Opportunity Theses

Some interesting opportunities for new businesses and business models are possible in the next few years. These opportunities are because of
(i) Increasing capabilities of new technology enablers
(ii) Second and third order effects of technologies and
(iii) Changing cultural, societal and demographic preferences or realities.

Here are some ‘opportunities theses’.

1. Trigger Events

Some events will catalyze the early arrival of future business models. For example, the 2008 recession resulted in the early arrival of AirBnB and Uber. The recession triggered the demand side to quickly adopt AirBnB and the supply side to quickly adopt Uber. Some trigger events on top of my mind are:
(i) Automation of Entry Level Intuitive Jobs that will shape new business models. Big Data, Machine Learning and AI together will cause a steep decrease in jobs that require pattern recognition. Radiologists, consultants, analysts, researchers, paralegals etc. will be less in number in the future. When entry level ‘intuitive’ jobs are automated, college education will become far more expensive to pay and won’t be as promising. This will catalyze new business models in education that will deliver education at far lesser cost and quickly retrain workers for new jobs. This will flatten organizations and change the nature of work. Consequently, businesses like recruitment, research, productivity etc. will have new business models. There will be demand for new and cheaper forms of insurance (job insurance?) and cheaper products. Loss of many middle class jobs will also create opportunities for tech-enabled collective bargaining and something like a Union 2.0.
(ii) Loss of faith in Stagnant, bloated and polarized Government will trigger new ways in which citizens will band together as communities and solve their problems faster. Peer-to-peer models of citizens connecting with each other and pooling in funding and skills to solve problems will become common.
(iii) Cultural shifts like a low savings nomadic lifestyle instead of focus on ownership and Demographic shifts like growing old age population in some countries will have significant impact on housing, healthcare, transportation etc.

Some Examples:



Omada Health uses software and very clever design to help users lose weight. More specifically, it wants to solve the seemingly impenetrable motivation problem that people have with losing weight. The bloated and unsustainable healthcare budget of the US is a trigger event that will push individuals and especially companies to embrace business models like that of Omada Health.



Neighbourly connects community projects and charities with people and businesses that want to help. When governments are more inactive, I suspect more peer-to-peer citizen and crowdfunding platforms designed to solve local issues without involving the Government will spring up.

2. Creators, Experimenters and Mass Collaboration

The cost, time and threshold ability to experiment and create have fallen dramatically. There is huge democratization of tools to experiment with new technologies like 3D Printing, Big Data or Machine Learning and they are delivered on Cloud. The population adequately knowledge to take advantage of these tools are increasing. China and India alone will have millions of experimenters. Blockchain will transform contracts, the patent system and trust in general giving real voice to the ‘small inventor’. Reputation might be a bigger incentive than money to experiment and create and share. New platforms will be mass collaboration among creators and experimenters. The way we innovate and do scientific research will change. News, Politics and Philanthropy will be transformed. For example, can tech enable everyone to be a ‘Philanthropist’ in some way? New platforms will influence winners in politics. Terrific startups and new business models will enable these.

Some Examples:

brigade    Wikipedia github-logoopen-ideog7fl9se1   foldit-picArimo3dp_sketchfab_logo

3. New Data Sources and Data Network Effects

New sources are becoming rich suppliers of data. Mobile, UAVs, Satellites etc. are some of them. Image processing, Machine Learning Algorithms and Cloud Computing are unleashing huge possibilities for new business models to turn aggregated big data into actionable information.  There will be new business models in consulting, investing, insurance, agriculture, public policy, mining real estate etc.

Some Examples:

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4. Rethinking from the ground up

Entrepreneurs will rethink current solutions from the ground up and new technology enablers will help them do that. How will kids learn best? A multi-aperture camera? Can social networks be used to improve mental health (a startup Koko is trying this)? Can software bring about behavior change? Can there be far less trial and error in drug research? Can the internet facilitate collective ownership of new businesses? Can we rethink food from the ground up (Hampton Creek and Impossible Foods)? Can the audience choose the course of a movie using VR? Are there easier and better ways to present one’s ideas than using a slide deck?

Some Examples:

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5. Enterprise Privilege to Individuals

A lot that has been the privilege of only Enterprises will be available to Individuals. I am talking about things as diverse and unrelated as supercomputing power, top quality cameras, security, top quality advice, tools for analysis, information, lobbying power, gourmet food etc. For example, can advice (say of McKinsey) that can be afforded only by Fortune 500 companies be available to Individuals? Can individuals afford to use machine learning tools in their hobbies and experiments?

Some Examples:


6. Removing Skill Barrier and Engineering Anxiety

More people will be able to focus on their job while removing moments of anxiety and uncertainty, some of it when it comes to complex engineering. For example, Cockroach Labs makes sure you don’t worry about data outages when building scalable applications. Ufora removes the trade-offs of data scientists between ease of use and scalability. Canva, a design application removes anxiety about lack of knowledge about design however a novice you are. Simscale lets you run complex engineering simulations in your browser.

Some Examples:

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7. Relentless Unbundling

Customers would be happy to pay far lower price for a piece of the bundle rather than whole. And companies focusing on a single piece sometimes might do better than a bundle since each piece may be disrupted technologically with a different business model. For example, lending, deposits, wealth management, payments, remittances, insurance etc. will be handled by different startups instead of the same bank. The trend is not new and has been happening for quite some time. But the results will be more pronounced when new technologies improve.

unbundling-banking-image-v2Source: CB Insights

8. Overhaul of High Non-Consumer – Low Scale – Expert Dependent Businesses

A special category of businesses that fulfill all of the following criteria are set for overhaul
(i) Very High number of non-consumers with current solution
(ii) The solution does not scale
(iii) Current solution employs ‘Experts’

Some common examples of the above can be Consulting, Law, Education, Investment Banking, Venture Capital, Hedge Funds etc. There will be far less need for experts and the solution is going to scale which will reduce the cost hence expanding the market bringing together many new consumers. All the aforementioned industries rely on intuition of experts. We will rely far less on the intuition of experts and machines will be able to precisely point the problem.

9. Donor Based Models

Expect many more businesses that rely on revenues from Donors. Wikipedia, KickStarter, DonorsChoose, Khan Academy are early forerunners. Milaap that enables micro-credit in India relies on donors. Neighbourly gets financing from citizens. New candidates in politics are able to break the barrier because of small donors. Theoretically, most businesses can be run with the help of donors. In the future, when people believe some platforms have too much power, they might opt for donor based models.

Some Examples:

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10. Images, Video and Visualization

More and more solutions will have their solutions that incorporate images and video.
(i) Machines will be able to make better sense of images and video in the future because of machine learning and recognize patterns within the trillions of images that are being captured every year. For example, patterns can be recognized from satellite images that will be used for consulting, investing or public policy. Images of farms captured by drones can be used to analyze soil and provide actionable insights. Medical images can be analyzed to identify and flag problems and abnormalities. Infrastructure will be built that can be used even by individuals and small startups. For example, Clarifai provides visual recognition APIs. Of course this will also produce many ethical challenges.
(ii) AR and VR will greatly enhance our capabilities to visualize (which I believe we are not good at). How will different sets of furniture look in our room? How would this shirt look on me? What is it like to be in a sub-Saharan country? How does this patient’s heart look like? Can you look through the eyes of a child living in war-torn Syria? Can you model and visualize the future of something with different variable inputs? Can you visualize the typical work day of a hospitality service professional and use it to train others? Can an online lecturer walk his students through realistic visualizations instead of PowerPoint slides? Can you click a photograph while walking on the street and see the names of different landmarks?

Incorporating images and videos, solutions across sectors are going to be impressive.

Some Examples:

Clarifai ModsyEmergent VR

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11. Orphan Jobs-to-be-done

There are some jobs-to-be-done with very bad solutions currently (analogous to orphan drugs). And some customer segments aren’t served adequately. Experimenters, extreme poor, those who don’t identify with the major political parties, talented people with zero college credentials, activists with less popular causes, communities with very niche interests, people with politically incorrect opinions etc. Technology will increasingly cater to these neglected or Orphan customer segments in the future and there is business opportunity in doing so.

These theses translate to opportunities in many different sectors and customer needs. We will soon be looking at many new startups that are going to take a shot at these opportunities and transform many different industries.

Some Examples:

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Jopwell  Walker and Company