Through the economic moat series, we've so far covered strong brands, then the network effect, followed by government regulatory barriers, and most recently economies of scale.

We're now down to just 2 moat factors left.

In today's article, we will go over one of the more prevalent moats in the emerging digital economy: HIGH SWITCHING COSTS.

Easy To Get In, Not So Easy To Get Out

High switching costs - also less flatteringly called customer lock-in - has been a "holy grail" of business for quite some time.

To have high switching costs, the product or service has to be foundational to a consumer's way of life, or critical to business process for a company. It has to fulfill a basic requirement that would need to be replaced in some shape or form by a competing product or service.

The criticality of this need creates risk to changing suppliers. Changing accounting software for a business would require evaluating a new package, then porting all existing data into the new software, then spending time auditing the transitioned data, developing new processes and training employees on the new system, and finally going "live" with it. That's a lot of time, effort, and risk, to say nothing of the possibility of future bugs or lack of support from the new vendor. Companies are going to be very deliberate about changing suppliers. It will have to take substantial advantages to consider a change.

High switching costs are really accentuated by a recurring revenue business model. It's great to sell a product that is essential to a business or consumer... but if you only sell it once, or infrequently, it creates clear decision points where the customer can consider and prepare for switching. With recurring revenue, the product or service becomes just a "way of life", with customers simply paying up and rarely considering whether to switch or not.

Where To Find High Switching Costs

Almost invariably, you find high switching costs in service-based companies - particularly business services.

Business customers are better lock-in candidates than consumers for several reasons. For one, they are larger, with numerous decision makers, all of whom are trying not to look bad or get fired for making a bad, high-profile decision. Secondly, they require more critical services to operate. All businesses need systems for paying employees, managing inventory, tracking costs and sales, marketing, and a whole lot more. Modifying any of these creates risk to ongoing business.

Nearly all business services have some switching costs - that's why it is such a great segment to look for investments. Even before the digital age, old economy firms like Automatic Data Processing (ADP) (with payroll processing) and Accenture (ACN) (previously Andersen Consulting, various business process outsourcing) built sticky, recurring revenue offerings that were key to their customer's operations.

Today, the software-as-a-service (SaaS) movement has turned all kinds of business software into recurring revenue service models. SaaS models have differing levels of "stickiness". The best ones are systems where companies enter critical data that is difficult to transition to a competitor. Less sticky would be software that does not manage proprietary data, or is used only by small, isolated segments of the business.

To illustrate this, let's take one SaaS firm we consider quite sticky - Atlassian (TEAM) - and another that does not have as high of switching costs: New Relic (NEWR).

Atlassian makes business software that manages user-created data. Its flagship product is JIRA, a software offering for managing and tracking product development "tickets", which can be new features, change requests, bug fixes, etc. It also offers Confluence, a system for creating and organizing online documents; and Bitbucket, which is used for source code management of software projects.

Take a look at those 3 primary products. ALL of them involve tools to create, organize, and/or manage immense amounts of user-created proprietary data. All of those tools are also used by a lot of employees, from line-of-business owners, to designers, to software developers and quality engineers, etc.

Consider now trying to replace Atlassian's tools. The effort and risk involved in moving gigabytes (or more) of user-created data can be daunting. Additionally, the breadth of use by Atlassian's tools creates even higher switching costs. Re-training possibly hundreds of employees, and suffering the months of lowered productivity and upended business processes from it is not something most firms are eager to do. Atlassian has some very high switching costs.

Compare this to New Relic. New Relic offers tools that monitor software applications and network infrastructure performance, providing business intelligence, alerting for potential issues, and highlighting potential bottlenecks.

This is a fast growing market, and indeed New Relic has some interesting characteristics as an investment. But, from a switching cost perspective, it is not as strong as Atlassian, for a few reasons. First, New Relic is a monitoring suite - it take real-time data and orchestrates it into usable reports. There is some use for old data from it, but the main use case is real-time monitoring. This makes switching to a competitor easier - there is no massive, user-created set of data that needs to be migrated in order to do so.

Secondly, New Relic is frequently used only by a limited number of employees, often dedicated "DevOps" teams responsible for troubleshooting and fixing issues. Switching monitoring software only requires re-training a small amount of people with specialized skills - much less daunting then changing tools used by several entire departments!

In short, it is important to understand how business tools and services are used to determine the level of switching costs. Items that are used by a wide array of employees across departments, solve absolutely critical business needs, and/or involve a lot of proprietary, user-created data have very high switching costs.

Let's wrap this section up by talking briefly about consumer-focused services. These are far less "sticky" than business services. Customers here are individuals or small families with no bureaucracy and less visible risk to making the wrong decision. Few companies provide services that are truly critical to the ongoing existence of personal life. While certainly there is some cost to moving from Apple Music (AAPL) to Spotify (SPOT), it isn't insurmountable. Some playlists may have to be re-created, and new user interfaces decoded, but that's about it. This is why you see Spotify trying to build out a proprietary library of podcasts - it creates unique, recurring content that helps keep customers on the platform.

In general, though, we don't find consumer services to be a great sector to find high switching costs, although there are some potential exceptions (financial services, for example, which are more disruptive to change).

The Future Of High Switching Costs

Historically, high switching costs have not been one of the more prevalent ways to build an economic moat. Brand building, network economics, and economies of scale were seen as the primary ways to gain a durable edge over the competition.

Switching costs really began to become a major moat factor with the rise of software in the 1980's, and have only become even more important since then. Microsoft (MSFT) spear-headed this movement by realizing the value in computing was the software, not the hardware, and has basically made Windows "the way to use computers" for decades. Other companies soon realized this and built similar, software based "default apps" in areas as diverse as image editing (Adobe's (ADBE) Photoshop) to CAD design (Autodesk (ADSK)). The SaaS movement simply took these switching costs and moved them to subscription pricing, which smooths out revenue and eliminates troublesome "decision points" in license renewals and software upgrades.

We're starting to see other industries look into "subscribe and stick" models. It has been highly successful for the gaming industry, which has gone from a hit-driven, boom-and-bust business model, to one of reliable, recurring revenues through online play and micro-transactions. For example, Grand Theft Auto V, a 7-year old game, is still Take Two's (TTWO) #1 revenue generator - and this is a company growing sales at over 20% a year! Activision (ATVI) (with Call of Duty and World of Warcraft), Electronic Arts (EA) (with FIFA and Madden), and even private Epic (with its omnipresent Fortnite game) - to say nothing of the Asian gaming giants - have all successfully embraced the model. Players make friends, become part of teams and clans, and generally build a digital social life in these games, making them very sticky and difficult to leave.

I'm interested to see where the "subscribe and stick" model goes next. Is Peloton's (PTON) online fitness community going to be as sticky as these game worlds? Maybe! Expect to see a lot of traditionally transactional business models move to this model going forward.