Innovator’s Dilemma on Steroids?

I find it helpful to break the question of disruption into three sub-questions:

1. What is the latent, or raw, potential of technological disruption?
2. What is the likelihood that this potential can be realized?
3. What is the probability that incumbents can prevail through the disruption?

1. What is the raw potential of disruption?

The first question, raw potential, should ultimately be quantified as much as possible, ideally into a dollar value.

For example, in banking, a traditional full-service bank can spend anywhere between $100 and $200 per customer account annually servicing its customers. A pure-play digital bank may be two orders of magnitude cheaper, at several dollars or even tens of cents per customer account annually.

A digital bank can also be more effective. The “3-1-0 principle” is often used as shorthand: a customer may apply for a loan in three minutes, receive a decision in one second, and receive the money in zero seconds. Few conventional banks can compete with that kind of experience.

In Clayton Christensen’s The Innovator’s Dilemma, disruptive innovations were cheaper but not initially better, and were therefore often ignored by incumbents. Over time, those disruptive innovations also became better. By the time the incumbent realized what had happened, it was often too late to catch up, especially if winning required a rapid build-out of new and stretching capabilities.

Some technology disruptions feel like The Innovator’s Dilemma on steroids. They have the potential to be 10 to 100 times cheaper and 10 to 100 times better. That kind of disruptive impact ought to blow everything out of the water if the latent potential can actually be realized.

2. Can the disruptive potential be realized?

The second question considers how difficult it is to realize the latent disruptive potential.

Here, there is typically an interplay of multiple factors: changes in consumer behavior that drive demand, regulatory constraints that shape what is possible, and supply constraints that may prevent an industry from servicing customer demand at scale.

Interestingly, the answer can vary widely by market.

Digital banks, for example, have taken off in many emerging markets where there is a large unbanked or underserved demographic and where regulatory regimes may be less strict or less mature. In developed markets, most people who want a bank account already have one, consumer inertia is relatively high, and regulations are well developed and strongly enforced.

The same technology can therefore have very different disruptive potential depending on the market context.

3. Can incumbents prevail?

The third question assesses the likelihood that disruption will upset the competitive dynamics within an industry.

In many industries, the position of incumbents is more stable than the rhetoric of disruption suggests. Technology disruptors may have limited impact on industry structure, even when the underlying technology is powerful.

Julian Birkinshaw’s HBR article, “How Incumbents Survive and Thrive,” argues that disruption is often less disruptive to incumbent players than commonly assumed. Healthcare, insurance, and banking are sectors where this appears to be true.

Insurtechs, for example, have generally struggled to establish a large-scale presence in the insurance industry. Incumbent insurance companies maintain a potent data advantage in pricing and underwriting that insurtechs are often unable to replicate. In some cases, this has driven challengers to financial ruin.

But just because new players are unable to usurp incumbents does not mean incumbents are safe.

In industries where the potential for technology impact is high but the odds are weighted toward existing players, the incumbents that harness the disruption will thrive. It is probably not a coincidence that leading players in insurance and banking, such as Ping An and JPMC, are also considered technology powerhouses.

What comes next?

There are, of course, sectors where incumbents are at grave risk.

Why did Nokia, Kodak, and Blockbuster lose their positions? What about retailers versus Amazon, or automotive OEMs versus Tesla and BYD? How can we better predict which technology disruptions will upend industry structure and competitive position? And what can incumbents do about it?

These are important questions that I will explore in future posts.

As ever, I welcome thoughts on these ideas, as well as suggestions for topics or examples to examine further.