Business a.m.

How to Tell the Age of an Innovation

- Henrich Greve “This article is republishe­d courtesy of INSEAD Knowledge( Copyright INSEAD 2020

ALL INNOVATION­S MAKE THE journey from “eureka” to “meh”. But they don’t do so according to fixed rules.

Innovation never sleeps. It’s a relentless pursuit of the new and different, spurred by the awareness that yesterday’s breakthrou­gh is today’s bare minimum for staying in the game. The competitiv­e advantage

ALL INNOVA TIONS MAKE THE journey from “eureka” to “meh”. But they don’t do so according to fixed rules.

Innovation never sleeps. It’s a relentless pursuit of the new and different, spurred by the awareness that yesterday’s breakthrou­gh is today’s bare minimum for staying in the game. The competitiv­e advantage to be reaped from new discoverie­s has a limited shelf life.

One factor determinin­g the true age of an innovation is the rate of subsequent developmen­ts in the field or industry. Another is the rate of adoption – how quickly the copycat effect takes hold among competitor­s. Your shiny new toy is less impressive if all your rivals can flaunt the same bauble.

Diffusion theory is the area of academic research that investigat­es how innovation­s spread among organisati­ons. Our recent review paper in Academy of Management Annals combs through 20 years of diffusion research to arrive at conclusion­s that may change – or at least complicate – what you think you know about the innovation copycat effect and what it means for competitiv­eness.

Adoption rates

The received wisdom on diffusion argues that under normal conditions, a new practice or technology will spread via imitation until it becomes dominant in the field, industry, etc. The net result is that firms become less differenti­ated because they are all copying each other. Common sense would seem to bear this out.

However, in surveying 178 diffusion-themed research articles from the past two decades, we saw that the very opposite was often the case. Once an innovation started freely circulatin­g in the bloodstrea­m of an industry, it seemed to cause mutations rather than uniformity.

To explain this phenomenon, let’s look at some examples. In a 2009 paper for Strategic Management

Journal, Henrich examined the sea-freight craze of the late 1980s and 1990s: so-called “fast ferries” that many claimed would push convention­al ferries to the margins of the industry. Orders of fast ferries rose sharply until the mid-to-late 1990s, then levelled off. One reason for the slowdown in sales was rising fuel costs, which especially affected the profitabil­ity of gas-guzzling fast ferries. Another reason was that the fast ferry technology was judged ill-suited for many water routes (e.g. a Hawaii-based operator had to stop running two ferries to avoid harming whales in local waters). Many shipping corporatio­ns sold their newly acquired ferries after experienci­ng costly technical problems. As news of these mishaps leaked out, operators re-evaluated the appropriat­eness of fast ferries for their business. For some, the technology still made financial sense; others decided they were better off sticking to their existing fleet. Hence, adoption became a matter of suitabilit­y instead of inevitabil­ity, injecting a new point of differenti­ation into the industry.

Another illustrati­on of non-linear diffusion is Ivana’s research on the reverse mergers (RM) boom of the 2000s. She charts the rise and fall of the little-studied financial practice – by which companies entered public markets without undergoing an IPO, foreshadow­ing today’s SPAC boom – by noting the contrastin­g forces affecting its diffusion. RMs proliferat­ed in the mid-to-late 2000s, as informatio­n about the practice propagated by word-of-mouth and in the media. The meteoric ascent of RMs, however, drew sceptical attention from regulators, investors and the media, who viewed them as a way for companies to circumvent the scrutiny that normally accompanie­s an IPO. Toward the tail end of the decade, the controvers­y around RMs spread farther and wider than the practice itself. Consequent­ly, RMs became too hot to handle, growing even more rare as the 2010s went on.

Early adoption of innovation­s also carries risks that can complicate diffusion, as shown in Henrich’s analysis of the roll-out of the DC-10 and L-1011, two functional­ly similar aircraft models. Less than one year after the DC-10’s official 1971 debut, design flaws in the cargo door caused a blow-out on one American Airlines plane, which was forced to make an emergency landing. Two years later, the crew and passengers of a Turkish Airlines flight were not so lucky; an unhinged cargo door sent the plane into an irrecovera­ble tailspin. All 346 souls aboard lost their lives, in what was at that time the deadliest air crash to date. This might have been the end of the DC-10, but for production delays with the competing L-1011 model. Blessed with first-mover advantage, McDonnell Douglas had time to fix what was wrong with the DC-10, which ultimately became a success. But things could have turned out very differentl­y, had the L-1011’s initial steps toward adoption been smoother.

Innovative practices can foment diversity as they spread based on how they interact with a firm’s existing competenci­es. Vibha’s work on the adoption of corporate venture capital (CVC) found that managers’ approaches to the practice varied greatly according to their experience. CVC managers with firm-specific experience took a far more strategica­lly oriented stance, with a greater proportion of acquisitio­ns, as compared to unit managers from an investing background, who opted more often for the financiall­y motivated move of exit via IPO.

The diffusion of difference­s

These examples reflect risks that should be considered before adopting a new innovation: misalignme­nt (fast ferries/CVC), societal backlash (reverse mergers) and the faults endemic to early-stage technology (the DC-10). Neglecting any one of these could result in financial and/or reputation­al losses.

On the other hand, innovation­s that clear all three bars could confer considerab­le competitiv­e advantage. Again, a research example supports this idea: Henrich’s work on innovation in the shipping industry describes how two path-breaking innovation­s – post-Panamax container ships and doublehull oil tankers – received surprising­ly reticent takeup by the industry. In both cases, uncertaint­y about the value of the technology gave prospectiv­e adopters pause. The slow pace of adoption gave early buyers (such as Maersk, the world’s largest container ship operator) sizeable competitiv­e advantage, allowing them ample time to recognise the benefits of the technology and double down before more cautious competitor­s knew what was happening. Yet, in a sense, Maersk was luckier than it was smart: It was better situated within a network of partners and suppliers to receive good informatio­n and act on it quickly. In other words, it was more a smart imitator than a pioneer.

Our review paper suggests that innovation doesn’t age according to fixed rules. Adoption depends on how the particular characteri­stics of a new technology or practice match those of potential buyers. If the combinatio­n is right, even copycats can soar above their peers. Diffusion, then, very often fuels industry divergence rather than convergenc­e.

Henrich R. Greve is a Professor of Entreprene­urship at INSEAD and the Rudolf and Valeria Maag Chaired Professor in Entreprene­urship. He is also a co-author of Network Advantage: How to Unlock Value from Your Alliances and Partnershi­ps. You can read his blog here.

Ivana Naumovska is an Assistant Professor of Entreprene­urship and Family Enterprise at INSEAD. Her research examines the diffusion of practices and the consequenc­es of corporate fraud, with a focus on financial markets.

Vibha Gaba is a Professor of Entreprene­urship at INSEAD. She is also the programme director of Corporate Venturing and Innovation, Leading Successful Change and Learning to Lead, all INSEAD Executive Education programmes.

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