Exponential Organizations by Salim Ismail

One day I stumbled came across Ismail’s 45 minute talk at Singularity University about Exponential Organizations and was fascinated by everything I heard. I just had to read the book.

And wow, this book was awesome.

Not only is it crammed full of optimism about the future, it gives us tips on how to position our businesses (large and small), to take advantage of the opportunities.

And it carries a warning.

Those businesses that do not evolve, will not survive.

I encourage you to buy this book and read it in full, but in the meantime, here are my notes on Exponential Organizations: Why new organizations are ten times better, faster, and cheaper than yours (and what to do about it) by Salim Ismail, Michael S. Malone, Yuri van Geest.

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Introduction

• An Exponential Organization is one whose impact (or output) is disproportionally large – at least 10 x larger – compared to it’s peers because of the use of new organizational techniques that leverage accelerating technologies.

Ray Kurzweil, who has studied this phenomenon for thirty years, to make four signature observations:

1. First, the doubling pattern identified by Gordon Moore in integrated circuits applies to any information technology. Kurzweil calls this the Law of Accelerating Returns (LOAR) and shows that doubling patterns in computation extend all the way back to 1900, far earlier than Moore’s original pronouncement.
2. Second, the driver fueling this phenomenon is information. Once any domain, discipline, technology or industry becomes information-enabled and powered by information flows, its price/performance begins doubling approximately annually.
3. Third, once that doubling pattern starts, it doesn’t stop. We use current computers to design faster computers, which then build faster computers, and so on.
4. Finally, several key technologies today are now information-enabled and following the same trajectory. Those technologies include:
   • artificial intelligence (AI),
   • robotics,
   • biotech and bioinformatics,
   • medicine,
   • neuroscience,
   • data science,
   • 3D printing,
   • nanotechnology
   • and even aspects of energy

When facing exponential growth, the experts in almost every field always projected linearly, despite the evidence before their eyes.

Kurzweil took Moore’s Law several steps further, noting that every information-based paradigm operates in the same way, something he called the Law of Accelerating Returns (LOAR).

Ten years ago we had five hundred million Internet-connected devices.

Today there are about eight billion.

By 2020 there will be fifty billion and a decade later we’ll have a trillion Internet-connected devices as we literally information-enable every aspect of the world in the Internet of Things.

The Internet is now the world’s nervous system, with our mobile devices serving as edge points and nodes on that network.

Think about that for a second: we’ll be jumping from eight billion Internet-connected devices today to fifty billion by 2025, and to a trillion a mere decade later.

We like to think that thirty or forty years into the Information Revolution we are well along in terms of its development.

But according to this metric, we’re just 1 percent of the way down the road.

Not only is most of that growth still ahead of us, all of it is. And everything is being disrupted in the process.

Rapid or disruptive change is something that large, matrixed organizations find extremely difficult.

Indeed, those who have attempted it have found that the organization’s “immune system” is liable to respond to the perceived threat with an attack.

Two key factors enabled Waze to succeed, and those two factors hold true for all next-generation ExO companies:

1. Access resources you don’t own. In Waze’s case, the company made use of the GPS readings already on its users’ smartphones.
2. Information is your greatest asset. More reliably than any other asset, information has the potential to double regularly. Rather than simply assembling assets, the key to success is accessing valuable caches of existing information.

The real, fundamental question of our exponential age is: What else can be information-enabled?

The key outcome when you access resources and information-enable them is that your marginal costs drop to zero.

Quite possibly the granddaddy of information-based ExOs is Google, which doesn’t own the web pages it scans. Its revenue model, the butt of many jokes ten years ago, has enabled Google to become a $400 billion company, a milestone it reached by essentially manipulating textual (and now video) information. LinkedIn and Facebook together are worth over $200 billion, and that’s just as a result of digitizing our relationships—that is, turning them into information.

CHAPTER THREE The Exponential Organization

Massive Transformative Purpose (MTP) Exponential Organizations, almost by definition, think BIG.

There’s a good reason for that: if a company thinks small, it is unlikely to pursue a business strategy that will achieve rapid growth.

• TED: “Ideas worth spreading.”
• Google: “Organize the world’s information.”
• X Prize Foundation: “Bring about radical breakthroughs for the benefit of humanity.”
• Quirky: “Make invention accessible.”
• Singularity University: “Positively impact one billion people.”

None states what the organization does, but rather what it aspires to accomplish.

The aspirations are neither narrow nor even technology-specific.

Rather, they aim to capture the hearts and minds—and imaginations and ambitions—of those both inside and (especially) outside the organization.

Some aim to transform the planet, others just an industry. But radical transformation is the name of the game.

The most important outcome of a proper MTP is that it generates a cultural movement—what John Hagel and John Seely Brown call the “Power of Pull.” That is, the MTP is so inspirational that a community forms around the ExO and spontaneously begins operating on its own, ultimately creating its own community, tribe and culture.

Martin Seligman, a leading expert on positive psychology, differentiates between three states of happiness:

1. the pleasurable life (hedonistic, superficial),
2. the good life (family and friends)
3. and the meaningful life (finding purpose, transcending ego, working toward a higher good)

Five external characteristics that define an Exponential Organization, for which we use the acronym SCALE:

1. Staff on Demand
2. Community & Crowd
3. Algorithms
4. Leveraged
5. Assets
6. Engagement

Staff on Demand

The half-life of a learned skill used to be about thirty years.

Today it’s down to about five years.

In any information-enabled business a large internal staff seems increasingly unnecessary, counterproductive and expensive.

Gigwalk, which relies on half a million smart-phone-enabled workers, offers an example of how this new world of employment works.

When Proctor and Gamble needs to know how and where its merchandise is being placed on Walmart shelves around the world, it can use Gigwalk’s platform to instantly deploy thousands of people who are paid a few dollars to walk into Walmart and check the shelves.

Results come in within an hour.

In years past, having a large workforce differentiated your enterprise and allowed it to accomplish more.

Today, that same large workforce can become an anchor that reduces maneuverability and slows you down.

Community & Crowd

“If you build communities and you do things in public,” he says, “you don’t have to find the right people, they find you.”

“At the top of every one of these communities is a benevolent dictator.” You need strong leadership to manage the community, because although there are no employees, people still have responsibilities and need to be held accountable for their performances.

Already, ExOs are leveraging community and crowd for many functions traditionally handled inside the enterprise, including idea generation, funding, design, distribution, marketing and sales.

This shift is powerful and taps into what university professor and social media guru Clay Shirky calls cognitive surplus. “The world has over a trillion hours a year of free time to commit to shared projects,” he said in a recent TED radio broadcast.

And that’s just today.

By 2020, when three billion additional minds using inexpensive tablets join the two billion currently online, Shirky’s trillion hours per year will triple.

Algorithms

Today, the world is pretty much run on algorithms.

From automotive anti-lock braking to Amazon’s recommendation engine; from dynamic pricing for airlines to predicting the success of upcoming Hollywood blockbusters; from writing news posts to air traffic control; from credit card fraud detection to the 2 percent of posts that Facebook shows a typical user—algorithms are everywhere in modern life.

Machine Learning is the ability to accurately perform new, unseen tasks, built on known properties learned from training or historic data, and based on prediction.

Deep Learning is a new and exciting subset of Machine Learning based on neural net technology. It allows a machine to discover new patterns without being exposed to any historical or training data.

In the same way that today we can no longer handle the complexities of air traffic control or supply chain management without algorithms, almost all the business insights and decisions of tomorrow will be data-driven.

AI and algorithms to mitigate and compensate for many of the following heuristics in human cognition:

• Anchoring bias: Tendency to rely too heavily, or “anchor,” on one trait or piece of information when making decisions.
• Availability bias: Tendency to overestimate the likelihood of events with greater “availability” in memory, which can be influenced by how recent the memories are or how unusual or emotionally charged they may be.
• Confirmation bias: Tendency to search for, interpret, focus on and remember information in a way that confirms one’s preconceptions.
• Framing bias: Drawing different conclusions from the same information, depending on how or by whom that information is presented.
• Optimism bias: Tendency to be over-optimistic, overestimating favorable and pleasing outcomes.
• Planning fallacy bias: Tendency to overestimate benefits and underestimate costs and task-completion times.
• Sunk-cost or loss-aversion bias: Disutility of giving up an object is greater than the utility associated with acquiring it.
• Complete list of all cognitive biases: http://en.wikipedia.org/wiki/List_of_cognitive_biases

Leveraged Assets

Recently there’s been an accelerating trend towards outsourcing even mission-critical assets.

Non-ownership, then, is the key to owning the future—except, of course, when it comes to scarce resources and assets.

Tesla owns its own factories and Amazon its own warehouses.

When the asset in question is rare or extremely scarce, then ownership is a better option.

But if your asset is information-based or commoditized at all, then accessing is better than possessing.

Engagement

Properly implemented, Engagement creates network effects and positive feedback loops with extraordinary reach.

Today, more than seven hundred million people around the world play online games.

Other games that use this technique include:

• MalariaSpot (hunt malaria parasites in real images),
• GalaxyZoo (classify galaxies according to their shapes) and
• Foldit (help biochemists combat AIDS and other diseases by predicting and producing protein models)

“Gamification should empower people, not exploit them. It should feel good at the end of the day because you made progress towards something that mattered to you.”

To be successful, every gamification initiative should leverage the following game techniques:

• Dynamics: motivate behavior through scenarios, rules and progression
• Mechanics: help achieve goals through teams, competitions, rewards and feedback
• Components: track progress through quests, points, levels, badges and collections

CHAPTER FOUR Inside the Exponential Organization

Exponential Organization can be encompassed with the acronym SCALE, so too can an ExO’s internal mechanisms be expressed with the acronym IDEAS.

• Interfaces
• Dashboards
• Experimentation
• Autonomy
• Social Technologies

Interfaces

Interfaces are filtering and matching processes by which ExOs bridge from SCALE externalities to internal IDEAS control frameworks.

They are algorithms and automated workflows that route the output of SCALE externalities to the right people at the right time internally.

A classic example is Google’s AdWords, which is now a multi-billion dollar business within Google.

A key to its scalability is self-provisioning—that is, the interface for an AdWords customer has been completely automated such that there is no manual involvement.

The X Prize Foundation has created mechanisms and dedicated teams for each of its prizes.

TED has strict guidelines that help its many “franchised” TEDx events around the world deliver with consistency.

And Uber has its own ways of handling its army of drivers.

Dashboards

There has always been a tension in business created by the need to balance instrumentation and data collection versus running the company and getting things done. Collecting internal progress statistics take time, effort and expensive IT. That’s why results were usually tracked annually or, at best, quarterly.

Today’s startups (as well as more mature enterprises) are leveraging wireless broadband, the internet, sensors and the cloud to track this same data in real time.

Experimentation

We define Experimentation as the implementation of the Lean Startup methodology of testing assumptions and constantly experimenting with controlled risks.

Autonomy

We describe Autonomy as self-organizing, multi-disciplinary teams operating with decentralized authority.

Valve Software, a game company, is a most unusual enterprise. It has 330 staffers but no classic management structure, reporting lines, job descriptions or regular meetings.

Instead, the company hires talented, innovative self-starters, who decide which projects they wish to join.

They are also encouraged to start new projects, so long as they fit the company’s MTP.

Autonomy is a prerequisite for permissionless innovation

Social Technologies

Social technology is finding fertile ground because the workplace has become increasingly digitized.

Social technology has 3 key objectives:

1. Reduce the distance between obtaining (and processing) information and decision making
2. Migrate from having to look up information to having it flow through your perception
3. Leverage community to build out ideas

From our perspective, Social Technologies are comprised of 7 key elements:

1. Social objects
2. Activity streams
3. Task management
4. File sharing
5. Telepresence
6. Virtual worlds
7. Emotional sensing

CHAPTER FIVE Implications of Exponential Organizations

In this chapter, we’ll examine in depth some of the characteristics of an ExO ecosystem.

In particular, we’ve identified 9 key dynamics at play:

1. Information Accelerates Everything

In 1995, 710 million rolls of film were developed at thousands of processing centers.

By 2005, nearly 200 billion digital photographs, equaling about eight billion rolls, had been taken and edited, stored and displayed in ways that were unimaginable just a few years before.

Today, web users upload almost one billion photographs per day to sites like Snapchat, Facebook and Instagram.

As we add trillions of sensors on every device, process and person, the process will accelerate even faster to an almost unimaginable pace (Big Data).

A final outcome of this trend is that we seem to be entering an era of “winner-takes-all” markets.

There’s really only one search engine (Google), one auction site (eBay) and one e-commerce site (Amazon).

Network effects and customer experience lock-in seem to be at the root of this fundamental change in the nature of competition.

2. Drive To Demonetization

One of the most important—and least celebrated—achievements of the Internet during the last decade was that it cut the marginal cost of marketing and sales to nearly zero.

By this we mean that with the web, it is possible to promote an online product worldwide for a tiny fraction of what it cost just twenty-five years ago.

A case in point: it costs Uber essentially zero to add an additional car and driver to its fleet.

By the same token, Quirky can find its next consumer product for essentially zero.

ExOs are able to scale their businesses with near 100 percent variable costs, even in traditionally capital-expenditure-heavy industries.

As technology brings us a world of abundance, access will triumph over ownership.

By comparison, scarcity of supply or resources tends to keep costs high and stimulates ownership over access.

3. Disruption is the New Norm

We see a consistent set of steps around disruptive innovation comprising the following:

• Domain (or technology) becomes information-enabled
• Costs drop exponentially and access is democratized
• Hobbyists come together to form an open source community
• New combinations of technologies and convergences are introduced
• New products and services appear that are orders of magnitude better and cheaper
• The status quo is disrupted (and the domain gets information-enabled)

We are seeing this evolution occur in drones, DNA sequencing, 3D printing, sensors, robotics and, certainly, Bitcoin.

4. Beware the “Expert”

History has shown that the best inventions or solutions rarely come from experts; they almost always come from outsiders.

That is, from people who aren’t domain experts but who offer a fresh perspective.

5. Death to the Five-Year Plan

In an exponential world, the five-year plan is not only unworkable, it is seriously counterproductive, and perhaps, deadly.

The future is changing so quickly that any forward look is likely to produce false scenarios, so much so that today’s five-year plans have a high probability of offering the wrong advice.

ExOs, sees five-year plans being replaced with the following elements:

• MTPs for overall guidance and emotional enrollment.
• Dashboards to provide real time information on how a business is progressing.
• Leveraging “Moments of Impact” for clean, productive decision-making.
• A one-year (at most) operating plan that is connected to the Dashboard.

6. Smaller Beats Bigger (aka Size Does Matter, Just not the Way You Think)

The answer to the question of how big an Exponential Organization can get yields yet another, more precise, question: How quickly can you convert exponential growth into the critical mass needed to become a platform?

Once that happens there is no practical limit.

7. Rent, Don’t Own

It is estimated there are now hundreds of “fablabs” operating around the world.

Soon, every town and neighborhood will have one, meaning that any individual or small team will be able to rent equipment and be as capital-empowered as an established corporation.

Today, airlines pay for engines by the number of hours flown.

In other words, something as expensive and complex as an aircraft engine has now become a rented, pay-as-you-go asset, rather than an expensive internal business unit.

8. Trust Beats Control and Open Beats Closed

Five key precepts to Zappos that drive culture across the organization:

1. Vision: What you’re doing
2. Purpose: Why you do it
3. Business model: What will fuel you as you’re doing it
4. Wow and uniqueness factors: What sets you apart from others
5. Values: What matters to you

Anything predictable has been or will be automated by AI or robots, leaving the human worker to handle exceptional situations.

At Facebook, however, development teams enjoy the full trust of management.

Any team can release new code onto the live site without oversight.

As a management style, it seems counterintuitive, but with individual reputations at stake—and no one else to catch shoddy coding—Facebook teams end up working that much harder to ensure there are no errors.

The result is that Facebook has been able to release code of unimaginable complexity faster than any other company in Silicon Valley history.

In the process, it has seriously raised the bar.

9. Everything is Measurable and Anything is Knowable

We usually track our health using just three basic metrics: temperature, blood pressure and pulse rate.

Now, imagine if we could measure each one of those ten trillion cells—and not with just three metrics, but with a hundred.

We are moving toward a world in which everything will be measured and anything can be knowable, both in the world around us and within our bodies.

Only enterprises that plan for this new reality will have a chance at long-term success.

CHAPTER SIX Starting an ExO

 

Step 1: Select an MTP (Massive Transformative Purpose).

Begin by asking the question: What is the biggest problem I’d like to see solved?

Identify that problem space and then come up with an MTP for it.

Even as a child, Elon Musk, perhaps the world’s most celebrated entrepreneur today, had a burning desire to address energy, transportation and space travel at a global level.

His three companies (SolarCity, Tesla and SpaceX) are each addressing those spaces.

Each has a Massive Transformative Purpose.

It’s the burning passion to solve an obsessive, complex problem that keeps an entrepreneur pushing along the rollercoaster ride of ebullience and despair that is the story of every startup.

Kahlil Gibran: “Work is love made visible. The goal is not to live forever; the goal is to create something that will.”

Step 2: Join or Create Relevant MTP Communities

There is a fundamental DNA path dependency here.

Are you primarily a community or are you primarily a company?

The reason you have to ask yourself this is because sooner or later the two will come in conflict. We [DIY Drones] are primarily a community.

Every day, we make decisions that disadvantage the company to bring advantage to the community.

According to Mullenweg, “Whenever this moment comes up, always bet on the community, because that’s the difference between long-term thinking and short-term thinking.”

Basically, if you get the community right, opportunities will arise. If you get community wrong, the engine of innovation dissolves and you won’t have a company anymore.

Step 3: Compose a Team

The following roles are critical if founding ExO teams are to deliver diverse backgrounds, independent thought and complementary skills:

• Visionary/Dreamer:
• User Experience Design:
• Programming/Engineering:
• Finance/Business:

Two distinct sets of skills:

• Discovery skills: The ability to generate ideas—to associate, question, observe, network and experiment.
• Delivery skills: The ability to execute ideas—to analyze, plan, implement, follow through and be detail-oriented.

Step 4: Breakthrough Idea

The three key success factors for an ExO idea are:

1. First, a minimum 10x improvement over the status quo.
2. Second, leveraging information to radically cut the cost of marginal supply (i.e., the cost to expand the supply side of the business should be minimal).
3. Third, the idea should pass the “toothbrush test” originated by Larry Page: Does the idea solve a real customer problem or use case on a frequent basis? Is it something so useful that a user would go back to it several times a day?

Silicon Valley is littered with the carcasses of companies with great technologies searching for a problem to solve.

There is no shortage of either ideas or new technologies.

After all, everybody in a place like Silicon Valley has an idea for a new tech business.

Instead, the key to success is relentless execution, hence the need for passion and the MTP.

Entrepreneurial success rarely comes from the idea.

Instead, it comes from the founding team’s never-say-die attitude and relentless execution.

As investor Fred Wilson says, “Startups should be hunch-driven early on, and data-driven as they scale.”

Step 5: Build a Business Model Canvas

Credit: Alexander Osterwalder.

Step 6: Find a Business Model

Eight ways to build a business model when the underlying information is free:

1. Immediacy:
   • Immediacy is the reason people order in advance on Amazon or attend the theater on opening night.
   • Being the first to know about or experience something has intrinsic cultural, social and even commercial value.
   • In short: time confers privilege.
2. Personalization:
   1. Having a product or service customized just for you not only gives added value in terms of quality of experience and ease-of-use or functionality, it also creates “stickiness,” as both parties are invested in the process.
3. Interpretation:
   • Even if the product or service is free, there is still considerable added value to any service that can help shorten the learning curve to using it—or using it better.
   • Kelly often jokes: “Software: free; the manual: $10,000.”
4. Authenticity:
   • Added value comes from a guarantee that the product or service is real and safe—that it is, in Kelly’s words, “bug-free, reliable and warranted.”
5. Accessibility:
   • Ownership requires management and maintenance.
   • In an era where we own hundreds of apps on several platforms, any service that helps us organize everything and improve our ability to find what we need quickly is of particular value.
6. Embodiment:
   • Digital information has no “body,” no physical form, until we give it one—high definition, 3D, a movie screen, a smartphone.
   • We willingly pay more to have free software delivered to us in the physical format we prefer.
7. Patronage:
   • “It is my belief that audiences WANT to pay creators,” Kelly wrote. “Fans like to reward artists, musicians, authors and the like with tokens of their appreciation, because it allows them to connect.
   • But they will only pay if it is very easy to do, the amount is reasonable, and they feel certain the money will directly benefit the creators.” He adds that another benefit of a simple payment process is that it capitalizes on users’ impulsiveness.
   • Examples include iTunes songs and Spotify, as well as Netflix subscriptions.
   • Customers choose to pay for each of these services even though the same content can be acquired through piracy.
8. Findability:
   • A creative work has no value unless its potential audience can find it.
   • Such “findability” only exists at the aggregator level, as individual creators typically get lost in the noise.
   • Thus, attaching yourself to effective channels and digital platforms like app stores, social media sites or online marketplaces where potential users can find you has considerable value to creators (and, ultimately, to users).

Step 7: Build the MVP

The MVP is a kind of applied experiment to determine the simplest product that will allow the team to go to market and see how users respond

Feedback loops can then rapidly iterate the product to optimize it and drive the feature roadmap of its development.

Step 8: Validate Marketing and Sales

Once the product is being used in its chosen market(s), a customer acquisition funnel will need to be established to help drive new visitors to the product. Its role is to qualify potential customers and convert them into users and paying customers.

• Acquisition: How do users locate you? (Growth metric)
• Activation: Do users have a great first experience? (Value metric)
• Retention: Do users come back? (Value metric)
• Revenue: How do you make money? (Value metric)
• Referral: Do users tell others? (Growth metric)

Step 9: Implement SCALE and IDEAS

1. MTP: Formulate an MTP in a particular problem space, one that all founders feel passionate about.
2. Staff on Demand: Use contractors, SoD platforms wherever possible; keep FTEs to a minimum.
3. Community & Crowd: Validate idea in MTP communities. Get product feedback. Find co-founders, contractors and experts. Use crowdfunding and crowdsourcing to validate market demand and as a marketing technique.
4. Algorithms: Identify data streams that can be automated and help with product development. Implement cloud-based and open source machine and deep learning to increase insights.
5. Leveraged Assets: Do NOT acquire assets. Use cloud computing, TechShop for product development. Use incubators like Y Combinator and Techstars for office, funding, mentoring and peer input. Starbucks as office.
6. Engagement: Design product with engagement in mind. Gather all user interactions. Gamify where possible. Create a digital reputational system of users and suppliers to build trust and community. Use incentive prizes to engage crowd and create buzz.
7. Interfaces: Design custom processes for managing SCALE; do not automate until you’re ready to scale.
8. Dashboards: Set up OKR and value, serendipity, and growth metrics dashboards; do not implement value metrics until product finalized (see Step 10).
9. Experimentation: Establish culture of experimentation and constant iteration. Be willing to fail and pivot as needed.
10. Autonomy: Implement lite version of Holacracy. Start with the General Company Circle as a first step; then move onto governance meetings. Implement the GitHub technical and organizational model with radical openness, transparency and permission.
11. Social Technologies: Implement file sharing, cloud-based document management. Collaboration and activity streams both internally and within your community. Make a plan to test and implement telepresence, virtual worlds and emotional sensing

Step 10: Establish the Culture

According to noted hotelier Chip Conley, “Culture is what happens when the boss leaves.”

Establishing a corporate culture starts with learning how to effectively track, manage and reward performance.

Step 11: Ask Key Questions Periodically

• Who is your customer?
• Which customer problem are you solving?
• What is your solution and does it improve the status quo by at least 10x?
• How will you market the product or service?
• How are you selling the product or service?
• How do you turn customers into advocates using viral effects and Net Promoter Scores to drive down the marginal cost of demand?
• How will you scale your customer segment?
• How will you drive the marginal cost of supply towards zero?

“It takes a 9x improvement to move people from incumbent products to new products from startups.”

Step 12: Building and Maintaining a Platform

• Gather: The algorithmic process starts with harnessing data, which is gathered via sensors, people, or imported from public datasets.
• Organize: The next step is to organize the data. This is known as ETL (extract, transform and load).
• Apply: Once the data is accessible, algorithms such as machine or deep learning extract insights, identify trends and tune new algorithms.
• Expose: The final step is exposing the data in the form of an open platform.

CHAPTER SEVEN ExOs and Mid-Market Companies

It is possible to take an established mid-market company and supercharge it to exponential growth. Examples:

• TED
• GitHub
• Coyote Logistics
• Studio Roosegaarde
• GoPro

CHAPTER EIGHT ExOs for Large Organizations

“Companies may promote the idea of new business creation, [but] in the end they are all in the business of reducing risk and building to scale—which is, of course, the antithesis of entrepreneurship and new ventures.”

Disruptive new ideas never map onto the traditional organization chart, and mature companies, above all else, are all about org charts.

Few companies, however, are able to transform quickly. Apple and IBM are two rare examples of large companies that have successfully undertaken an extreme transformation and executed it fairly quickly.

Four such strategies for large organizations to deploy in an accelerating business world while still keeping their core operational businesses intact:

1. Transform leadership.
2. Partner with, invest in or acquire ExOs.
3. Disrupt[X].
4. Implement ExO Lite internally.

1. Transform Leadership

Four ways to transform the leadership layers of a big company:

1. Education
   • Singularity University, in partnership with X Prize and Deloitte, set up a four-day workshop called the Innovation Partners Program (IPP).
   • Every six months, eighty Fortune 500 C-Level executives receive two days of briefings on accelerating technologies, followed by two days of seminars introducing ExO-style organizational tools, including case studies, interviews and practice sessions on incentive prizes.
2. Board Management
   • Educate the board so that it is equipped to buy into the CEO’s plan for radical change. In addition, track your board using OKRs.
3. Implement Diversity
   • Sebastian Thrun, CEO of Udacity and a driving force behind the Google car, recently said, “When I’m hiring employees today, imagination is much more important than experience.”
   • Gender: Companies with all-male boards underperformed those of mixed-gender boards by an astounding 26 percent.
   • Recommendations: Break up bastions of old-line thinking and replace them with individuals and teams offering diversity in terms of experience and perspective.
   • Remember that one of the most important aspects of diversity requires putting young people into positions of power and influence. In addition, include more women on your board.
4. Skills and Leadership
   • Recommendations: Keep diversity in mind when appointing to governance and advisory boards.
   • Regularly take your senior leadership through a personal transformation program.
   • Examine your own leadership skill sets.
   • Remove anyone who puts his or her own career ahead of the success of the enterprise.

2. Partner with Accelerators, Incubators and Hackerspaces

• Amazon – Clearing the Rainforest of “No”:
• If you’re a manager at Amazon and a subordinate comes to you with a great idea, your default answer must be YES. If you want to say no, you are required to write a two-page thesis explaining why it’s a bad idea.
• In other words, Amazon has increased the friction entailed in saying no, resulting in more ideas being tested (and hence implemented) throughout the company

CHAPTER TEN The Exponential Executive

 

5 Likely Breakthrough Technologies:

 

1. Sensors and the Internet of Things

• We’ll see a leap from eight billion Internet-connected devices today to fifty billion by 2020.
• Anything and everything will have sensors embedded, from wearables and packages to even food.

Implications:

• Infinite computation (as Moore’s Law continues) and infinite storage, both essentially free; the Quantified Employee; AaaS (Analytics as a Service); hardware as the new software via developments such as Arduino; new business models based on connected products.

2. AI, data science and analytics

• Ubiquitous usage of Machine Learning and Deep Learning algorithms to process vast caches of information.

Implications:

• Algorithms driving more and more business decisions; AIs replacing a large percentage of knowledge workers; AIs looking for patterns in organizational data; algorithms embedded into products.

3. Virtual/augmented reality

• Avatar-quality VR available on desktop in 2-3 years. Oculus Rift, High Fidelity and Google Glass drive new applications.

Implications:

• Remote viewing; centrally located experts serving more areas; new practice areas; remote medicine.

4. Bitcoin and block chain

• Trustless, ultra-low-cost secure transactions enabled by distributed ledgers that log everything.

Implications:

• The blockchain becomes a trust engine; most third-party validation functions become automated (e.g., multi-signatory contracts, voting systems, audit practices). Micro-transactions and new payment systems become ubiquitous.

5. Neuro-feedback

• Use of feedback loops to bring the brain to a high level of precision. Implications: Capacity to test and deploy entirely new classes of applications (e.g., focus@will); group creativity apps; flow hacking; therapeutic aids, stress reduction and sleep improvement.

These new technologies will, in turn, underpin the appearance of five likely meta-trends:

5 Likely Meta-Trends:

 

1. Perfect knowledge:

Implications:

• With the Internet of (Every)thing, sensors, low Earth orbit (LEO) satellite systems and unlimited sensors, users will be able to know anything they want, anywhere and at any time.

2. Virtual worlds

Implications:

• Philip Rosedale notes that Hollywood special effects migrate to the desktop after five years.
• Avatar is now three years old and will soon be available on the Oculus Rift.
• Almost perfect VR is around the corner, and will deliver experiential reality and transform retail, travel, and living and working environments.

3. 3D printing

Implications:

• 3D printing (and soon 4D) will not radically change big manufacturing, but it will enable an entirely new class of products that will displace traditional manufacturing. A Kinko’s model of local 3D printing of virtually anything will appear shortly and the technology will have a major impact on warehousing and transportation. U.S. manufacturing will be revitalized as recent offshoring trends reverse.

4. Disruption of payment systems

Implications:

• In 2012, Visa and MasterCard credit card purchases totaled more than $1.5 trillion in the U.S. alone.
• Payment systems and money transfer mechanisms haven’t changed for decades, but with Square, PayPal and now Clinkle and Bitcoin, this domain is ready for a major transformation.
• One form will come via mobile/social wallets and seamless transactions.
• A second will come via micropayments (probably via the block chain).
• The ability to move infinitesimal transaction amounts will underpin entirely new business models.

5. Autonomous vehicles

Implications:

• In September 2014, California will issue the first license plates for driverless cars. Starting with delivery vehicles and then taxis, predictions call for existing road capacity to increase 8-10 times once a critical mass of AVs is reached.
• Ridesharing is an intermediate step toward fully automated transportation, which may have a bigger visible impact on society than anything else, including sustainability, urban planning (almost no parking lots) and fewer traffic fatalities.

Your Thoughts?

Have you read the book?

What was your favourite parts?

What do you think about the future of business?

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