How to Win at the Platform Game

Many business leaders are overlooking a way to grow their company and capture untapped value. Most of them understand the superior value of business models built around subscription-based software as a service (SaaS) and models built around marketplaces that join together many buyers and sellers. Few, however, understand the exponential growth and value that comes when both of those strategies are combined with data and machine learning models. As well, many leaders simply haven’t considered adding these strategies and models to their own business to create platform economics and growth — whether they’re running a startup, a midsize company, or a legacy organization.

But the opportunity to integrate these three strategic elements is becoming a critical business imperative. Companies today compete with one another for human capital (customers, partners, and employees) and financial capital (debt and equity investors). Growth stocks have outperformed value stocks since 2008, a reality that has accelerated during the pandemic. Investors are reallocating more of their capital to growth companies to align with a shift in consumer buying patterns (for example, from Regal Cinemas to Netflix). These facts reinforce the “grow or die” mindset — especially for companies that want to access the best talent, customers, suppliers, and investors.

Just as “beating the market” means focusing on growth stocks to investors, for companies it means allocating resources in ways that also drive growth and, therefore, superior performance. Some business models are better at this than others. Manufacturing and distribution are capital intensive, while financial and professional services are capital inefficient. SaaS and platforms, on the other hand, are capital light, with platforms even better by this measure than SaaS. Building a platform business model with (1) subscription revenues with a large user base, (2) a robust marketplace of sellers, and (3) machine learning models based on data has become the best business model for the modern world, offering the most capital-efficient model on the planet.

So how do you go from a bad business model that is capital inefficient to a spectacular one that is as light as air? You do it through this combined trilogy.

The Power of SaaS and Machine Learning

In his seminal 2005 book The World Is Flat, journalist Thomas L. Friedman clearly presented facts and figures showing that the world is increasingly connected and that every company competes with every other company for human and financial capital. In 2011, in the article “Why Software Is Eating the World,” technologist and venture capitalist Marc Andreessen spelled out why software is a superior business for disrupting the physical world and its related supply chains, noting that software is more scalable and efficient than all other industries and therefore generates better returns. And in 2018, in the article “Models Will Run the World,” hedge fund investors Steven A. Cohen and Matthew W. Granade laid out the lessons learned as investors and showed how, if software eats the world, machine learning models with data will run it.

I cite these three important pieces of writing because they help explain why the biggest and most valuable companies in the world today have mastered this new multisided growth model, with the goal of giving customers valuable connections to a plethora of suppliers and feeding them more of what they want, thanks to machine learning and data-driven recommendations.

In addition, putting these three components together creates a reinforcing loop that results in network effects that are scalable, extendable, and protectable. Software and subscription services power the on-ramp of customer buying (think Netflix, and search on Amazon), seller and partner marketplaces drive engagement (Shopify, Apple’s App Store, and Airbnb), and machine learning improves recommendation accuracy and outcomes (Match.com and Spotify) with data from interactions and transactions generating insights that feed every facet. Individually, each element can offer significant benefits. But the real breakthrough is in combining all three. (See “AI and Data Are the Fuel to SaaS and Platform Models.”)

Here are some examples. Catalant is a platform for gig workers who provide strategy, corporate finance, and operational leadership capabilities to midsize and large companies. Catalant has significant data that it uses to generate matching algorithms to create more effective outcomes for its clients. It also launched a subscription service in 2020 called the Catalant Platform to help companies leverage their own internal workforces and integrate them with Catalant’s 75,000 workers.

Anaconda is an open-source software community platform for 27 million Python data scientists. Data scientists on Anaconda’s platform create packages — libraries of programming code that can do specific tasks — that they and the companies they work for can use to create insights and recommendations. (Anaconda had seen 10 billion downloads of these packages as of spring 2021.) As a community of developers, Anaconda has data on each and every package, including who uses it where to accomplish what task. This creates an unassailable data moat as these learning libraries keep data scientists returning to learn the best ways to solve problems with Python.

Rockwell Automation is a large industrial organization that makes automation products and services for businesses and consumers. It employs about 23,000 people and has customers in 100 countries. It recently acquired Fiix, an AI-powered maintenance system that uses a SaaS platform to connect machines, mechanics, and information. This is a key acquisition for its vision of, as the company puts it, “bringing the Connected Enterprise to life across industrial enterprises.”

Three Steps to Get Started on ‘Beating the (Competition) Market’

Going from linear to exponential growth requires leaders to make hard decisions about their business model designs, including where to say yes and no to capital requests. Companies need to figure out how to take advantage of these three principles to accelerate the growth and value of their businesses. I recommend the following steps:

1. Implement subscription software. This is your company’s path to attract, engage, and manage your customer and partnership relationships to generate recurring revenues. Success is measured by the number of subscribers and the annual recurring revenue generated.

2. Create a large marketplace of sellers. A marketplace of sellers will accelerate your growth as your customers buy more of what is available — creating even more demand for more sellers. Consider including your competitors in the marketplace rather than just selling your own goods and services, so that buyers have choices. Think outside the box to get there. The fashion subscription platform Rent the Runway did so by pursuing various key strategies in parallel: The company created a subscription model that was unique in the industry and built a marketplace of individuals and designers who wanted to rent out their clothing rather than sell it.

Success is measured by the number of sellers and the gross merchandise value of goods and services sold on behalf of others in your marketplace, along with your company’s commission on those goods sold — aka your “take rate.”

3. Use machine learning and data generated from your SaaS on-ramp and marketplace. This data will offer insights at scale about both your customers and suppliers, showing their wants and needs. With this data, you can build the empathy necessary to ensure that you serve both audiences in the ways they want to be served. Success is measured by the amount of data generated, the number of machine learning models built, and the insights and recommendations generated from their combination.

Today, this three-legged stool is more essential than ever, given that every business is now competing for financial and human capital. At the very least, it’s critical that you have sufficient numbers of people in your organization working on software, marketplaces, data, and machine learning if you are intent on beating the market or at least keeping up with the best.