The most overlooked digital transformation challenge for managers is not so much digitalisation itself, but its secondary effects.
Of course, digitalisation proposes a host of opportunities, and managing them is not easy. How to use cloud, big data analysis, AI, predictive maintenance, industry 4.0 etc. are big challenges for themselves. Even things like creating a unique platform where the customer can access all your offerings online is sometimes quite difficult.
But once you look at what secondary effects emerge because of these changes in your organisation and its environment, you realise that the foundations of almost everything you know are profoundly shaken.
It has mainly to do with two aspects of digitalisation: Moore’s law and net neutrality. In this article, I am going to explore implication of Moore’s law. Click here for the second part.
The first source of change: Moore’s law
Moore’s law is not so much a law, but the statement that every 18 months, the capacity of a microprocessor doubles, and its price is cut in half. This has been true from the 1960 to this day. It simply implies an enormous speed of exponential innovation. If the same speed of innovation were applied to air travel from 1970 to today, a flight from Paris to New York would cost less than a penny and last less than a second.
So just by coincidence, everything connected to digital technology sits on the back of an exponential accelerator of innovation.
What are the implications of Moore’s law?
Exponential growth – outside in
Curt Carlson, at the time CEO of SRI international, the most productive developer of the foundational technologies of Silicon Valley, has famously stated:
In exponential times, if you improve your performance incrementally, you fall behind exponentially.
If you focus on the history of your own organisation, and compare its present state to where you’ve come from, a continuous past of incremental improvement will make you proud. Every year you’re better than before! Only – the speed of improvement around you is faster, and if you miss the early signals, or miss the capacity to accelerate with it, you’re gone before you know what hit you. It also means that the legacy (old contracts, old technology) of established players is not as big an advantage as it may seem. Sometimes, this not only applies to companies, but to whole industries.
The speed of commodity
The speed of innovation also means that novelties become common very fast. This relates to hardware and software. Take for example space technology. In classical space technology, there is the paradoxical saying “Only use in space what has been proven in space.” This makes sense, since it is tremendously expensive, or impossible to fix things in space. So you won’t risk a billion-dollar satellite by using technology of which you don’t know yet whether it works in space. The consequence is that satellites run on very old technology. Meteosat (2nd generation), has taken 20 years of development, there are currently 4 in orbit, and they cost 1 Bn € each. The capacity of their in-board camera is to cover 1 square km with 1 pixel – that was what the technology was capable of 30 years ago.
By comparison, the start-up Planet Labs has built a satellite for a similar task: take 1 picture of all the Earth’s surface per day. Their “Doves” (you can see one in the picture above) were built on a completely different combination of technology, price, and quantity. They use gyroscope and cameras from current smartphones – cheap, modern, but not tested in space. Since they cost less than 200 000 € (estimate), it was possible to send 149 into orbit – one batch at the time. Price and quantity were the condition to include one or two experiments with each batch – if some of them break down, it’s not the end of the mission. Relying on existing, commoditized technology, development of the first satellite took 3 years. The quality? One pixel covers 3 square meters on Earth – no surprise with today’s Smartphone camera technology.
This means that the option to piggy-back on a commodity instead of an expensive customised or niche product, has become much more widespread and powerful because of Moore’s law.
The substitution divide
Many products include digital as well as non-digital parts. Since the digital part substitutes faster, and is usually also more connected to a digital ecosystem which substitutes faster, it can affect the whole concept of product life-cycle.
After two years my car is old because it cannot stream Spotify.
Shift left on the S-Curve
The S-Curve is the form of development of most technologies and markets over time. Depending on the phase of the S-curve, different rules apply to competition. At the beginning, it is about attracting interest with innovation. In the steep part, it’s about expanding the attention with marketing, and ramping up production. In saturated markets at the top of the curve, it is about optimising cost, and the big players are in a better position to survive a price war because of their potential to produce at lower cost. In the old world, that was usually when a new technology came in, and the question was who had jumped to the new S-curve early enough.
In the digital world, technologies substitute each other quicker. This often implies that the new S-curve starts long before the old one has reached saturation. The relation between the investment into fast expansion (the steep part of the curve) and its pay-off in the saturated market has fundamentally changed.
One example of this is the music industry. The change from vynil to CD was still “old world”. Now, CDs still are still sold at 50% of their peak in 2000, while download (such as iTunes) is already being overtaken by streaming (such as Spotify).
Attention to customer value
The customer needs, their changes, and the discovery or creation of new needs prove to be more than ever the most valuable compass for the direction of product or service strategy. With digital innovations impacting the customer’s ecosystem with such speed and complexity, the relation of your offering to the customer’s needs is a constant source of surprise.
When the video games company Valve published Team Fortress 2, they had introduced the option for players to create their own hats for the characters they played. Within weeks, the players not only did that, but started trading the hats with each other, exchanging thousands of dollars in the process. For Valve, who had not foreseen that, the option was to immediately design a marketplace for this trade, or loose the connection to that part of their customers’ activity. As their CEO Gabe Newell put it:
Your fiercest competitor is not the other games producers. It is your players.
The amount and lifespan of options
Buy one now? Wait for the next?
Every decision for an asset is a decision against other options. This fact alone is vexing. Whenever you set on one technology, you exclude some features which are only available in other technologies. In a slow moving world, this decision was between the alternatives on the table. You could analyse your options, and then decide. The faster the technological substitution, the more your decision is against alternatives that are just around the corner. Think about buying a computer. If you are looking for an experience which guarantees to ruin your day, just visit a shop a couple of months after you’ve bought a new laptop, and see what you could have gotten now. In retrospect, it would always have been better to wait – but you cannot wait forever. In terms of complexity theory, the gap between premature conversion (closing your search too early) and eternal boiling (closing your search too late), has become narrower.
The same intensified dilemma applies between alternatives which are not fully developed yet. Think about the car industry’s decade-long indecision between the fuel cell and the battery as a substitution for the combustion engine. The digital world is full of such phases of indecision. You cannot wait until the technology, infrastructure and market demand are fully developed. You have to act, knowing that part of what you do is in vain.
Constant change
“Due to the exponential innovation in tech, the rationale of digital business models is in constant change. The bottleneck is not technology, nor money. It’s the human side of the organisation.”
Carsten Schloter
In cyber-social systems, it is the social which lacks behind constantly. Business models, strategies, organisations and skills are in constant change. This means a shift of management attention between running the operational business and developing it. It means an increased weight of everything bureaucratic, everything difficult to change. Like so many others, automotive is a whole industry concentrated on optimising for low cost of production. Compare this to Wikispeed, or the Saab Gripen plane, and you see a new paradigm coming around the corner: optimise for low cost of change, so you can incorporate innovations in every small iteration.
It also means people’s capability to learn, and time dedicated to it, is put under pressure – think about the divide between young and old employees. It also means that if you hire a new person, their capability to fill the vacancy at hand is still important, but their capability to be useful at different, unknown positions within the company gains in relevance, because chances are, the vacancy at hand will not exist in a few years from now, and you cannot afford to replace the majority of your workforce every few years.
The changing relevance of relationships
Last but not least, the speed of digital innovation implies that a growing number of things are either automated, delegated to highly specialised departments, or outsourced to suppliers.
In many U.S. courts, judges use algorithms to indicate a defendant’s “risk”. Based on this risk factor, they may increase bail, sentence, or parole terms. These algorithms are not transparent, but have proven to be very accurate when checked against past cases – reason enough to start using them, isn’t it? The judges were very surprised to learn that on thorough inspection, one of the things these algorithms did was pure racial profiling. Just for growing up in a African-American neighbourhood, the risk index attributed to you went up considerably.
What does this mean for other contexts? You find an increasing number of people who yield the results of something digital they don’t really understand – starting with you as the chief generalist of your business model. The pressure on trust and reliability of your relationships has just gone up – not because you lack transparency on what is going on on the other side of the interface, but because albeit the transparency, you don’t understand what it means, and have to rely on the other party’s word.
The second part of this article takes a look at the effects of the internet, more precicely, of net neutrality: click here.
