Tag: EC Column

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4 ways generative AI makes founders more interesting to journalists

Craig Corbett Contributor
Craig Corbett is a partner at Publicize, a PR agency helping tech leaders and investors push their brands to the front and center of a rapidly evolving media landscape.

The advent of generative AI will lead to a tectonic shift in how startups do PR over the next few years. In July, the Associated Press became the first major news company to sign a deal with OpenAI, while media job cuts have reached record highs.

Gutted newsrooms could stymie one of the greatest engines of startup growth. While generative AI will enhance the capabilities of many publications, they’re also creeping onto news sites in ways we can’t foresee while journalists are laid off. Inevitably, some startups will choose to use AI to churn out thought leadership and PR content.

The problem with that is, if anyone and everyone can do something, then it becomes devoid of value. If any founder can ask ChatGPT to create a listicle on “5 reasons e-commerce will grow in 2023,” then the internet will become even more saturated with that kind of content. And that content is professional-sounding, yes, but impersonal, starved of real-life narratives, and flair-less.

Startups that want to be seen amid the flurry as AI enters the media will need to remember that what most people really want is a human story.

The good news is, this will actually push startup PR to evolve. In-house PR teams will want to elevate their content above the tedious noise. PR agencies will strive to show startups why they shouldn’t be using ChatGPT to do their job. Editors will scream out for original articles over rehashed content. PR and human-written thought leadership will have to sharply differentiate itself from the unoriginal content of overused AI.

Seeing a strong voice of reason or controversy, a provocative response to current events and rapidly unfolding topics — that’s something people are always hungry for. It’s alive, shaped by the world around us, and helps us make sense of it.

Ironically, AI could make PR more responsive, human, relevant. So, where do AI’s limits lie — and where will successful PR strategies shine in the age of ChatGPT?

Embed yourself in current (and future events)

AI does not exist in the present. It’s trained on past datasets, but it can’t follow today’s news, much less if that news hasn’t been published online.

I know from my PR work that journalists take a heightened interest in a business leader when they can speak knowledgeably (and quickly) on unfolding events. As do readers: 62% of professionals want to see thought leadership on current trends.

But how will generative AI change this scenario? It’s likely that the role of journalists will move away from what’s generally achievable by AI — generic advice articles, listicles, etc. — and they’ll have more time to write articles on current events and hard-hitting trends, imbued with relevant commentary.

So, that’s what they’ll want to see more of from founders — commentary on the Senate just passing a new immigration bill and how that will affect tech talent; a thought piece on how startups can leverage a new TikTok trend for growth.

An effective PR strategy will involve a shift in behavior:

  • Monitoring daily media for current events.
  • Inserting yourself and your company into breaking news.
  • Being a founder who can provide punchy opinions on select themes.
  • Assessing which topics you can speak to beyond your niche: for example, a fintech founder can seek to become an expert in emerging regulation.
  • Linking this kind of outreach back to your core mission and messaging.

Other than being timely, the difference between you and ChatGPT is that you have friends. You have your finger on the pulse of specific “offline” circles in a way that’s not possible for an AI bot. Journalists will value you being able to bring insights on the word on the street — what the sentiment is over X news story among your peers, the conversations you have with colleagues over the state of the industry.

Finally, you can also peer into the future. A true industry expert can read what’s happening on the ground — not just online — ask for peers’ opinion on a matter of interest, and offer predictions on where a trend is going. Be careful only to do so when your margin of error is small.

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3 reasons to maintain a follow-on allocation

Champ Suthipongchai Contributor
Champ Suthipongchai is a co-founder and general partner at Creative Ventures, a method-driven deep tech VC firm investing in startups that address the impact of increasing labor shortages, rising healthcare costs and the climate crisis.
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A venture fund maintaining some allocation for follow-on investments is not unheard of. But should VCs do this?

Follow-on investments won’t ever be the deciding factor in which funds win or lose, but they will continue to distinguish the top decile from the top quartile.

After all, if a company achieves wild success — the goal of any venture investment — then the initial investment will always do better than any follow investment.

So, as investors, why don’t we put everything into that first check to maximize the return? The answer to this requires an exploration of venture mechanics.

Follow-on investments increase the chances of follow-on investment

Follow-on investments are strategic and can often be the difference between a successful next financing round and your portfolio company going bust. They tell new investors that you have skin in the game and believe in your portfolio company, so they should too.

Imagine you’re a lead investor talking to downstream investors about the “best” company in your portfolio. You want them to lead the next round and suggest they do so, but when they ask if you’re joining the round, you tell them no.

Even if your reasoning is that you don’t reserve any capital for follow-on investments, you’re not sending a positive signal.

And what they do next . . . well, what do you think you would do in that position?

There is too much variability to be precise with the runway

Beyond optics, we find many idiosyncratic risks of venture capital. Besides a once-in-a-lifetime pandemic, you cannot always accurately predict things like FDA approval timelines or supply chain constraints, which means your portfolio company’s runway will likely be shorter than what is necessary to get to its next milestone.

Ultimately, there’s too much variability in how far a funding round will take a company, and even the best efforts to estimate runway are often wrong.

What’s more, even if a company reaches its milestone, a small coffin leaves little room to negotiate a good valuation, leaving earlier investors more diluted than they should be.

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Operational and finance tips for early-stage startups in a tough market

Ben Boissevain Contributor
Ben Boissevain is the founder of Ascento Capital, a boutique investment bank that provides advisory services for M&A, capital raises and valuations to technology companies in the U.S. and internationally.
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There is no question that this market is tough for tech startups. The market meltdown today can be compared to the dot-com meltdown in 2000 and the Great Recession meltdown in 2009. But even in tough markets, there are many survivors. This article explores survival tips for startups — for both operational and corporate finance. For the many companies that do survive, there will be an opportunity to grow faster since fewer competitors will fight for market share and corporate finance conditions will improve.

An excellent example of survival is Amazon, which was on the verge of bankruptcy in the dot-com meltdown in 2000. Amazon’s stock price plummeted from $106 to $10. Amazon survived by pivoting to selling internally developed technology to others — selling its e-commerce platform to other retailers through Amazon Services and selling its cloud computing technology through Amazon Web Services.

How tough is the market?

This market meltdown is tough on an historical basis:

  • Venture Capital (VC): Global VC funding in Q2 2023 fell to $65 billion, down 49% compared to Q2 2022.
  • Private Equity (PE): PE firms deployment is down a similar 49% in Q2 2023 from the quarterly peak reached in Q4 2021.
  • M&A: The M&A market for VC-backed startups in the U.S. is on its slowest pace since 2013, as the world’s economy was coming out of the Great Recession in 2009.
  • IPOs: 55 IPOs have been priced so far this year. The last time there were fewer IPOs was 2009 in the Great Recession.

Operational survival tips

For a company in survival mode, cash is king. Review a cash flow report, not a GAAP report, every day. Slow down paying vendors and require payment from customers in 30 or even 15 days. Focus sales efforts on quick wins that bring in cash, not elephants.

Cut expenses to the bone. Think Elon Musk sleeping on a couch. Review every line item. Consult with employees on areas to cut. Even small items like canceling subscriptions will change the corporate mindset from growth at all costs to a path to profitability.

Shifting the goals to a path to profitability fits with the new investor mantra, the Rule of 40 — if a company’s revenue growth rate is added to its profit margin, the total should exceed 40%.

One area to explore is using AI to perform tasks such as creating legal documents, generating key words for SEO, and writing software code. Almost 30% of new GitHub code is now written with AI assistance.

Unfortunately, terminating employees is sometimes necessary for a company’s survival. Be transparent with the employees, management, and the board. Consider furloughing employees and not terminating them to retain talent.

Finally, consider a hard pivot like Amazon in 2000. Listen to the market to determine where the demand is for a company. What other products or services can the company provide and what other market can the company serve?

Corporate finance options

If a company has a limited runway, pursue multiple corporate finance options simultaneously. Do not pursue the next VC round, run out of money, and then try to pursue M&A. The M&A process requires at least six months.

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Are your product and service teams creating value for customers?

Bryan House Contributor
Bryan House is the SVP of product and customer success at Elastic Path, where he leads the UX, product management, enablement and customer success teams.
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Those of us who have seen software transition from perpetual licenses to recurring revenue SaaS businesses know there’s been a fundamental shift in how revenue is earned over time. Recurring revenue businesses have to prove their value and win the customer’s trust every day. It’s no longer enough to rest on the laurels of a high-value contract term.

Still, some relics of the old world make their way into SaaS businesses, including the way service teams are incentivized. Certain legacy patterns of thinking need to make way for a more modern approach to value creation for the customer. In the old model, customization was key to unlocking services revenue.

Even today, service teams are incentivized to create custom work to drive revenue, too often at the expense of complexity with the objective of retaining the customer for the long-term.

Rather than maximizing services dollars per project, SaaS companies need to rethink the way they incentivize service teams and align them more closely with product teams. Let’s look at how this collaboration can maximize customer lifetime value (LTV) and result in more retention and expansion opportunities for recurring revenue businesses.

Engage for recurring impact

During customer onboarding, service teams typically consult with the customer on their jobs to be done, or most urgent problems to solve. As a result, you’ll usually see a service team create a scope of work (SOW) for customization as a gate around promised work versus future work to prevent scope creep. While this backstops potential downstream project risk, it ultimately misaligns incentives, putting the focus on short-term revenue capture (more and more customization) at the expense of long-term lifetime customer value.

SaaS companies need to rethink the way they incentivize service teams and align them more closely with product teams.

In this model, the customer becomes frustrated by the level of customization required to make a given product functional. Eventually, the software becomes too difficult to manage and the customer churns. In an alternate model, the service team’s goal is to leverage as much from product as possible and implement a defined scope at a predictable price, with a flexible time and materials budget for out-of-scope work.

In doing so, the services and product teams (preferably on the same team) are aligned on the company objective of improving overall net dollar retention. Or, as a recent Harvard Business Review article puts it, in subscription models, recurring revenue is the result of recurring impact, and services are a key driver of this recurring impact throughout the customer life cycle.

A new model for commerce services

One of the biggest business challenges in commerce is replatforming. It’s a painful inflection point where the market (read: vendors) has conditioned merchants to believe that ripping and replacing a legacy system is the only option. That’s often where service teams come in and create a host of upfront custom work, leading to a vicious cycle where commerce platforms become cumbersome and virtually unusable all over again. It’s time to break the cycle!

I often advocate for breaking down the larger challenge of replatforming into smaller component parts. It’s the fastest path to delivering value and contributes to customer LTV. Instead of a wholesale replatform, teams can start small by choosing a single product line or problem to be solved, and pairing it with services activities that allow the customer to maximize their value with an existing product.

In this scenario, it’s important to pair services alongside the product team with each step. Let’s take a common problem to be solved with e-commerce catalog management as an example. During customer onboarding, a catalog modeling exercise delivered by the service team can help merchants understand their product set and variation/configuration options (e.g., sizes/colors,

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Ask Sophie: Any tips for F-1 student visa approval amid the rising denial rate?

Sophie Alcorn Contributor
Sophie Alcorn is the founder of Alcorn Immigration Law in Silicon Valley and 2019 Global Law Experts Awards’ “Law Firm of the Year in California for Entrepreneur Immigration Services.” She connects people with the businesses and opportunities that expand their lives.
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Here’s another edition of “Ask Sophie,” the advice column that answers immigration-related questions about working at technology companies.

“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”

TechCrunch+ members receive access to weekly “Ask Sophie” columns; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.

Dear Sophie,

I was accepted into a prestigious robotics engineering master’s program in the U.S. that begins in the fall! However, I heard the denial rate for F-1 student visas is increasing. Why? 

How can I increase my chances of being approved?

— Soon-to-Be Student

Dear Soon-to-Be,

Thank you for studying in the States! The U.S. needs and appreciates international students like you. This visa adjudication change will cost billions to the U.S. economy, and it’s a step backward with tech job vacancies growing and the swift rise of several emerging technologies. The United States is in critical need of international students like yourself to support our security and economy to remain competitive throughout this century.

I’ve got lots of tips and strategies for you, but before I dive in, some good news: Earlier this week, the U.S. Citizenship and Immigration Services (USCIS) held an additional random selection round — or lottery — among the H-1B registrations that were submitted but not selected in the March lottery to meet the annual cap of 85,000 H-1B visas. The USCIS has notified the additional 77,609 registrations that were selected. (The USCIS selected 110,791 registrations in March.)

The second selection round could indicate that the number of cap-subject H-1B applications that the USCIS expected to receive by the June 30 deadline fell short of estimates, or, probably less likely, that the agency denied H-1B applications at a higher rate than expected. Decreased petitions would have likely stemmed from a combination of some continuing layoffs as well as the same candidates being entered into the lottery multiple times by separate companies, a change that the American Immigration Lawyers Association has proposed to DHS, which recently issued a brief response.

The F-1 is a great way to learn and grow in the United States. Studying in the U.S. and completing your degree also offers the opportunity to work in your field through F-1 OPT (optional practical training) and STEM OPT, the two-year extension of OPT. Last month, robotics engineering and seven other fields of study, including institutional research and composite materials technology, were added to the STEM Designated Degree Program List, now making you eligible for STEM OPT!

Now, about those declining F-1 approval rates — you’re correct: According to the Cato Institute, the denial rate for F-1 student visas jumped to an “unprecedented” 35% in 2022, compared to the 14% denial rate in all other nonimmigrant (temporary) visa categories, which include the H-1B specialty occupation visa and the O-1A extraordinary ability visa. Before 2021, F-1 student applications had a similar denial rate as other nonimmigrant visa applications. However, in 2021 and 2022, F-1 visas were denied at double the rate of all other nonimmigrant visas.

Students can apply for an F-1 visa only after they have been accepted into an approved university program, so “[t]his means that the U.S. Department of State turned down 220,676 students who would have likely paid roughly $30,000 per year or $6.6 billion per year in tuition and living expenses,” writes David Bier, the author of the Cato Institute report. “Over four years, that number rises to $26.4 billion in lost economic benefits to the United States.”

Let me dive into your questions, starting with the why.

Why is the F-1 denial rate increasing?

The State Department doesn’t specify the reasons for denying an F-1 visa. However, most consular officers deny nonimmigrant visas when you fail to prove in your visa interview that you have nonimmigrant intent, which means you only intend to remain in the U.S. temporarily and eventually plan to return to your home country.

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5 questions investors should be asking inception-stage generative AI founders

Navin Chaddha Contributor
Navin Chaddha is managing partner at Mayfield, the inception-stage venture capital firm behind Lyft, Poshmark, and HashiCorp.
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We believe that we are at the dawn of the generative AI era, similar to the prior PC, web, mobile and cloud eras, which represents a sea change in how consumers and businesses will interact with technology. However, building successful companies will require a specialized focus from investors — not just in providing capital but also in operational prowess that’s as unique and forward-thinking as the generative AI industry itself.

Last week, we announced the first dedicated seed vehicle in our history, the $250 million Mayfield AI Start, which will support founders starting at day zero.

As we meet with many AI-native founders, here are the top five pieces of company-building advice we’re sharing with them.

1. How do you plan to dominate this new tech stack layer?

Paradigm shifts propel the rebuilding of the technology stack, creating new enduring companies in every era. For instance, Oracle rose to prominence as the PC era enterprise software provider, but in the cloud era, Salesforce and the SaaS model became a viable alternative. Intel dominated as the chip king in the PC era but mobile customers preferred ARM (Advanced RISC Machine), which is now being displaced by RISC-V today.

As we meet with many AI-native founders, here are the top five pieces of company-building advice we’re sharing with them.

The AI era has already created leaders like Nvidia on the chip front and is giving rise to emerging leaders like open source AI model community Hugging Face (similar to GitHub in the cloud age) and foundational model platform OpenAI, whose ChatGPT is being compared to the Netscape browser moment of the web era.

So we are encouraging AI-first founders to think big about how they will become an independent company that dominates a layer of the new technology stack.

Image Credits: Mayfield Fund

2. Are you providing a painkiller or a vitamin?

AI-powered innovation, in particular with large language models and generative AI, has the opportunity to create new markets and shift the dynamics in existing markets. But it is important to identify what innovation bet a founder is making and frame it as a painkiller, not a vitamin for the specific persona they are targeting.

Some questions we are encouraging founders to ask include:

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How SaaS architecture impacts pricing and profitability

Ratnesh Singh Parihar Contributor
Ratnesh Singh Parihar is principal architect at Talentica Software who has expertise in architecture and design, scaling and handling large systems, solving complex engineering problems, and modernizing legacy applications.

Having worked as a solution architect and designed multiple SaaS applications, I believe many companies have struggled to choose the right SaaS architecture for their product offering. In this article, I will share my learnings to help companies that are building SaaS applications make a pragmatic decision about product architecture, while considering its impact on pricing and profits.

The pay-as-you-go pricing model has gained popularity because of the increased flexibility for customers. However, to enable pay-as-you-go, you need the right product architecture to support it, such as tracking the use of services and offering customers the flexibility of managing infrastructure as per their requirements.

A poorly designed SaaS architecture creates limitations in setting the pricing strategy for the offerings and impacts new customer acquisition. Conversely, a good architecture sets the appropriate pricing model and accommodates special architecture-design requirements, while enabling scalability and customizability.

Before setting up a SaaS architecture, it’s important to answer these questions first:

  • How would the customers pay?
  • For what services (computation and values) would the customers pay?
  • How will the usage be measured and invoices be created for the customers?

In a SaaS setup, costs incurred in managing operations impact profitability to a large extent. Operational expense optimization involved in managing the SaaS model depends on three crucial factors — infrastructure cost, IT administration cost, and licensing cost.

Image Credits: Talentica Software

However, the bigger question is: How do you ensure that these costs are well-optimized and priced correctly? Here are a few examples:

Salesforce Online: Salesforce provides a lead management system for enterprise sales and marketing teams. The online version uses the cloud to reduce the hassles of hardware and IT procurement. It also charges customers based on the size of sales and marketing teams to stop the payment of one-time high license costs.

Azure SQL: As the RDBMS (relational database management system) leader, the SQL server provides a hosted solution where customers pay a high license cost and hire a DBA (database administrator) for regulating backup, geographical replication, and disaster recovery. But Azure SQL is a cloud-based system that is accessible online and you pay only for storage and IOPS (input/output operations), with the rest taken care of by Azure.

WordPress: WordPress provides an online platform with white-labeled solutions, customization, and multiple integrations for its customers. Moreover, it collects customer usage data and charges on that bases.

Why is it important to pick the right SaaS type?

This is a common question. Let me explain why with two different examples.

Example 1

A company introduces isolated application VMs (virtual machines) for all its customers. In the majority of cases, these boxes will remain underutilized. If customers pay only for utilization, the company could end up with huge losses.

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Strengthening security in a multi-SaaS cloud environment

Steven Tamm Contributor
Steven Tamm is a technology adviser to Spin.AI and a former Salesforce CTO with extensive experience in cloud computing, e-commerce, virtualization, developer tools, cybersecurity, compliance and SaaS.

Managing security across multiple SaaS cloud deployments is becoming more challenging as the number of zero-day and ransomware attacks continues to rise. In fact, recent research reveals that a staggering 76% of organizations fell victim to a ransomware attack in the past year.

It’s no secret that protecting data is hard, and with the rise of cloud technologies, it’s becoming harder. But when it comes to cloud SaaS application risk, what does that look like? And what actionable steps can teams and IT pros take to help mitigate those risks at their organization? In this article, I’m going to explore those questions and provide some insights.

Navigating the maze of SaaS challenges

Modern organizations encounter a variety of SaaS challenges, including the absence of configuration standards, multiple APIs, and user interfaces (UIs) with varying access levels and potential data leaks across interconnected systems. Securing structured data in CRM applications, communication data in messaging platforms, and unstructured data from file providers is already difficult.

However, when these systems are sourced from different vendors, it becomes even more challenging to detect and prevent attacks in a timely manner. The interconnected nature of these systems makes tracking data provenance difficult and facilitates broad spread of malware and ransomware.

This challenge is further exacerbated when organizations extend their systems to include external users. With expanding footprints, the inadvertent leakage or destruction of sensitive data becomes a significant concern. Popular platforms like Salesforce Communities, Slack Connect, Microsoft Teams, Microsoft 365, and Google Drive create a complex web of identity, permissions, and integration controls.

Unfortunately, most endpoint management tools on the market were designed for a pre-cloud, pre-bring-your-own-device (BYOD) era, making them inadequate for managing the modern SaaS landscape. So how do you take control?

Taking control with new solutions

When managing risk in the cloud, it’s crucial to select IT and security solutions that truly address the intricacies of the deployed SaaS applications and were born 100% in the cloud without any legacy on-premises components. The good news is that vendors are developing innovative solutions to help IT and security teams do this. But it’s essential to explore the options and consider the following:

First, do they go beyond basic factors such as OAuth scopes, login IP addresses, and high-level scores, and instead delve deeper into data usage patterns and even examine the code of all integrations?

Second, many major SaaS vendors provide event monitoring, antivirus protection, and basic data leak prevention as check boxes. But these features often fall short when it comes to preventing and remediating data attacks because of miscalibrated thresholds in alert systems and logs that are not tuned for specific organizations. That results in alert overload and fatigue. It’s important to understand how a solution improves risk scoring and alert prioritization.

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Cyber insurance audit: Painful necessity, or a valuable opportunity?

Ilia Sotnikov Contributor
Ilia Sotnikov is a security strategist and VP of user experience at Netwrix.

Not that long ago, few companies even considered purchasing insurance to mitigate their financial exposure from a cyber incident, and for those that did, obtaining a policy was as easy as filling out an application and writing a check. Those days are now squarely in the rearview mirror. Today, companies everywhere are rushing to get cyber insurance — the value of the global cyber insurance market reached $13.33 billion in 2022 and is projected to soar to $84.62 billion by 2030.

However, the increased number of policies combined with the sharp uptick in costly attacks led to higher costs for cybersecurity insurance providers. To stem their losses, insurance companies now often require proof that an organization has implemented a variety of security measures in order to be eligible to purchase a policy.

Rather than resisting or resenting risk assessments from potential cyber insurance vendors, IT leaders should regard them as an opportunity to strengthen their organization’s security posture.

Cyber insurance involves risk assessment

Across the insurance industry, policy requirements and premiums vary according to risk assessment. For instance, installing an anti-theft system might reduce the cost of insuring an expensive sports car. A person living in a flood plain can expect to pay more for a homeowner’s policy than someone with a similar house on higher ground — or they might not be able to purchase a policy at all, as homeowners in states like Florida are discovering.

It is the same for cyber insurance. An insurance provider may impose more security demands on a company that hosts large volumes of personally identifiable information (PII) than it does for a company of similar size with far less PII. And organizations that lack sufficient security controls to bring risk down to a level acceptable to an insurance provider might not be eligible for any policy at any price.

What cyber insurance actually covers

The main focus of cyber insurance is obviously on covering the financial risks of an incident. Typically, you can expect the insurance to cover the firsthand costs to the business that are the direct result of the cyber event, such as:

  • Forensic analysis and incident response. Some insurers require that you engage specific managed incident response services.
  • Recovery of data and systems caused by actual loss and destruction.
  • Cost of the downtime due to the cyber event.
  • Costs incurred from sensitive data breaches, such as handling PR activities, notifying impacted clients, or even providing credit monitoring services to customers.
  • Legal services and certain types of liability for regulated data, including covering the costs of the civil lawsuits.

It is important to note that insurance rarely or never covers some of the longer-lasting impacts of the event, such as any future profit loss due to theft of intellectual property or the need to invest in cybersecurity program improvements after the event.

There is no consensus on reimbursement for paying a ransom. Not all insurers cover this type of expense. Some experts argue that it can encourage further attacks and fund criminal activities. In some jurisdictions, the discussion is going back and forth on whether paying ransom should be banned altogether.

As with any insurance policy, you can expect extra clauses. These may include the top amount they cover, the requirement to go through a due process with the law enforcement agencies, or involvement in professional ransom-negotiation services.

The must-have security measures for cyber insurance

A recent Netwrix study reveals useful details about the process of qualifying for cyber insurance today. It found that 50% of organizations with cyber insurance implemented additional security measures either to meet the requirements of the policy they selected or to simply be eligible for a policy at all. The figure below shows the specific requirements they reported having to meet:

Image Credits: Netwrix/Netwrix Hybrid Trends Security Report 2023

Don’t take this list as comprehensive or authoritative. For instance, implementing MFA does not necessarily mean requiring MFA for all users; an insurer might require additional authentication only for users with privileged access to sensitive data and systems. In addition, remember that these controls are interrelated. For example, in order to require MFA for access to particular types of data, you need to know where sensitive and regulated data resides and have control over user and administrative privileges.

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Clinical pathways are the currency of health tech

Jeff Diamond Contributor
Jeff Diamond is a senior associate at Fika Ventures.
Aaron Szekel Contributor
Aaron Szekel is a venture partner at Fika Ventures.

As healthcare becomes more entrenched in the digital revolution, the need for an approved set of protocols for care delivery — clinical pathways — is becoming increasingly critical.

Clinical pathways, as defined by the Children’s Hospital of Philadelphia, are the “standardization of care that translates guidelines and/or evidence into localized infrastructure and processes.” These processes have significant financial implications, as they can decrease payer (insurance) denials, allow providers to enroll in performance-based reimbursement, or help resource-constrained provider systems better allocate financial resources.

These financial benefits, coupled with current macroeconomic forces — the struggle for profitability in hospital systems, the rise of team-based care (via non-physicians), the challenges of utilization management at scale for insurance companies, and strict legislation around patient communication and healthcare systems interoperability requirements — have paved the way for pathways to become the de facto operating system for healthcare.

Pathways provide a currency for patients, providers, payers, and technology companies to prove a return on investment (ROI), both clinically and financially. Ultimately, this has created a unique opportunity for emerging and legacy healthcare companies to build around pathways, leveraging new datasets, delivering novel reimbursement models, preparing for and complying with new transparency and interoperability legislation, and utilizing advanced AI to provide personalized understanding and delivery of information.

Data is the driver of pathway’s success in clinical and operational settings

In the past, national guidelines dictated decisions made all the way down to the local level. Now, local, and even personalized, evidence-based pathways are driving decisions, thanks to the ability to access, create, and analyze new datasets.

Access to data, standardization of data rights, and the utilization of HIPAA-compliant collaboration tools, such as Datavant, will continue to improve compliance and create a more democratized, fine-tuned system of analysis for personalized pathways. The Centers for Medicare & Medicaid Services (CMS), under advisement from several healthcare companies, is now implementing an approved format for hospital charges as single machine readable files (MRFs), which will be leveraged to standardize all charge information.

With the ability to access, create and analyze new datasets, personalized, evidence-based pathways are driving more healthcare decisions.

This will allow both large (national) and small (local) providers to access previously unavailable data that can then be used to enhance care coordination and delivery, promote quality improvement, advance research, and increase ROI.

We spoke with Eric Leroux and Dan Imler, emergency department MDs and the co-founders of clinical pathways startup Curbside, about the ability to utilize new data models in the transition from the national to the local level for clinical logic creation. They pointed out that while nationalized datasets have a role to play in insight generation, “the clinical and financial responsibility of point-of-care decision making is still inherently local . . . decisions must be governed there to have any real impact,” especially in value-based care constructs.

As more companies like Curbside and AvoMD work to bridge the gap between art (no guidelines) and science (NCCN guidelines) when creating pathways, we expect more investment in startups that focus on the intersection of digital health and fintech as evidenced-based pathways and localized reimbursement engines become more necessary.

Reimbursement models

Pathways have evolved as a “cornerstone of future reimbursement methodologies and quality efforts,” as described by Dr. Robin Zon in ASCO Connection. They can help providers avoid “time-consuming prior authorization and appeals with payers,” and capture “stage and molecular data for a more refined risk adjustment.” Today, clinical pathways can be used for reimbursement via a number of models, from value-based care (VBC) to legacy fee-for-service (FFS).

For example, CMS uses clinical pathways to create a benchmark for cost and quality in the Medicare Shared Savings Program (MSSP). Providers who can provide care at a lower cost than the benchmark and who can meet certain quality standards are eligible for shared savings.