Why Is It So Much More Difficult For Healthcare Providers To Adopt Health IT Than Medtech?

Medicine has made great strides over the last 50 years. Modern medicine looks a lot different than the medicine of 1966. Today providers are 3d printing bones, replacing organs, and conducting minimally invasive surgery.

Yet healthcare operations of 2016 are remarkably similar to healthcare operations of 1966. Why haven’t the delivery systems of healthcare changed? Why haven’t core provider operations changed much in the last 50 years, and why do providers struggle to adopt health IT even though they’ve adopted so many medical innovations?

The Innovation Has Been In The Tech, Not The Process

In short, because it’s much easier to adopt new medical treatments than to adjust the operations of a healthcare delivery system. The former is an incremental improvement. The latter requires business model changes, changing job roles, and more.

The R&D burden for the vast majority of medical innovation is extremely high. Achieving FDA clearance is incredibly difficult and expensive: tens of millions of dollars, and in the case of pharmaceuticals, hundreds of millions.

But once a new pill, cream, device, test, or treatment has been invented, the healthcare system can “adopt” it pretty easily. All of the existing infrastructure is in place — pharmacies, labs, ORs, physicians, surgeons, etc. A few examples:

The only cost to healthcare providers to prescribe a new pill is educating the physicians. Physicians are mandated to earn Continuing Medical Education (CME) credits, and many are active in their respective specialty-specific communities. Pharmaceutical companies know this and market to physicians through these channels. Once a physician has learned about a new treatment and is convinced of its clinical benefit, her organization — a solo practice or hospital — doesn’t need to do anything else in order to prescribe the new medication to the patient. The physician prescribes the treatment, and the patient will receive a prescription and a nearby pharmacy will dispense the pills. This process happens identically if the treatment is brand new or if it’s penicillin. The medication prescription process is remarkably unchanged in the last 50 years. Even moving from paper to e-prescribing hasn’t really changed the workflow around prescriptions. The pharma company will work with medical distributors like McKesson to ensure the treatment makes its way to pharmacies in every geography. Providers don’t need to worry about where the pill came from or how it got there.

Similarly, the only cost to a healthcare organization to adopt a new piece of lab equipment is the cost of the equipment itself. A hospital already has an ASCP-certified lab (the ASCP certifies labs for quality and safety standards), lab technicians, etc. The only additional costs to the hospital of adopting a new medical diagnostic tool is the device itself, and few hours of training per lab technician. The hospital doesn’t need to build any new physical or virtual infrastructure, or define new processes. Once the new device has arrived, physicians are educated, and can then place orders that will utilize that machine. The process change required is minimal.

A significant majority of medical innovations are “black boxes.” Physicians don’t need to understand every chemical reaction that will occur in the body after a pill is taken. The pill is effectively magic — the patient consumes it and gets better. The same is true of the latest diagnostic tools. Put the blood in, get an answer out.

There are certain medical innovations that require some operational changes. For example, let’s examine robotic surgery. Surgical robots are a “black box” like other physical devices — surgeons don’t need to understand the control systems in the robot that guarantee millimeter precision. But surgeons and surgical staff need to be trained and certified to conduct robotic surgery. The training program for daVinci, the leading surgical robot, typically takes a few months to complete. However, surgical robots don’t change the operational processes around surgery. Patients are still referred to surgeons by more general physicians, surgeons still consult patients before surgery, patients still come to the hospital, staff still prep and sterilize the OR, the patient is still anesthetized, and the patient is still prescribed bedrest, antibiotics, and perhaps other medications afterwards. Although the technical implementation of surgery is vastly different, the broader process around surgery hasn’t really changed.

Health IT Requires Material Process Change

Health IT innovations couldn’t be more different than medical innovations. Health IT solutions by definition are not medicine. Health IT solutions do not directly impact the health of the patient at all, even if the patient logs in and uses an app. No It solution will magically make a patient better, and no IT solution will diagnose. Medical diagnostics and treatments require chemistry. IT is not chemistry.

It’s important to note that all health IT solutions require some level of organizational workflow change. The change may be relatively trivial, but a workflow change is required. Many of the greatest opportunities to improve outcomes and reduce cost to be gained from adopting health IT require massive organizational changes. Omada Health is a great example of a radically different diabetes management service. In fact, Omada’s technology and service is so unique that the company chose not to sell the software to existing providers, but to act as providers themselves and contract directly with self-insured employers, payors, and in some cases, at-risk providers. Omada determined that their clinical service would be more effective if they built it themselves, rather than helping hundreds of organizations modify their existing operations. Their success indicates that this was probably the right decision.

Information technology can do four fundamental things: collect, process, store, and share information. IT will never do anything more. When a provider organization adopts a novel health IT solution, there is an implicit acknowledgement that the organization was organized sub-optimally. When an organization adopts a novel piece of health IT software, the organization needs to rethink existing workflows and processes. Let’s use Patient IO as an example.

First, a quick primer on Patient IO. Patient IO is a cloud based care management platform that’s sold to large healthcare provider organizations. When hospitals discharge a patient after surgery, the discharge nurse typically provides the patient a few one-pagers that inform the patient on dietary restrictions, medication requirements, how to gradually get back into sports and athletics, etc. The patient is left to manage the entire post-discharge process herself. Using Patient IO, providers prescribe patients the app. The app sends regular reminders to patients using push notifications. For example, if the patient is supposed to walk .5 mile per day for the first week, then 1 mile a day for the 2nd week, the app will track activity on the user’s smartphone, and send the patient reminders throughout the day to increase activity. That data is reported back to the provider, and providers follow up with patients and their families as necessary to encourage activity. The same concept can be applied broadly for any care plan for any disease or procedure.

Adopting Patient IO is a big change for provider organizations. Previously, the organization may have staffed a few people to call patients and follow up after surgery. If the patient answered the phone, the caller may have asked a few questions about physical activity. The patient may have lied about the truth out of embarrassment. With Patient IO, nurses engage with dynamic dashboards based on hard data. These dashboards show compliance of patients based on time (eg all patients seen last week), by disease state (eg all diabetes patients), procedure (eg all patients who had knee replacement), and other factors that the nurse determines to be useful. The nurse then engages non-compliant patients with much greater rigor than the organization otherwise would have since the organization can devote energy and effort to help the patients most in need.

Patient IO is just an information arbitrage tool. Previously, healthcare organizations had no ability to track or understand this data. Now they do. As a result, it’s logical for them to rethink how they care for patients using this new tool. The tool itself does not make the patient better. Instead, the tool helps patients take better care of themselves, and helps providers engage with patients who are struggling with compliance.

Building Patient IO’s tech required 1/100th the financial resources that it took to develop a drug, but requires 1000x the organizational change. The same is true for most IT solutions. They are orders of magnitude more capitally efficient than traditional medtech, but require huge organizational changes to reap the benefits.

Over the last 50 years, providers haven’t developed the organizational capability to change their fundamental processes. They simply didn’t have a reason to. Although medicine was advancing rapidly, the advancement was literally contained to just the medicine. No one other than the vendor and the FDA really needed to understand the inner workings of the black boxes that were being invented. Healthcare delivery broadly remained unchanged until recently. Information technology is breaking old assumptions in healthcare delivery processes. This, coupled with the rapid succession of government mandates (meaningful use, ICD 10, managing lives at-risk, etc), has strained healthcare delivery systems. They are still learning how to adopt technology at the pace at which technology moves.

The future is incredibly exciting. As processes and medicine evolve together, we will be able to achieve results that were never before possible.

Why Are Tech Giants Investing in AR and VR?

All of the tech giants are investing at virtual reality (VR) and augmented reality (AR). For players like Apple, the target business model is obvious: sell high-end, polished consumer experiences at healthy margins. The same generally true of other hardware players such as Samsung and HTC. Sony and Microsoft are investing not to profit on hardware, but to profit on the ecosystem around the hardware.


But why are advertising companies like Facebook and Google investing in AR and VR? And how will direct response (Google’s dominant revenue stream) and brand advertising (Facebook’s dominant revenue stream) work in AR and VR?


Facebook and Google are investing in AR/VR as defense. The historical precedent is clear: Google bought Android as a defense mechanism to reduce the risk that Microsoft would dominate mobile. Although Android itself isn’t directly materially profitable to Google, Google leverages Android as a source of control over the technology ecosystem to ensure unfettered access to Google’s revenue engine: search.


Mark Zuckerberg has stated that he wishes that Facebook controlled a mobile OS. Why? Because he would prefer that the OS support social sharing through Facebook’s social networks as effortlessly as possible. Zuckerberg wants to create a social OS. This would make Facebook’s products even stickier, draw more engagement to Facebook properties, and ultimately generate more profit.


Given the power that Apple and Google exert over their respective mobile ecosystems, it’s natural that both advertising-based tech giants are investing heavily to control the AR and VR ecosystems of the future. What revenue opportunities do VR and AR offer Google and Facebook?


AR and VR present the greatest advertising canvases conceivable. AR and VR UXs will offer, on a per person basis, orders of magnitude more ad inventory that can be hyper targeted more precisely than ever before. That is the perfect combo for advertisers: scale, precision, and context.


OS makers dictate the rules of the game for their respective hardware form factors. The OS explicitly allows and disallows certain actions by 3rd party apps. Beyond supporting modal, foreground applications, iOS and Android define how apps can interact with the lock screen, home screen, notifications, hardware controls, and silicon components. Android is far more extensible than iOS, but even Android places explicit limits on developers. For example, 3rd party developers can’t replace the notification engine.


Mobile has eaten the world because smartphones have come to consume the white spaces in our lives: people turn to their phones to tweet, SnapChat, and check Instagram/Facebook while waiting at traffic lights and subway stations, at restaurants while waiting for a friend, and even in the bathroom. This has created an enormous opportunity to profit: attention is the world’s most valuable commodity. This is why Facebook has absolutely crushed it on mobile. Facebook controls a significant majority of attention for most users in a new advertising canvas (white space of people’s lives), and Facebook is selling access to that attention for enormous profit.

But mobile has, on a relative basis, hardly touched the active moments of our consumer lives: driving, eating, playing sports, watching movies, socializing with friends, etc. Yes, people play with their phones intermittently while doing all of the above, but one cannot read an actor’s bio and watch a movie at the exact same moment in time. Although Google Maps and Uber have transformed how all of us get around, none of us need to actually interact with our phones while we’re driving or Ubering (and in fact, we shouldn’t as a safety precaution). Audio cues are sufficient. No one uses their phone while playing sports.


AR and VR present an opportunity to layer in ads contextually into active parts of our lives. I’ll cover VR first, then AR.


Technically, VR is a modal activity. You can’t be doing something in VR and the physical world concurrently. But there will be virtual worlds that people can explore for hours on end with all kinds of virtual activities — games, Major League Drone Racing, virtual white boarding spaces, movies, porn, etc. These virtual environments will represent the ultimate advertising canvas for brand and direct response advertising.


For example, between drone races, Facebook/Google will present ads to buy similar drones and register for drone racing lessons. This represents the perfect combination of brand advertising — knowing who you are and creating purchase intent — with direct response advertising — efficiently finding and buying what you know you want.


Or while you’re drawing out the next UI in a VR whiteboarding space with a colleague who lives 500 miles away, you’ll see an ad for an app that helps you build better wireframes. The ad will show how you can literally drag and drop wireframe elements with your hands in virtual space, and interact intelligently with your whiteboard.


AR presents myriad awesome advertising opportunities. As you drive down the highway at 3PM, Google/Facebook will show you an ad to pull into McDonald’s in the next 15 seconds for a 15% discount on chicken salad. Google/Facebook know you haven’t eaten lunch today based on some health tracking, that you’re on a low-carb diet, and McDonald’s knows its slow time between lunch and dinner and will be glad to generate lower margin revenue during off-peak hours. AR is the perfect advertising medium for the physical world. AR presents the ultimate medium for gaming human psychology around scarcity. The opportunities for limited time offers are infinite!


Despite the huge opportunity mobile has presented, AR and VR represent advertising canvases that are orders of magnitude larger. The limitations that iOS and Android impose on 3rd party developers will be insignificant to advertisers relative the limitations that AR/VR OSes will impose on 3rd party apps and advertisers. There will no longer be a lock screen or home screen. Literally the entire world, virtual or physical, will be the “home screen.” The advertising opportunities are nearly infinite, and as such Facebook, Google, and the other tech giants are going to duke it out to dictate the rules of that experience.

The Deception of Positive and Negative Growth Percentages

Growth and decline percentages are deceiving in the startup universe. Many don’t recognize all of the implications of exponential growth and the associated hiring challenges. This problem manifests most commonly when a startup begins to achieve product/market fit and Initial Traction (~$1M ARR). 

When a startup is growing 10-15% m/m on the path from $500K - $1M ARR, the startup is adding $50-$100K in ARR each month, or $4-8K MRR. 10% m/m growth isn’t bad, but it’s not great. Great startups are growing > 15% m/m as they pass $1M ARR, and the Select Few are growing >25% m/m.

But what many fail to recognize is how the math scales. At $1M ARR, growing 15% m/m requires adding $150K in ARR, or $12.5K in MRR each month. Thus, from the time a startup achieves $1M ARR, they should hit $1.5M ARR in 3 months if they want to maintain 15% m/m growth.

At $1.5M ARR, 15% m/m growth means the startup needs to add $225K in MRR each month. So the startup should grow from $1.5M to $2M in just over 2 months, or 33% faster than the prior $500K in ARR.

This math isn’t particularly difficult to understand. But many underestimate just how hard it is to accelerate growth as the numbers get bigger. There are tons of startups that get to a point of adding $100K in ARR each month. 10x-ing that - adding $1M in ARR each month - requires real thought and and planning. Jason Cohen of WPEngine describes this problem very well. At a rate of adding $1M ARR each month, it will take 100 months, or more than 8 years, to achieve $100M ARR. Growth has to accelerate.

How does all of this tie to hiring? As startups add multiple customer acquisition channels, hire more than 2 sales people, and generally scale, startups need to invest in infrastructure. All kinds of it. This means marketing automation, sales automation, and customer success automation - collectively customer lifecycle systems and processes - to accelerate growth. There should be minimal innovation around these disciplines: innovate myopically. But startups need to hire the right people so that they don’t have to innovate in these disciplines. Tech/product focused founders rarely have expertise setting up customer lifecycle systems and processes. They should bring in the people who have implemented those processes before, and empower them to do it.

Those people are going to be more expensive than many founders naturally think. I remember the first time I looked at what an amazing VP Customer Success costs after raising a Series A. I couldn’t believe it: $150-$200K and .5%-1.5%. Great VP Sales can go much higher. But the great ones are worth their salary 10x over. Because they will make the startups’ customers happy in a way the founders otherwise never could, and those customers will fuel the best kind of growth: word-of-mouth (WOM). Not only does WOM scale incredibly well, it scales well inexpensively, driving down CAC and ensuring that startups don’t compromise the fundamental law of startup growth (fantastic post). That amazing VP Customer Success will drive down CAC and drive up LTV, ensuring the startup stays venture-fundable as it scales to $100M ARR. The amazing VPs are worth any amount of cash and equity to acquire.

The situation is particularly amplified for companies that are doing $1-2M ARR and are 4+ years old. If the product/market fit is tight and the market opportunity is real, then that means the startup needs serious customer acquisition help across all fronts. If there were any top notch marketing or sales people around, they probably left because they didn’t have the help around them they needed to drive revenue growth. And so now the company is left with B players without strong customer acquisition and customer success leadership. Those companies are the ones that most need to find a spark  to rethink the entire customer acquisition process and ignite growth. Those people will be expensive in cash and equity terms, but if they are any good, they will be worth their cost 100x over. As Jason Lemkin of SaaStr loves to say, salary and equity vest (and equity has a cliff), so the cost of being wrong is relatively low given the slow growth rate anyways.

Hiring becomes even more important when thinking about growth given the time cycles involved. Hiring great executives takes months, and onboarding takes 30-60 days, so founders need to have incredible foresight to time VP-level hires right to ensure they maintain an exponential growth curve. That means in many cases it will take 6 months to hire and onboard great VPs. So that means that startups should start looking for their first great VP hires between $500K - $1M ARR. If the startup is growing is 15% m/m and it takes 6 months to find and onboard the VP, then the startup will be at $1M-$2M ARR - or double the revenue of when the search started - before the VP is delivering material value. This is not intuitive to founders who, up until this point, have been able to tweak almost anything overnight other than the product fuel growth. It’s not naturally intuitive to think that a single thing - hiring an executive - will take 6 months. Exponential growth can be deceiving.

The flip side of thinking about growth - which is theoretically unlimited - is thinking about a fixed pie. And this is where percentages are really deceiving. When discussing negative percentages - revenue declines, accelerating burn, etc - it feels like the pie is being eaten… because it is. These are fixed pie scenarios. All of a sudden, 15% of the pie is gone. It feels like crap because psychology dictates that humans strongly prefer loss aversion to gains.

The problem that many entrepreneurs make is applying the same fixed-pie mindset and applying it to growth percentages and thinking about equity value. Positive and negative percentages need to be thought through opposing lenses: negative percentages should be thought of as a fixed pie that’s being eaten, while positive percentages need to be thought through the lens of infinite growth. Companies can become infinitely large - see Apple and Google - so the real dilemma isn’t how to minimize losses, but how to maximize growth. All decisions should be made through the lens of maximizing growth, even if material costs are incurred. Startups can always grow more than they can lose (unless gross margins are negative, in which case the business shouldn’t exist). Invest in that growth, even if it feels expensive through a fixed-pie lens. 6 months later, it will feel like a bargain when looking backwards through an infinite growth lens.

Should Your Startup Go Full Stack?

I’ve written about the problems associated with selling into value chains where there are disparate P&Ls. In this post, I’ll dive into the solution to this problem: going full stack. I’ll also cover when going full stack makes sense.

Chris Dixon of a16z has noted the rise of a number of high-profile, full stack startups across many industry verticals. What is a full stack startup? Full stack startups are those that, rather than selling a novel piece of technology to incumbents, use the technology they’ve built to serve the incumbent’s customers directly, bypassing the incumbent in the process. There are many of examples of modern full stack startups and their respective antitheses. A few examples:

Uber vs Hailo - Everyone knows that Uber bypassed taxis and instead when straight to the end consumer. On the other hand, Hailo responded to Uber by selling an Uber-like platform to local taxi companies. Hailo has struggled while Uber has run away with the market.

Buzzfeed vs ThoughtLeadr - BuzzFeed is changing the media business because their entire strategy is based on sourcing and producing content that’s designed to be easily consumed through the best discovery channels: social media. Everything they do stems from a deep understanding of how users share content. As a result of that, they have devised an incredible formula that seamlessly intertwines native advertising with socially shared digital content. ThoughtLeadr and many companies like it are trying to empower media organizations to rethink content strategy and distribution around native advertising and social sharing. BuzzFeed does the tech and content production in house. To be clear, I am close with the team at ThoughtLeadr, and I actually love what they’re doing. BuzzFeed can’t be the only media property on the planet. The world needs companies that can help old-school media properties thrive in the digital age. ThoughtLeadr is doing just that.

Oscar vs traditional healthcare insurers - Oscar recognized that health insurance should be completely rethought around smartphones. Smartphones enable new models where insurers consume vastly more consumer data (think movement, etc), and present a potent communication medium. Rather than trying to help traditional health insurers transform their entire businesses - customer acquisition, service, preventative care, etc - Oscar decided to build a brand new health insurance company that didn’t have any legacy baggage.

HealthSpot vs Teladoc - Teladoc owns and operates its own technology to enable virtual physician consults, whereas HealthSpot built/assembled technology and sold it to provider organizations. Healthspot recently ceased operations, while Teladoc recently IPO’d and is growing hand-over-fist as healthcare continues to consumerize.

One Medical Group (OMG) and Kaiser Permanente (KP) vs traditional healthcare providers - KP and OMG are two prominent examples of “full stack” healthcare providers. KP is enormous and has been around for a while and operates as an health plan and fully-featured provider organization. OMG is the leading pioneer of the Direct Primary Care model, which borrows many health-plan like features and functions. These organizations both invest heavily in their own technology development, and use that to offer differentiated healthcare services to their customers. KP and OMG stand in stark contrast to more traditional healthcare providers, who simply make money for doing stuff to patients.

I don’t mean for these examples to paint the picture that being full stack is always the right answer, and that being partial stack is the wrong answer. There are many successful companies that are explicitly not full stack: Workday, SalesForce, Slack, Zenefits, etc. These startups have been successful partial stack companies because they do not break the daily workflow of their users.

For example, let's look at SalesForce. Although sales professionals like to complain that SalesForce is clunky, slow and a not helpful in their daily workflow, SalesForce is just a tool that’s designed to reinforce a process that the sales people should have been adhering to in a paper world: contact and pipeline management. Zenefits users are still buying health insurance, and still filling out forms. The process itself really hasn’t changed; all Zenefits has done is unemploy health insurance brokers. Slack users are still designing, coding, etc; with Slack, they can collaborate with their colleagues more effectively. The same can be said of the other examples above.

On the other hand, tech companies should consider going full stack if they break the operational processes of the primary users of their solution. Uber could never sell into the taxi industry because Uber commoditized taxis, and taxi company owners didn’t want to subject themselves to that. Oscar could never sell its novel technology to traditional health insurers because it would have required rethinking every function in the insurance company. HealthSpot couldn’t usher traditional healthcare providers into a retail care delivery model.

Why can’t incumbents adopt technology solutions that completely break the daily workflow of their primary revenue-generating employees? In short, it’s too operationally disruptive. The organizations simply cannot absorb the change. When an employee’s daily workflow is completely rethought, the vast majority of her existing operational knowledge is not only worthless, but actually destructive in the new paradigm. Processes that made sense in the old paradigm no longer make sense in the new paradigm. Convincing thousands of employees and managers across disparate geographies and changing incentive structures to unlearn bad habits (to be fair, they were good habits in the old paradigm) is nearly impossible. In the case of Oscar, this is even more problematic as the changes would have spanned employees across every function in the company. Old and new paradigms simply cannot coexist in the same organization. Note: this is the fundamental problem that Clayton Christensen details in The Innovator's Dilemma.

As we see more verticals SaaS-ify, I suspect most startups will rightfully decide not to go full stack. For example, TalkDesk, ServiceMax, and Veeva rightfully didn't go full stack.  Although the new wave of vertical-SaaS vendors strive to be the all important system of record, they are generally seeking to re-inforce processes that should have already existed. In most cases, SaaS solutions are not radically changing the cost structure associated with delivering the services in question and are not re-inventing the business.

In summary, startups should go full stack if they are going to genuinely break the workflow of their target user. Otherwise, they should go partial stack.

PS, Given my background in electronic medical records (EMR), I'll add some commentary to that industry. EMRs break the daily workflow of the primary revenue generating employees of healthcare provider organizations. So why haven't EMR vendors gone full stack? Not a single traditional EMR vendor has even tried to offer healthcare services. There are a few reasons: during the golden era of EMRs, telemedicine wasn't reimbursable, so it wasn't practical to consolidate providers centrally given the intrinsically local nature of healthcare delivery. On the other hand, every novel tech-enabled healthcare service builds and manages its own technology in house: One Medical Group, Doctor on Demand, Teladoc, etc. The providers that are pioneering new delivery models recognize the importance of technology in their new models and are rightfully insourcing it to go full stack. This tech investment also serves as their barrier to entry and differentiator.

Online Dating Empowers Women

I'll preface this blog post by saying that this blog post is meant to highlight trends in America in the 2005-2015 era. This post isn't meant to be a 100% accurate, definitive truth about dating. There are millions of women who will say this doesn't apply to them, and that's right. I acknowledge this. Rather, this post is meant to articulate the changes online dating has brought to a significant percentage of women in America. Here we go:

Before the Internet became commonplace in America, American women generally met men in one of two ways: out at a bar, or through a referral. In the last few years, online dating has exploded on mobile devices and has become a major channel through which men and women connect. For the purposes of this blog post, I’ll outline some of the key differences between online dating, meeting women out at bars, and referrals that I’ve observed as a single male in my mid twenties living in Austin, TX.

Defenses - women generally have their defenses up when they’re out at bars at night. They know men are out to hit on them, that most men are trashy, and as a result, women explicitly choose to play “hard to get.” This is entirely rational behavior given the general male populace. Contrast this with online dating, in which there’s no need to have one’s defenses up. Women can choose who they want to speak to online, and block those whom they don’t. Although women can always end a conversation when out at a bar, it’s a lot harder to leave a physical, in-person conversation due to social pressure and logistical space constraints than to simply hit the “block” button on a mobile app.

Solo vs groups - as a man, it’s dramatically more difficult to approach a group of women rather than just one. This makes it very difficult to get one-on-one time with the woman I’m trying to speak with, simply because she’s with a group of friends. Women rarely go out alone. But online, all conversations happen in one-on-one settings. This enables men to speak to women who they otherwise wouldn’t have been able to, and conversely allows women to speak to men who they otherwise wouldn’t have spoken to.

Inversely, women act differently individually than they do in groups. When they’re out with friends, there is a certain level of group-think at play. The woman generally follows the wishes of the collective group, even if she would prefer not to. Similarly, women will speak differently with men when they know their friends are around than when friends aren’t around. A woman may choose to flirt less with a man because she knows her friends are around than if her friends weren’t.

Power to choose - women can choose who they want to have conversations with online. Although this is technically true out at bars, in practice women have little control over who they speak when they’re out. Through the course of a night, any number of men may approach a woman. Women are free to reject the men, but aren’t typically going up to speak to men. There are exceptions, but in general, women are waiting to be hit on. But online, services like Tinder and Bumble explicitly force women to opt into the conversation before the conversation even starts. This means women don’t waste their time with men who they don’t want to, and vice versa. Rejecting a group of men in person is substantially more difficult than it is to reject a single man online.

Similarly, online dating makes it much easier for women to proactively reach out to men that they’d like to speak to. Although women can always talk to a man out a bar, it’s much more difficult to approach a strange man at a bar than it is online. Moreover, since women aren’t expected to speak to strange men out at bars, women have less practice talking to strangers at bars than men do, compounding the problem further.

Online dating radically changes the dating process. Rather than going out and hoping to be hit on, women can very proactively manage the "top of the funnel" in their dating lives by leveraging technology. Women can manage this process discreetly, with no external pressure, motivations, or constraints. Specifically, online dating empowers women to: talk to more men, talk to more men that they would like to speak to, quickly filter out the men that they don’t want to speak to, speak to men without the social pressure that friends exert on them, and to reach out to men that they otherwise wouldn’t have. Although apps like Tinder have created a perception that online dating exists only to support "hook ups," this is patently false. There are many desirable characteristics of online dating, and that's exactly why men and women alike have adopted dating apps like Tinder so quickly.