Industrial IQ: Where High Tech Meets Low Tech

Tech is breaking out of the Silicon Valley sandbox, transforming traditional, trillion-dollar industries in the process.

Nan Li |

The history of Silicon Valley, and what continues to define the technology sector zeitgeist today, can mostly be reduced to a simple tenet: digital solutions to digital problems.

Think servers, security, e-commerce, mobile apps, marketing software, adtech, and digital media. We are entering the 4th decade of tech startups rolling out the internet, making it simultaneously accessible and addictive while monetizing the usage. This tried-and-true playbook has been perfected as Silicon Valley has transformed from a field of apple orchards into a global economic force.

Despite the magnitude of this business success, these “digitally-native” categories ultimately represent a small slice of the economy, and an even smaller share of what matters in the world.

Change is afoot, and rapidly accelerating. Technologies that have historically been kept within the confines of Silicon Valley’s sandbox are now permeating every corner of the global economy. This has sparked a wide range of legacy industries to adopt technologies that have, until today, been concentrated in companies like Google. Data science, machine learning, robotics, distributed services, automation, and software-defined operations are just beginning to transform many more “traditional” industries like construction, logistics, manufacturing, agriculture, and pharmaceuticals.

This is what we call Industrial IQ.

As new hybrid startups emerge to explore these frontier-yet-familiar sectors, Silicon Valley is changing as well. Obvious has been investing in many of these startups over the years with the likes of Dexterity Robotics (machine learning-enabled, dexterous robots for warehouses), Recursion Pharmaceuticals (AI-powered drug discovery platform), Canvas (human-in-the-loop robotics applied to construction), Zymergen (computational platform for industrial chemicals), and XpertSea (machine vision, data science, and state-of-the-art sensors for aquaculture). Partnering with these companies from their early stages have given us a front row seat as they build transformative enterprises in massive, analog industries.

From this vantage point we are seeing a new playbook emerge, one that is customized for the high-tech meets low-tech world of Industrial IQ. The general shifts in this new playbook vs. the traditional Silicon Valley one are stark, with valuable insights for startups looking to spread technology to legacy sectors.

A New Playbook for Enterprise Sales

Older, more established industries operate much differently, and startups must discern these differences to succeed. Some represent additional challenges to building a company, while others are actually advantages if you play your cards right.

  1. Improved Access
    Starting off on a positive note: legacy industries are much easier to gain access to for a budding tech company. While the CIO, CSO or CTO of a large enterprise may be overwhelmed with the tech vendors and VCs vying for her attention, the buyers of Industrial IQ technologies aren’t often focused on technology purchasing full-time. It could be the Director of Operations at manufacturing facility, the VP of Supply Chain at a logistics company, or the Head of Biological Research for a pharmaceuticals firm. Nonetheless, these types of industry contacts are typically more willing to respond on LinkedIn or meet at a conference. The messaging that tech startups can pitch: you want to learn about their industry and/or offer them something in return—from a sneak preview of an unreleased product to a broader representation of tech industry innovation and optimism. This dynamic can be used to gain access for your startup, even if you have an incomplete product or are early on.
  2. Listen, Then Talk
    Once you are in the door, the next step is to listen. This may seem somewhat trite as one of the foundational laws of great sales is leading with customer awareness. However, I rarely see companies do enough information gathering in the early phases of client engagement. Instead, they hastily attempt to dazzle clients with product demos, or (worse), deliver monologues on why their technology is superior. First, buyers in traditional industries are often unfamiliar (read: unimpressed) with Silicon Valley and the tech industry as a whole—and sometimes may view too much technology as a negative. Immerse yourself in client challenges, and then talk about the product in the context of what it’s solving for. Second, if you treat the potential client as a thought-leader (which they are by talking to you!) and incorporate their feedback, you have the ability to create early client buy-in and a real champion internally. Joint development will give your early clients a deeper emotional connection vs. a traditional tech sale. Ideally, you can aim to cultivate a relationship-level dynamic, one that feels like you’re co-developing the future together.
  3. It Takes a Village
    As technology breaks fresh ground in these companies, more interdependencies and bottlenecks for new products are emerging than in traditional enterprise software. With an unpredictable purchasing decision process and disjointed stakeholders, legacy businesses need to be mapped out to know who needs to approve your technology before a sale. The day-to-day user of your product, the IT department, the finance department, the innovation team, and the CTO can all be involved before something actually goes through. Visualize the organization in your conversations, and ensure that everyone’s concerns are being addressed before going too far (only to realize there was a hidden deal-breaker elsewhere). There are also frequently issues with technical debt, legacy systems integration, and hands-on personnel training (maybe even in-person). Resist making assumptions, and get to a detailed view on how you can work with your client.
  4. Less Disruption, More Collaboration
    Because of the interconnectivity of the people and systems in Industrial IQ categories, collaboration is the key to any startup’s success. This will involve a radically different mindset than one that has been groomed by Silicon Valley. The tech industry is filled with battle cries focused on a “take no prisoners” style of rapid innovation: “Move Fast and Break Things”, “Fail Fast”, and an annual conference simply called “Disrupt”. By definition, disruption is a non-consensual term. I, the agile startup, will build something truly innovative and disrupt You, the industry incumbent. We all celebrate the heroics of a company like Netflix completely upending Blockbuster with a drastically different technology and business model. However, disruption can carry with it a hubris and elitism that doesn’t work well within complex, non-digital industries. In industries like pharmaceuticals and manufacturing, the stakes are simply too high to “break things”, and the incumbents are too complex to be “disrupted”. Remember that your client in these industries have centuries of domain expertise, armies of trained experts, billions of dollars of equipment, and real estate. Even if they may not be the most tech savvy or forward thinking, they are world class at what they do—and what they do is extremely hard. It is best to give them due respect for operating some of the most complex and important sectors in our economy, and partner with them to make sure technology can serve them, not circumvent them entirely.
  5. Timing Is Everything
    Finally, in the spirit of serving your client and not the other way around, make sure to recognize your client’s readiness for what you are building. There are few things in this world as unsatisfying as being right about an idea, but getting the timing wrong. The risk of misjudging market or client readiness adds a layer of complexity to an already difficult entrepreneurial journey. In Industrial IQ sectors, there is too much going on and the incumbents are simply too big for a startup to be able to enact change in technology adoption. You need to know what to look for and accurately map where you are in the client’s path towards adopting technology.

With timing specifically, I’ve simplified this into The Five Stages of Industry Readiness: a discrete series of steps industry incumbents often follow as they adopt new technology and work with startups.

Full Stack: If You Can’t Join ’Em, Beat ’Em

No matter how well you execute go-to-market for your Industrial IQ product, you may find difficulty in the market for a host of reasons. In those cases, an alternative path is to bring on additional industry expertise and build a full stack company. One of the companies I work with, Visor, is building software and machine learning tools to automate tax filing. The company realized that selling this software to small CPA firms across the country would be a nightmare, so they decided to hire their own CPAs and build an online alternative to H&R Block. Visor’s CPAs are inherently more efficient and effective because of the technology, but Visor delivers tax filing services directly to consumers. Another firm, Recursion Pharmaceuticals, is pioneering the use of artificial intelligence and automation in drug discovery. Instead of licensing the technology, Recursion is developing assets directly and has recently started to dose humans in a Phase 1 clinical trial on an internally developed trial drug. My partner 

Vishal Vasishth wrote about this phenomenon in the healthcare industry, with a rise of companies taking on patients directly instead of trying to sell into hospitals.

Not long ago it would have been inconceivable that a startup would compete in capital intensive businesses like building pharma companies or factories from scratch. However, startups can now compete in these established industries thanks to an increasing amount of venture capital and the emergence of investors backing companies making big investments for big gains. Now, startups in established fields can control their own destiny: instead of selling their software or innovation to clients in the field, they can build a tech-enabled company to compete directly with the incumbents.

It’s worth restating that Industrial IQ categories are hard to disrupt, and the full stack approach may be untenable for your target industry. Compliance issues, established workflows, and organizational politics may make it difficult for users in your industry to adopt your product or service. Calculate the friction between selling to an existing market against the barriers to entry to become a contender in that market directly. And if you do decide to go full stack, make sure you bring on the right set of capabilities that will help you navigate the industry.

Services: The Cousin of Full Stack

As a third alternative to selling directly or going full stack, tech startups can position their product in established industries as an outcomes-based services model. This means that a tech product is packaged in a way that is metrics-driven and mapped to an operating metric that already exists in the client’s P&L. Approaching customers with a services model creates pricing transparency and, ideally, can make an apples-to-apples comparison between a legacy process and one that a new technology vendor can fill.

For instance, a number of years ago I invested in an agriculture robotics company called Blue River Technology that automates weeding and crop management services in farms (it doesn’t get more high tech meets low tech than a sophisticated computer vision and robotics package being dragged through a field by a John Deere tractor). Blue River found that the best way for them to introduce robotics into their area of the agriculture industry was to map out the cost of the weeding that farmers already pay for (labor + chemicals), and make sure that they priced below that function. Their customers didn’t pay for robots, they paid for what they always paid for—their farm to be tended.

While it may be difficult to portray your product’s value to internal stakeholders or external customers, I recommend creating an “at-risk” revenue model based on the delivery of some end benefit. Using the at-risk model is an easier way to transition a tough product sale conversation into a much clearer and easier-to-define services engagement.

Industrial IQ & The New Economy

We’re entering a new phase of the global economy where every industry is becoming a tech industry.

Obvious suspects like robotics, AI, and machine vision are transforming manufacturing and supply chain processes to deliver improved efficiency with less waste. Behind the scenes, a stabilized and expanded internet is combining with innovations in mobile and wired infrastructure to bring digital services to traditionally “non-digital” sectors.

A new breed of tech companies are following a different, more empathy-driven playbook to break into these areas. We believe that this new wave of expansive technology will be a defining feature of the next chapter of Silicon Valley. If you are working on this, we’d love to talk to you.

Nan Li

Nan is an experienced investor focused on computational biology.

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