• Faculty & Research

    Knowledge creation on China, from proven China experts.

    386
  • Faculty & Research

    Knowledge creation on China, from proven China experts.

    386
  • Faculty & Research

    Knowledge creation on China, from proven China experts.

    386
Monday, June 7, 2021

Success stories are hard to replicate, successful mind-sets maybe not

By Bai Guo

‘Innovation’ is a buzzword which entrepreneurs and business professionals both love and hate. In any given industry, innovation is getting increasingly important and indispensable. Yet, when looking for innovative opportunities, we may get confused, lost, hesitant, troubled by uncertainties, and even struggle with anxiety.

Luck, it seems, plays a big role in innovative endeavours. Many respectable enterprises arguably did all the ‘right’ things – they hired good people, carefully researched the market, invested in R&D – yet still couldn’t escape the tragic fate of being defeated and replaced.

Is it true that innovation is essentially a game of pure luck? Is it even possible to capture innovative opportunities with a high potential for commercial success? If it is possible, then how?

The key to successful innovation

According to Professor Clayton Christensen of Harvard University, innovations are either ‘sustaining’ or ‘disruptive’.

Sustaining innovation, which many companies are good at, improves the functions of established products. When pursuing this path, failure is generally the result of inferior technology compared with competitors.

Stories of small groups of grassroots players taking on the incumbents are not unheard of, and some newcomers have even singlehandedly disrupted entire industries. Disruptive innovation is the biggest fear of established market leaders and the biggest dream of many innovators.

There are, however, some common misunderstandings about disruptive innovation. The first is that disruptive innovation is technologically more complex and harder to achieve. Upon being introduced to the two terms, it is tempting to assume that to ‘sustain’ is technologically easier than to ‘disrupt.’

Disruptive innovation is indeed no easy task, but that doesn’t mean it is technologically more advanced or complex. If it were, small players at the bottom of the market would not have the chance to turn the tables and cause disruption.

Take, for example, vehicle engines. Fuel supply systems used in petrol engines involve highly sophisticated technologies both in their design and manufacturing. Despite Chinese companies’ decades-long efforts, engines developed in China, either for automobiles or aircraft, are still technologically inferior to those developed by established foreign companies with century-long experience.

The rise of electric vehicles (EVs), however, has shaken up the automobile industry. Last year, the market valuation of Tesla grew by seven times, topping the combined market cap of the nine largest car companies, including Volkswagen, Honda, Hyundai, GM and others.

Thanks to the disruption caused by EVs, a new generation of Chinese cars – Nio, Lixiang, Xiaopeng and WM – have enjoyed a chance to thrive. Though currently nowhere near Tesla, they have at least earned a place in the race.

Another common misunderstanding is that disruptive innovation delivers products of higher performance. This is also not true. Disruptive innovations are not necessarily breakthrough technologies that make good products better. In their initial stages, they might even perform worse than existing solutions.

When digital cameras first appeared, compared with film cameras, their imaging technology was slower and recorded a smaller number of pixels. Likewise, when mobile phones started to offer photography functionality, their cameras were no match for digital cameras.

Being functionally inferior, however, didn’t stop digital imaging from taking over the photography industry, or mobile phones from cannibalising the digital camera market.

This example implied an important secret about disruptive innovation. Consider the chart below.

The vertical axis represents product performance, and the dotted line illustrates users’ needs regarding a particular function. To fulfill these needs, companies will invest resources in R&D to offer better products. This is the path of sustaining innovation.

Generally speaking, well-managed leading companies, with advantages and resources they have acquired as early movers, tend to lean towards sustaining innovation.

When the performance of the available product is lower than the users’ desired level (represented by the green zone), sustaining innovation can enhance the product performance and make it more competitive.

Once the offered performance exceeds the users’ needs, however, users will no longer be incentivised to pay extra money for additional improvements in performance. If another product happens to meet the essential needs of the users, that product will instead enjoy growth.

Digital cameras are exactly such a case. Though photos taken by digital cameras could not compete with that of film cameras, they could still satisfy users’ need to record memorable moments in their lives. More importantly, digital cameras allow users to take numerous photos at almost no additional cost, plus view the photos on a screen right after they are taken.

Only when a function identifies and meets an unsatisfied need can it trigger a strong inclination to buy. Successful innovations commonly offer better solutions to deliver the right results desired by users.

Whether an innovation can be successful, especially in a commercial sense, is dependent on its comparative advantage, rather than its absolute advantage.

How to identify comparative advantage

As has been said, the success of an innovative product lies in its comparative advantage. The big question is, how to identify that comparative advantage? The first thing is to stay observant. You have to monitor changes happening in industries directly related to your product. Strong expertise in a given field can lead to bias or arrogance against newer solutions or technologies.

For instance, when LED lights were first invented, they performed so badly that almost no one anticipated that they would replace incandescent bulbs in near future. Managers at Kodak, likewise, never imagined digital cameras would replace film cameras so rapidly, despite the irony that the inventor of the first digital camera, Steve Sasson, was – and still is – a Kodak employee.

You also need to look for connections between your product and industries that are not directly relevant. Whenever you notice a new change, trend or technology that is rapidly gaining traction within or far outside your own industry, do the mental exercise of envisioning possible synergy. A brilliant cross-over may thus be created. After all, any invention is, in essence, a re-assemble of existing elements.

Taking Steve Jobs’ creations as an example – be it the iPod, iPad, iPhone, or iWatch – all of them were based on existing technologies. Indeed, not everyone is capable of inventing a new product through R&D, yet innovation is more about the ability to re-imagine existing things.

Today, the internet has greatly facilitated the free flow of information. Data science and digital intelligence are used widely across industries, changing how we live and work, and how businesses are organised and managed. Opportunities for innovation are everywhere. What we need is the ability to identify, imagine, create and execute what may turn out to be a successful innovation.

Equally important is to re-evaluate how business is organised and managed. We need to look out for organisational hindrance of innovation.

Traditionally, businesses were organised and managed to improve the efficiency of existing tasks, which could easily kill the possibility of disruptive innovation. If key performance goals set for engineers, for example, focus on finding ways to print higher-fidelity photos at lower costs, or improving the sound quality of phone calls, engineers may miss the opportunity to explore how to view images without printing them, or how to watch movies on a mobile phone.

Similarly, traditional research usually puts customers into demographic groups and asks each group what functions they are looking for in certain products. But, the reality is that two 45-year-old men both with master’s degrees may live totally different lives. Their true wants and needs are often not captured by generic surveys.

Furthermore, you need to think like a customer. When seeking innovative opportunities, it is important to put aside the mind-sets of a business owner or manager, and see your business through the lens of your customers.

We often talk about giving customers what they want, but we habitually fall back into the old habit of running our businesses as managers. When we focus too much on what we can do and what we have been good at doing, our strength may become our obstacle.

While we are perfecting our leading products and services, we may fail to realise that what we are offering already exceeds what our customers are asking for.

For example, when a mobile phone company upgrades its camera from 2 million pixels to 12 million, customers might eagerly welcomed and paid for this improvement. But if the company continues to improve its camera from 12 million pixels to 100 million pixels, will such change still thrill the average customer?

Blindly pursuing the perfection of a mainstream function is not cost-effective, and can easily result in excessive competition.

Put yourself in the shoes of users

Today, we live in an era of excessiveness. What people want, but rarely find, is not perfectly functioning products, but social recognition, personal realisations, inner fulfilment, and the elimination of hassles and annoyances.

One common understanding suggests that innovation is driven by development either in technology or users’ demand. Personally, I believe innovators should always put themselves in the shoes of users.

I am not saying technology is not important. On the contrary, technological advancements are vital to unlocking new possibilities for innovations. Many ideas once unimaginable and demands once unattainable have been made possible by technologies. Technological progress has allowed us to do what was once beyond human capability.

If what can be achieved by human beings is represented by a circle, then technology has undoubtedly pushed the outside edge of the circle further away from the centre. Technological advancements, however, do not directly translate into applicable business plans.

If we focus too much on technology, we risk thinking like an engineer who is obsessed with his own technological creation and refuses to be honest with the market reality. What an engineer claims to have invented ‘for users’ might not be what the users truly want or need.

One example is Google Glass. It was an interesting idea, and the glasses did look cool. But if wearing the glasses meant a blink of the eye would allow you to record everything going on in front of you, including the slightest facial expression of the person next to you, who would ever want or dare to talk to you?

A commercially viable innovation should start with an accurate understanding of users’ needs. Or, more precisely put, innovation is about finding the unstated needs of users, then fulfilling that need by delivering what users want and incentivising purchases.

Market research can only tell us what users say they want, normally in the form of adjectives. What we should try to do is to explore and elicit the needs that customers have but do not know how to articulate yet.

Unstated needs are usually expressed through a series of actions and emotions triggered by particular scenarios. Identifying them calls for a few tactics. The first is to reconstruct the scenarios where the product is being used. Undoubtedly, scenario reconstructing is a useful skill.

Why do young people today like to order milk tea in the afternoon? They surely like the taste of the milk tea. What is more important, however, is their need for a little harmless distraction that can get them through the long, tiring working day.

To serve that inner desire, milk tea today is no longer just milk and tea, but full of toppings: ‘bubbles’ (chewy tapioca), egg pudding, coconut jelly, fluffy mochi and more. People drinking milk tea don’t want to finish their cup too quickly; instead, they want something they can slowly munch on. The calories from the drink are not what they are spending their money for, nor is the taste. They are looking for a little fun to pass the time.

As you get better at reconstructing the scenarios where your product is being used, you will be able to see products as services. They fulfill their mission and deliver desired experiences to users. Underserved needs are what drive innovation.

We also need to learn to use data spontaneously generated by users. Big data is constantly being talked about but rarely properly used. It is often processed in much the same way traditional data has been treated.

Traditionally, data was deliberately collected by companies through, for example, market research and surveys. As a result, data samples were limited in number and subject to sampling biases. In addition, surveys usually followed designed sets of questions and answers, which further limited the breadth of information one could extract from participants.

After data was collected, traditional statistical methods of data analysis were predominantly applied. Participants were grouped into demographic segments, and their opinions and answers were studied and calculated to paint a picture of what the majority of customers tended to like.

In today’s increasingly smarter and better-connected world, sources of data have greatly expanded, yet data analytics still largely follows traditional doctrines, just with larger data sets annotated with more detailed labels.

Traditional data analytics is still useful in decoding user behaviours, but not so useful in uncovering innovative opportunities associated with detected behaviours.

The data users spontaneously generate is a gold mine of unstated and thus unsatisfied needs. But, the data itself won’t tell you where the gold is, and you need to know how to look for the gold. By reconstructing the scenarios where products are being used, unsatisfied needs (and innovative ways to capture them) may surface.

In a word, the focus of data analysis should shift from summarising patterns using widespread behaviours to uncovering the reasons behind relatively rare, seemingly irregular behaviours (that users themselves cannot explain).

Identifying and capturing subtle signs, unravelling the often ignored hints, and translating such information into new product ideas – these are the merits that make a good innovator and are a core competence we need to cultivate.

Bai Guo is an Assistant Professor of Strategy at CEIBS. For more on her teaching and research interests, please visit her faculty profile here.

Add new comment