug in history.

The bug was part of the Y2K (Year 2000) problem, where many computer systems could not correctly handle dates beyond December 31, 1999.

This led to widespread panic and significant investment in updating systems.

Had someone discovered it before shipping to production or even during coding, the cost would have likely been only a few million.

You can also describe this as process phases:
Coding → Testing → Shipping to Production

What you want is to fix the issue as early as possible.

This is called “Shift Left”:

‣ Good: Fix the bug once a developer discovers it.
‣ Bad: Fix the bug once a user experiences it.
‣ Worst: Fix the bug once a hacker has made use of it.

But Shift Left is not only something applicable to software development. It is a mindset change.

Here are 5 more examples:

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1. Negative feedback:

‣ Good: Right after an event.
‣ Bad: Waiting until the annual performance review.
‣ Worst: Firing an employee because they never got to know the feedback.

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2. Disruptive innovations:

‣ Good: Proactively monitoring and assessing innovations.
‣ Bad: Assessing them once everyone is doing it.
‣ Worst: Being kicked out of business because of them.

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3. Health and fitness:

‣ Good: Regular exercise and a balanced diet.
‣ Bad: Starting to exercise after experiencing health issues.
‣ Worst: Suffering from chronic diseases due to prolonged neglect.

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4. Financial planning:

‣ Good: Starting to save and invest early in life.
‣ Bad: Beginning to save after significant life events.
‣ Worst: Facing financial crises due to a lack of savings and investments.

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5. Education and learning:

‣ Good: Continual learning and skill development.
‣ Bad: Seeking new skills only when job demands change.
‣ Worst: Unemployment or underemployment due to outdated skills.

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Next time you struggle to get started with something, think about this.

[Michael Fichter 🚢 @_MichaelFichter]

https://t.co/bhjLFy4UQM

[Michael Fichter 🚢 @_MichaelFichter]

The 1 Skill That Helps You To Become A Digital Transformation Winner (And Never Fear Being Replaced By AI Again)

With Generative AI improving every few days, the number of tasks that can be automated increases significantly.

Therefore, it is natural to worry about the impact of AI on your job.

However, some areas will become more critical. Those are the ones where humans have a leap.

Greg Orme mentions them as the "4 C’s" in his book "The Human Edge": Curiosity, Creativity, Collaboration, and Consciousness.

In a nutshell, you don’t have to fear AI much if you find work that:

‣ Requires you to innovate, not copy.
‣ Requires you to focus, not distract.
‣ Requires you to collaborate, not work alone.
‣ Requires you to ask questions, not answer them.

Strategic Thinking is the 1 skill that ticks all 4 boxes.

And you must master it to become a Digital Transformation Winner.

Here’s why:

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1. Operational tasks will disappear.

With AI taking more work over, you can have teams of 1 person. You can have departments of 1 person. You can even have companies of 1 person.

You need a CEO, and AI workers take care of the rest.

The rise of Solopreneurship is proof of that.

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2. Technological changes will reduce the shelf life of most skills.

The half-life period of skills is constantly dropping. To stay ahead, you need to learn fast.

But most importantly, know where you are heading towards.

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3. Decision-making in the flood of data-driven insights becomes crucial.

With AI, data-driven insights are abundant.

Strategic Thinking is essential for interpreting these insights and making informed decisions.

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What are your thoughts?

[Michael Fichter 🚢 @_MichaelFichter]

@menkesu Fully agree. Smaller and open-source LLMs will become more important this year. For most tasks the big models are not sustainable. However, key to the smaller models is high-quality data and a data strategy.