BOOK OF THE MONTH

 

Book of the Month is brought to you in association with Ron Immink. IITD members can use the code “IITD2019”  on his website which allows members to download Ron Immink's books for free, including a free Skype session him. Click HERE.

 

Unlearn - Barry O'Reilly

Review by Ron Immin

 

 

 

At the next Climate-KIC masterclass, “Fearless entrepreneurship” in Trinity College Dublin, Barry O’Reilly will be speaking about “Unlearning”. It dovetails lovely with the theme, which is less planning and more doing. In our view, it always begins and ends with numbers and a 100-day plan.

 

Mindset

But without the right mindset, that is not going to work. What got you here, won’t get you there. Highly effective leaders are constantly searching for inspiration and for new ideas. But before any real breakthroughs can happen, we need to step away from the old models, mindsets, and behaviours that are limiting our potential and current performance.

 

Unlearn

The way to think differently is to act differently. You must unlearn what you have learned. The main reason for the Romans becoming masters of the world was that having fought successively against all peoples, they always gave up their own practices as soon as they found better ones. Exceptional leaders have discovered it’s not how smart they are, how much they know, how long they have been in an industry, or what they have learned. It’s the ability to recognise when to unlearn and when to let go of past success and their outdated thinking and behaviours, and innovate

 

Training and development does not work

Most training and development efforts in businesses today routinely fail to hit the mark. Harvard Business Review article points out that American businesses spend a tremendous amount of money on employee training and education. In 2015, this number was estimated to be approximately $160 billion in the United States and $356 billion globally.

 

Be vulnerable

This first step in the cycle of unlearning requires courage, self-awareness, and humility to accept that your own beliefs, mindsets, or behaviours are limiting your potential and current performance and that you must consciously move away from them. Unlearning is an act of vulnerability—of leaving behind the certainty of what you know and opening yourself up to uncertainty.

 

Doing

Status-quo leadership is no longer an option (applying the same models and methods everywhere you go). Leaders believe they simply need to tell people to think differently, and they will act differently. This is a fallacy that must be unlearned. You have to learn by doing. With time, focus, and permission to be bold. The single most important action of any leader is to model the behaviours you wish to see others exhibit in the organisation.

 

Iterate

The best leaders don’t have all the answers; they ask better questions. The best leaders try stuff. Black box thinking! Best leaders think big, start small (small investment + small risk + small build), and create a safe environment to fail. No PowerPoint or promises with only words to back it up. Only results of actions with feedback. Relearning is a process of experimentation to try new behaviours and take in new data, new information, and new perspectives.

 

Habits

The best leaders know where they want to go. By identifying the aspiration or outcome you wish to achieve, paired with the deliberate practice to get there and starting with small steps (starting is the keyword here), you can start to move toward your desired state and achieve extraordinary results.

 

Creating atomic habits 

Leadership is about storytelling. Tell stories of what success might look like if they solved the challenge they decided to tackle. Ask people to visualise or tell themselves the story of what it would look like six months, a year, or three years after they solved that challenge. Visualising and telling stories of success in the future is a great way to unlearn your thinking and create a bold vision and definition of that success. The powerful part of telling stories is that we start to describe the behaviours that we, our people and our customers would be exhibiting if we have indeed unlearned.

 

You put numbers on everything

For instance, if you wish to leave work feeling accomplished, quantify it. How often would it be happening? Hopefully, not just once. How about four out of five days a week, or even better, 80% of the time? Using rates and ratios makes our measure of success more actionable and accountable over time.

 

Lead by example

Always remember, the best way to create new behaviours—for yourself and for your organisation—is to demonstrate them yourself and show people you are committed to improving how you work, how your systems work, and how everyone could work.

 

Starting small, even smaller than you think

The key reason for starting small is to make people feel successful as quickly as possible and to enable them to see the result of their new behaviour as they progress toward their larger aspiration or outcome. The path to success is to break down the aspiration into small, specific behaviours using a method called “Tiny Habits”. Behaviour happens when three things come together: motivation, ability, and a prompt. Doing something small can have a systemic-level impact and network effect, making something magical happen in the organisation.

 

Springboard

As you experience breakthroughs and free ourselves of your existing mental models and methods, you learn to let go of the past to achieve extraordinary results. Your breakthroughs provide the opportunity to reflect on the lessons we have learned from relearning and provide the springboard for tackling bigger and more audacious challenges ahead of us.

 

Sport

Professional athletes have long known the power of using feedback and reflection to improve their performance and achieve breakthroughs. After breakthrough, the cycle starts all over again as leaders deliberately practice unlearning, building muscle memory to push forward with new initiatives, new innovations, new ideas, and new systems of operating.

 

Task orientation

In the majority of organisations, being busy is systemic, and often for perverse reasons. You breakthrough by stepping back and reflecting on exactly what it is you are doing and the results your effort is yielding. “Did you do the tasks?” and then move on to the next one, and the next. It’s much harder to take the time to find out if the task you did actually impacted the outcomes that you were trying to achieve. Outcomes matter more than outputs.

 

Measure your outcomes over output

Strive to gather feedback in real-time to discover rapidly how your efforts have been received, thus optimising your adaptions and next actions in minutes, hours, and days rather than weeks, months, and years as might be the case with traditional approaches.

 

Declare a hypothesis for improvement that will address the challenge you’re facing
Define outcome-based measures of success before starting experiments, and then hold yourself accountable for them.
Recognise that the only true failure is the failure to learn, so learn fast.

 

Deliberate practice

The key is deliberate practice, which demands explicit focus, reflection, and taking on more challenging tasks to keep improving and progressing toward extraordinary results. That is why the people who push ahead are the ones who are constantly trying to find their knowledge thresholds, their skills thresholds, and taking one step beyond that.

 

Experimentation

Da Vinci didn’t have a to-do list; he had a to-discover list. The reason the biggest, most successful companies in the world are all technology companies is because they’ve built platforms that allow them to discover exactly how their customers interact with them and to more deeply understand their customers’ behaviours. Today’s most innovative and successful companies run thousands of experiments each year.
In 2011, Amazon had the ability to deploy software every 11.6 seconds, which means the company could discover something new every 11.6 seconds.
Recognise this?

CEOs, executives, and managers who hold onto legacy thinking and outmoded methods such as command and control—telling people what to do and exactly how to do it— are not only micromanaging through control systems designed by themselves and for themselves, they are also limiting the potential of the entire organisation. They forget what it is to problem-solve for themselves, and they embrace disempowerment to the point that having to think for themselves sparks fear. This learned helplessness halts extraordinary breakthroughs. When no decisions are made at the edges of the organisation—where the information is richest, the context most current, and the employees closest to customers, the organisation grinds to a halt.

 

Peter principle

The majority of managers have risen to their current positions based on their competency to know what to do when to do it, and always having the answer or solution at hand rather than helping others discover the answers and solutions. The end result of this very common situation is the Peter Principle, where managers rise to their highest level of incompetence and battle to stay there for fear of being found out.

 

Legacy

A worker’s role is not to think, just do. Yes, this leadership conditioning and behaviour still prevails in the majority of twenty-first-century organisations—and is still taught, modelled, and learned. Leadership is about making other people successful by helping them discover the answers for themselves and guiding them along the way. Real leadership is leaving a team, an initiative, or a business—whatever situation you decide to tackle—in a better state than when you started, with new skills, capabilities, and knowledge to cope with the road ahead, even after you’re long gone. Leaving a legacy.

 

The myth of military command and control

Great leadership consists of clearly defining purpose, intent, and the outcomes to be achieved, and then creating systems that allow people to figure out for themselves (by way of experimentation) the best ways to achieve those desired outcomes. The army relinquished command and control by its leaders in the nineteenth century, after the Napoleonic wars. They replaced it with mission intent. Leaders describe their intent—communicating the purpose of the orders, along with the key outcome to be achieved—and then trust their people closest to the situation, who have the richest information, to make decisions aligned with achieving that outcome. That is why I think you can learn so much from the military.

 

Fearless leadership

That is why we have Erwin van Beek, ex-special forces, do a 4-hour leadership session at “Fearless entrepreneurship”. Leaders should have the confidence that their team is capable of making good decisions for themselves. Clarity is the responsibility of leadership. Clear mission intent. With a number.

 

Go to the fringes

High-performance individuals and companies create systems that allow the people closest to the richest sources of information to have the authority to make decisions because they have the most context of the situation and the competence of skills required for how best to take action. Read “Employees first, customers second“.

 

Delegate

Stop making decisions yourself and let other people make decisions. It’s not about the leader solving the problem. It’s about coaching the employee to improve their capability and competency of doing the work, so they can better solve problems. The question for leaders is how they can move decision making to the appropriate individual and have the confidence necessary to delegate authority.

 

Engage with customers

For the majority of companies, engaging customers, and obtaining their feedback comprises the last step in the product journey. After we have spent significant time and money. We must unlearn the way we engage, collaborate, and create with our customers, and relearn how to interact, leverage, and connect with them to discover new innovations and breakthroughs together. Today’s most effective leaders wholeheartedly embrace the idea of removing the friction in how they communicate with customers, so they are able to solicit and receive a steady, raw feed of unsanitised information and data that is true, accurate, and as close to real-time as possible.

 

Unfiltered feedback

You need to incorporate the feedback of all your customers—both internal and external—to understand how the business is working, how the products and services you’re delivering are working, and how both can be improved. Most leaders’ default conditioning is to build or maintain layers of supervisors and managers, which creates communication handover points. These handover points always lead to slow decision making, poor collaboration, and loss of context as what’s actually happening in the organisation gets lost in the message. The best way to get actionable information is to ask your customers, putting yourself in their shoes to understand what’s really happening. Read ‘The moment of clarity“.

 

Go outside

The days of the CEO being a scary person, locked behind the door on the twenty-first floor, who had all the answers, are rapidly coming to a close. The answers to your questions aren’t in your office; they’re outside in the world, where people are using your products and services. If you really want to understand what’s going on, you’ve got to go to the source, and you’ve got to be willing to listen.

 

Remember

When you truly innovate, build the future, and courageously face down uncertainty, what happens is that complex, unpredictable, and unintended consequences occur. When you build hierarchies of knowledge or silos, and information doesn’t travel across the company, organisational learning does not occur. To prevent this, you have to train, reflect on results, and have conversations that remind people what happens when things go bad. To help its employees remember, each year NASA conducts what it calls a Day of Remembrance

 

Become Antifragile

Netflix conducts game days where, unbeknownst to the teams, parts of the company’s live production systems are randomly shut down, and their products and services start breaking. Intentionally disabling computers in Netflix’s production environment became such a habit within the company that they built a piece of software called Chaos Monkey to randomly and automatically trigger system failures to test how their systems and teams responded to outages.

 

Incentives

Leaders in most organisations today are massively incentivised to do what they’ve always done and squeeze a little bit more out of the existing system, versus taking a risk and unlearning what has delivered past success. Existing incentive structures are one of the biggest inhibitors for driving innovation in any organisation. It’s time to unlearn individual pay-for-performance incentives and relearn to create the conditions for authentic motivation, courageous behaviours, and exploring risky initiatives in a controlled manner to get the breakthroughs to achieve extraordinary results.

 

Intent

If people don’t understand or are not clear on the intent of the company, they can never move toward it. “Powerful”  explains that the litmus test was being able to stop any of the company’s employees, at any level of the company, in a break room or elevator and ask them this question: “What are the five most important things the company’s working on for the next six months?” If they couldn’t reel them off one, two, three, four, five, ideally using the same words used in communications to the staff, then the Netflix leadership was failing to do its job, not the individual.

 

Purpose

People want to have a sense of contributing to the greater good—of their organisations, their communities, and the world at large. In cases where employees have clarity of purpose in their work, alignment on how their efforts contribute to achieving it and appreciation for their efforts are enough to prompt the desired behaviours, and no incentives are needed.

 

For Jeff Bezos, at Amazon, it’s always Day One

When employees move past Day One, they become complacent and fearful, relying more on the comfort of the status quo instead of constantly seeking new frontiers and courageously leaning into the discomfort of the unknown. The former is the pathway to organisational decline and death. The latter is the pathway to greatness.

 

Action is everything

As Jeff Bezos says, “There is no Day Two—every day is Day One”. Unlearning does not lead with words; it leads with action. People do not change their mental models of the world by speaking about it; they need to experience the change to believe, feel, and see evidence of it. If you always prioritise incredible personal growth, impact, and paradigm-shifting experiences, success will gravitate toward you as if you were a magnet. So, choose not to be mediocre. Choose a life of greatness sat work, at home, in your community, and in the world.

 

 

 

 

Loonshots - Safi Bahcall

Review by Ron Immink

 

 

Innovation

“Loonshots” is a very different book about innovation and organisational design. Closer to Taleb and “Antifragile”  than “Creative construction“. Also reminds me of “The day after tomorrow“. Solid, fluid and superfluid as key concepts to manage your innovation portfolio.

Managing superfluid

Particularly superfluid is difficult. Those are the loonshots you need, but loonshots by their nature are completely and utterly unpredictable. However, the most important breakthroughs come from loonshots, widely dismissed ideas whose champions are often written off as crazy. Without loonshots companies (and empires) will eventually die.

Phase transition

Loonshots shares the lessons and learning of how to manage innovation from a loonshot perspective. It as with startups and biology, you need lots of weird ideas, and there is no way of predicting which ones will succeed. It is all to do with phase transition. Organisations work in the same way and when you start to understand why teams suddenly turn, you can start to control those transitions. The same way as temperature controls the boiling and freezing of water. Solid, fluid, superfluid.

Water

Think of the water molecules in the tub as a platoon of cadets running randomly around a practice field. When the temperature drops below freezing, it’s as if a drill sergeant blew a whistle and the cadets suddenly snapped into formation. The rigid order of the solid repels the hammer. The chaotic disorder of the liquid lets it slip through. Systems snap when the tide turns in a microscopic tug-of-war. Binding forces try to lock water molecules into rigid formation. Entropy, the tendency of systems to become more disordered, encourages those molecules to roam. As temperature decreases, binding forces get stronger and entropy forces get weaker. When the strengths of those two forces cross, the system snaps. Water freezes.

Competing forces

All phase transitions are the result of two competing forces, like the tug-of-war between binding and entropy in water. When people organise into a team, a company, or any kind of group with a mission they also create two competing forces, two forms of incentives. We can think of the two competing incentives, loosely, as stake and rank. When groups are small, for example, everyone’s stake in the outcome of the group project is high. The perks of rank, job titles or the increase in salary from being promoted, are small compared to those high stakes. As teams and companies grow larger, the stakes in outcome decrease while the perks of rank increase. When the two cross, the system snaps. Incentives begin encouraging behaviour no one wants.

Inevitable

The bad news is that phase transitions are inevitable. All liquids freeze. No group can do both at the same time, because no system can be in two phases at the same time. One molecule can’t transform solid ice into liquid water by yelling at its neighbours to loosen up a little. When the density exceeds a critical threshold, the system will flip from the smooth-flow to the jammed-flow state.

Control parameters

Identifying control parameters is the key to changing when systems will snap: when solids will melt, when traffic will jam, or when teams will begin rejecting loonshots. As the temperature of water falls, molecules vibrate more slowly until they reach a critical temperature, at which point their binding energy exceeds their entropy, and they crystallise into the rigid order of ice. That’s the liquid-to-solid phase transition.

Live on the edge

To nurturing loonshots, you need to live on the edge of a phase transition: the unique conditions under which two phases can coexist. Engineering serendipity, create the opportunity and space to explore the bizarre and creating a dynamic equilibrium between loose and structure. The magic is in the network, a shared purpose and the loose connections.

The rules

Do not undertake a program unless the goal is manifestly important and its achievement nearly impossible
If anything is worth doing, it’s worth doing to excess.
Shelter radical ideas

There is a need for separating and sheltering radical ideas—the need for a department of loonshots run by loons, free to explore the bizarre. Where failure is accepted and expected. The breakthroughs that change the course of science, business, and history, fail many times before they succeed. Sometimes they survive through the force of exceptional skill and personality. Sometimes they survive through sheer chance. In other words, the breakthroughs that change our world are born from the marriage of genius and serendipity.

Create a loonshot structure

There is a pervasive myth of the genius-entrepreneur who builds a long-lasting empire on the back of his ideas and inventions. Rather than champion any individual loonshot, the secret is to create an outstanding structure for nurturing many loonshots. Rather than focus on being a visionary innovator, be a careful gardener. Getting the touch and balance right requires a gentle helping hand to overcome internal barriers, the hand of a gardener rather than the staff of a Moses. The tips (not that dissimilar to “Zone to win“):

Separate the phases

The goal of phase separation is to create a loonshot nursery. The nursery protects those embryonic projects. It allows caregivers to design a sheltered environment where those projects can grow, flourish, and shed their warts. Tailor the tools to the phase

Love your artists and soldiers equally

Surviving those journeys requires passionate, intensely committed people—with very different skills and values. Artists and soldiers. Manage the transfer, not the technology. Manage the balance between loonshots and franchises—between scientists exploring the bizarre and soldiers assembling munitions; between the blue-sky research of Bell Labs and the daily grind of telephone operations. Rather than dive deep into one or the other, focus on the transfer between the two. Intervene when the balance breaks down. Keeping the forces in balance is so difficult because loonshots and franchises follow such different paths.

Beware the False Fail

False Fail—a result mistakenly attributed to the loonshot but actually a flaw in the test. We will see the False Fail over and over, both in science and in business. There are many reasons projects can die: funding dwindles, a competitor wins, the market changes, a key person leaves. But the False Fail is common to loonshots. Skill in investigating failure not only separates good scientists from great scientists but also good businessmen from great businessmen.

Create project champions
Fragile projects need strong hands. Great project champions are much more than promoters. They are bilingual specialists, fluent in both artist-speak and soldier-speak, who can bring the two sides together.

Listen to the Suck with Curiosity

Listening to the Suck with Curiosity (LSC), overcome the urge to defend and dismiss when attacked LSC means not only listening for the Suck and acknowledging receipt but also probing beneath the surface, with genuine curiosity, why something isn’t working, why people are not buying. It’s hard to hear that no one likes your baby. It’s even harder to keep asking why.

Ferocious attention to detail

Ferocious attention to scientific detail, or artistic vision or engineering design, is one tool, tailored to the phase, that motivates excellence among scientists, artists, or any type of creative.

Beware of the Moses trap

When ideas advance only at the pleasure of a holy leader—rather than the balanced exchange of ideas and feedback between soldiers in the field and creatives at the bench selecting loonshots on merit—that is exactly when teams and companies get trapped.

The types of loonshots

There are two types: P and S.

 - With P-type loonshots, people say, “There’s no way that could ever work” or “There’s no way that will ever catch on.” And then it does.
 - With S-type loonshots, people say, “There’s no way that could ever make money.” And then it does.
 - Deaths from P-type loonshots tend to be quick and dramatic. A flashy new technology appears (streaming video), it quickly displaces what came before (rentals), champions emerge (Netflix, Amazon), and the old guard crumbles (Blockbuster).
 - Deaths from S-type loonshots tend to be more gradual and less obvious. It took three decades for Walmart to dominate retail and variety stores to fade away. S-type loonshots are so difficult to spot and understand, even in hindsight, because they are so often masked by the complex behaviours of buyers, sellers, and markets.

 

Mindset
The book covers mindset, and there the book reminds me of “The algorithmic leader“.The difference between a system mindset and outcome mindset. Teams with an outcome mindset, analyse why a project or strategy failed. Teams with a system mindset, probe the decision-making process behind a failure. How did we arrive at that decision? System mindset means carefully examining the quality of decisions, not just the quality of outcomes. Which is why probing wins, critically, is as important, if not more so, as probing losses. Failing to analyse wins can reinforce a bad process or strategy. Always ask how the decision-making process can be improved

Examples of randomness

The book is full of examples and what it illustrates is the sheer randomness, the messiness, the serendipity of breakthrough ideas and companies. Bell lab, Genentech, Pixar, Star Wars, James Bond, IKEA but it also points out one organisation that has been at the forefront of many breakthroughs, which is DARPA. Since 1958, this one two-hundred-person research group, deep inside a massive organisation, has spun out the internet, GPS, carbon nanotubes, synthetic biology, pilotless aircraft (drones), mechanical elephants, the Siri assistant in iPhones, and more. Never underestimate the importance of government on innovation and technology development.

Lessons from DARPA

The DARPA’s principles are elevated autonomy and visibility; a focus on the best external rather than internal

 - DARPA is run like a loose collection of small startups, with no career ladder. Their employee badges are printed with an expiration date.
 - DARPA’s structure has eliminated the benefit of spending any time on politics, of trying to sound smart in meetings and put down your colleagues by highlighting the warts in their nutty loonshots so that you can curry favour and win promotions.
 - DARPA managers are broadly known in their community. They are granted authority to choose their projects, negotiate contracts, manage timelines, and assign goals. The combination of visibility and autonomy creates a powerful motivating force: peer pressure.
 - In DARPA recognition from peers is a form of intangible or soft equity. It can’t be measured through stock price or cash flows. But it can be just as strong a motivator, or even stronger, as both a carrot and a stick.

 

Your company

You won’t apply the same way to every company (most companies are not faced with problems that might be solved by a giant nuclear suppository). But every organisation can find opportunities to increase autonomy, visibility, and soft equity. Some additional tips:

Beware of the skill fit

Match employees and projects and ensure optimal skill-fit. Poor project–skill fit can also result from an overmatch: skills so far above project needs that the employee has maxed out what he or she can contribute. Employees who are not stretched by their assigned projects have little to gain from spending more time on them. How much might politics decrease and creativity improve if rewards for teams and individuals were closely and skillfully matched to genuine measures of achievement?

Watch the incentives

“Powerful” has an interesting perspective on incentives.  Competitors in the battle for talent and loonshots may be using outmoded incentive systems. Bring in a specialist in the subtleties of the art—a chief incentives officer. Companies with outstanding chief incentives officers—experts who understand the complex psychology of cognitive biases, are skilled in using both tangible and intangible equity, and can spot perverse incentives—are likely to do a better job than their competitors in attracting, retaining, and motivating great people. In other words, they will create a strategic advantage.

Management span

Wider spans (15 or more direct reports per manager) encourage looser controls, greater independence, and more trial-and-error experiments. Which also leads to more failed experiments. Narrower spans (five or fewer per manager) allow tighter controls, more redundancy checks, and precise metrics. When we assemble planes we want tight controls and narrow spans. When we invent futuristic technologies for those planes, we want more experiments and wider spans.
A wide management span helps nurture loonshots: it encourages constructive feedback from peers. Peers, rather than authority.

Disruptive innovation

The author makes a good point about loonshot versus disruptive. A loonshot refers to an idea or project that most scientific or business leaders think won’t work, or if it does, it won’t matter (it won’t make money). It challenges conventional wisdom. Whether a change is “disruptive” or not, on the other hand, refers to the effects of an invention on a market. Early-stage projects in rapidly evolving markets behave like a leaf in a tornado. You wouldn’t put a lot of faith in guessing where that leaf might end up. It’s easy to point to technologies that disrupted a market in hindsight, once the leaf has landed.

Embrace the crazies

Look for the innovation outliers (read “Quirky” and the “Rebel talent“. Perhaps everything that you are sure is true about your products or your business model is right, and the people telling you about some crazy idea that challenges your beliefs are wrong. But what if they aren’t? Wouldn’t you rather discover that in your own lab or pilot study, rather than read about it in a press release from one of your competitors? How much risk are you willing to take by dismissing their idea?

Survival

You want to design your teams, companies, and nations to nurture loonshots, in a way that maintains the delicate balance with your existing business, so that you avoid ending up like the Chinese and Roman Empire or most of the companies in your sector in the near future. See loonshots as insurance for day after tomorrow.

 

 

The Algorithmic Leader - Mike Walsh 

Review by Ron Immink

 

 

How do you make decisions? I am taking a bet that you spend very little time thinking about thinking or how and why you make the decisions you make. Let alone how you can use AI to do that even better and consistent.

 

Books

Once you have read “Principles“, you should be looking at your business in a different way. Before “Principles” there was “Making money is killing your business“. Your business as an engine or combination of (decision making) processes. That is why I started to read “The Algorithmic leader”. Managing and optimising your decision making as a leader, using and applying machine learning.

 

Algorithms

Algorithms are not some computational incantation that somehow bring machines to life. They are more like a recipe for baking a cake: a step-by-step process (mixing ingredients) to solve a problem The very concept of an algorithm predates the modern computer by several thousand years; it can be traced back to some of the greatest minds of the ancient world who also used algorithms to think through difficult challenges.

 
Deep learning
With the advent of deep learning, computers can train themselves on datasets that contain millions of inputs and outputs, evolving as they do so. Being smart when machines are smarter than you require you to become something new. You can safely assume that if something can be automated, it will be—if not by you, then almost certainly by one of your competitors.
 
Consistent
And unlike a human being, an algorithm will come to the same conclusions every single time, whether it is Monday morning or Friday afternoon, cold or hot, or after the algorithm has handled thousands of similar cases.
 
Live management
Soon algorithms will shape almost every aspect of our lives. They will determine our right to enter a country (US Customs now requires you to share your social media handles on request), buy train tickets (as happens with the social credit system in China), or shop at Amazon (Amazon can fire you as a customer if you start returning too many high-value items). Our refrigerators will keep track of what we eat, our toilets will report on our physical health, or our shoes will vibrate to alert us to walk in the direction of something we might find personally interesting.
 
35,000 decisions a day
It has been estimated that an adult might make around 35,000 decisions every single day. Your kids are unlikely to be in that position, given that an increasing number of their choices are being automated for them. Once you have experienced a world where your decisions are handled for you by smart algorithms, there is no going back. Those born after 2007, is the first not only to have had access to smartphones from birth but also to have been completely immersed in algorithmic platforms.
 
Interface
The next big shift in interface design is the move toward more natural interactions. Our bodies are becoming interfaces. Whether it be smart speakers or sensors, smart tattoos or augmented reality glasses, we are learning to sense and respond to data in a more intuitive way. The more natural the interface, the more likely we are to start forgetting about the algorithmic machinery hard at work in the background. Instead of automation creating more standardised experiences, your future customers will expect you to leverage machine learning to create more natural, personalised, human-level interactions. Human-level interfaces that understand our natural speech, recognise our faces, respond to our emotional states, and even track our gestures will be useful. They will allow us to effortlessly communicate our intentions and accomplish our objectives without resorting to command interfaces and workflows. Algorithms and data make “anticipatory design” possible. 
 
Manipulation
When algorithms become deeply embedded in our daily lives, they have the potential to greatly influence how we behave. If we reach that point, we will no longer be able to easily discern how much of our memory, experiences, tastes, or even our own identity is native to us and how much is merely the technological extensions of ourselves.
 
Optimal design of your business
So the question to ask is; if an AI were to design an organisation optimised for machine learning, how would that company operate? If you could start your business again with a clean sheet of paper and the ability to leverage AI, algorithms, and automation, what would you do differently? You need to become an algorithmic leader. The job of an algorithmic leader is not to work. Their real job is to design work. Here are the tips from the book to become one:
  • Put data at the heart of the business
  • Build a central data lake
  • Map the way you make decisions and solve problems
  • Adapt your decision making, management style, and creative output to the complexities of the machine age
  • Map your connections and relationships
  • Connect people, partners, and platforms
  • Avoid digital incrementalism.
  • Apply first principles thinking
  • Move beyond true and false
  • Break problems down into a series of smaller, more manageable problems (decomposition)
  • Separate the strategy (how to approach a problem) from the execution (crunching the data)
  • Apply probabilistic thinking or think like a gambler
  • Augment your intelligence
  • Track the results of your cognitive systems
  • Compare your decisions against people who are making decisions in a wide variety of areas
  • Keep meetings brief
  • Conduct decision audits
  • Principles rather than processes are what matter
  • Focus on the exceptions
 
Imagine
Imagine what services might be made possible? The best way to imagine a future shaped by AI is not to focus on machines and their current capabilities but to think about the potential interactions between algorithms, human behaviour, and identity. Imagine a future without your company in it. If firms only exist to either reduce or eliminate transaction costs, what if technology like blockchain could do this more effectively? Would the firm as a concept still need to exist in its current form? In the future, some firms may operate without people or locations. They will be “decentralised autonomous organisations” based entirely on smart contracts that react to data and other algorithms. Imagine what life might be like in ten years. Build a picture of what life might be like in thirty years. He then asks himself what technologies, business models, and infrastructure might, therefore, need to be in place in fifteen years, ten years, five years, and next year.
 
The book is full of examples
Publicis, a multinational marketing company, has already started using algorithms to organise and assign its 80,000 employees, including account managers, coders, graphic designers, and copywriters. Whenever there is a new project or client pitch, the algorithm recommends the right combination of talent for the best possible result.
IBM has also applied for a patent for a system that monitors its workforce with sensors that can track pupil dilation and facial expressions and then use data on an employee’s sleep quality and meeting schedule to deploy drones to deliver a jolt of caffeinated liquid, so its employees’ workday is undisturbed by a coffee break.
Rolls Royce builds a virtual copy of every engine they make, combining data insights from throughout the business with design and manufacturing data, resulting in a perfect digital twin of their underlying physical asset. The Rolls-Royce Trent engine is an early example of a digital twin. A digital twin is a digital model of a physical object or process that allows you to optimise its performance. You could build a digital twin of a manufacturing line or a factory, a self-driving car, or even just a small component in a larger system, for example.
 
Google spent two years studying 180 of its teams. It called the study Project Aristotle. The researchers discovered that the best teams at Google exhibit a range of soft skills or “group norms”: equality, generosity, curiosity about teammates’ ideas, empathy, and emotional intelligence.
For Bezos, there are two categories of decisions. Type 1 decisions are the mission-critical, high-impact choices that influence higher-level strategy and can determine your future; Type 2 decisions are the lower-stakes choices that can be reversed if need be. You are better off acting on or even automating Type 2 decisions as quickly as possible. Amazon’s senior leaders typically leave all Type 2 decisions to the teams and individuals below them so they themselves can focus on Type 1 decisions.
Rakuten created its own algorithmic brain trust. Every quarter, all the senior leaders gather to discuss data.
When you arrive for an appointment at Forward, you are scanned by a full-body scanner that checks multiple physical attributes and downloads the diagnostic data collected by your wearable devices about your physical activity levels and heart rate.
A bank started to track who was talking to whom in the company, and what the social network looked like. Then, using just those metrics, they tried to predict subjective and quantitative ratings of performance for different employees as well as self-reported job satisfaction levels. The data from even these simple employee interactions proved to be an incredibly accurate predictor of performance.
IBM has also applied for a patent for a system that monitors its workforce with sensors that can track pupil dilation and facial expressions and then use data on an employee’s sleep quality and meeting schedule to deploy drones to deliver a jolt of caffeinated liquid, so its employees’ workday is undisturbed by a coffee break.
 
About decision making
Good decisions should be difficult. Their difficulty reflects the challenging nature of the topics and issues they relate to; they require strong cognitive skills if you are to arrive at a good solution. If your decision doesn’t seem difficult to make, you are probably not asking the right questions.
About decentralised control
The British Empire, expanded globally over a hundred-year period until it managed over 20 per cent of the land on the planet without any direct control from the centre. Buccaneers, tradesmen, and merchant seamen were given lots of delegated decision making in a highly self-organised fashion. When messages went from being transported by ships, with a send and receive time of six months, to a mere six minutes, everything fell apart. Because, as Parsa explained with a wry grin, the centre suddenly started to micromanage.
 
About the law
Under the General Data Protection Regulation, which came into effect in 2018, the European Union requires companies to be able to explain a decision made by one of its algorithms. Which means there will be lawsuits that require you to reveal the human decisions behind the design of your AI systems, what ethical and social concerns you took into account, and how well you monitored the results of those systems for traces of bias or discrimination. Document your decisions carefully and make sure you understand, or at the very least trust, the algorithmic processes at the heart of your business. If an AI causes a deadly mistake, who is ultimately culpable: the programmer who designed the algorithm, the data scientist who chose the training data, the safety engineer who failed to intervene, or you, the business leader who approved the optimisation target?
 
About work
In the future, you will be either working for the algorithm or if you are lucky, on the algorithm. What happens when more and more people are employed as part of a transient workforce governed by algorithms? For example, courier nomads may have the latest holographic phones, bone-conduction headphones, and low-latency, augmented reality eyewear, but make no mistake, they will be the physical manifestation of a new algorithmic underclass. Even within organisations, you will find growing inequality and a widening gap between top executives and an outer fringe of transient workers.
 
The algorithmic leaders
  • Focus on their future customers, not their existing ones
  • Design their operating model for multipliers, not margins
  • Analyse problems from first principles, not by analogy
  • Seek to be less wrong with time, rather than always being right
  • Humanise and complexify, rather than standardise and simplify
  • Are guided by user empowerment, rather than mere regulatory compliance
  • Ask whether they have the right approach, rather than whether they are getting results
  • Manage by principles, rather than processes
  • Believe that they should automate and elevate, rather than automate and decimate
  • Transform for purpose, not just profit

 

The book is a harder version of “The new leadership literacies“. Just add algorithmic to the skill set. Combine it with some meditation and mindfulness to make sure you stay on the right side of manipulation.

 

 

 

 

 

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