“Digitization” seems to be the buzzword of our time to unlock just about any business conversation, it’s literally omnipresent. And yet there is no established definition. Are you using this word correctly? Or are you simply wanting to jump on the trend to seem innovative? This is what we like to call ‘Innovation Theatre’.
The original meaning of the term Digitization was converting analog signals into binary ones. The prime example of that meaning was digitizing music to CDs. However, this narrow definition does not do justice to the widespread implications of the ongoing transformation in business and society alike.
We have developed our own digitization framework, based on our many discussions with partners, innovation leaders, and VCs. It shall help you to decide on the right approach for your strategy. This framework will touch upon the two different objects of digitizing – our ongoing business and our future business, as well as the 2 levers to transform – people and technology.
Why do we need to digitize?
Let’s start with the why, in order to put the framework in perspective and make sure we apply it for the right reasons.
Technological development has changed customer expectations. In the past, it was sufficient to develop a standalone new product, and once the product was ready, push it into the market. However, communication and information have become so widespread and fast, that this previous way of working is not functioning anymore. Customers now want their expectations to be exceeded, almost immediately.
Simply put, technology turns customer intimacy into a competitive advantage and hence it develops an edge of growth or margin. This is unprecedented in history because, for the first time, technology enables scalable customer intimacy.
Vice versa, the lack of it has become a death sentence for a business (most notably in the form of bad reviews with better scoring competitors just a click away).
There is a very direct consequence for the way we manage a digital business: Traditional metrics such as cost or revenue ratios don’t make sense for growing digital models, at all. The only meaningful financial perspective here is the unit economics view:
All that counts is how much you pay for a new user and how much money the user will generate over his/her lifetime within your business. Hence, there is an inherent financial incentive to make customers happy in order to loyalize them, e.g. through good value-for-money or superior service. Actually, this should be hard-wired into every truly digital model.
The second effect of this technology development is that it has become easier for new entrants to develop products and go to market. In the past, big investments in digital infrastructure and marketing were necessary. Now, with cloud services and ‘as-a-service’ offerings, the required investments have been reduced to a minimum, and new players can go from inception to market in a matter of weeks. This hurts when it takes your company months or even years to come up with new products or insights.
The third reason why we should transform is the huge crisis we’re currently facing with COVID-19. Nobody knows what the result of the pandemic will be, but what is already clear is that digital penetration has condensed years into weeks. The cost in human lives and economic destruction is enormous and very sad, but it also offers enormous opportunities. But your company needs to be able to capture these opportunities and grow them into new businesses, now or never.
Customer focus means experimenting and exploring
The challenge with customer focus is that the customer often doesn’t know what they want. Often they only realize after having experienced a solution that actually there was unidentified pain. This means we can not ask the customers what they want, or if they would buy a product or service. We need to adopt an explorative mindset, experimenting continuously to surface the real pain points for our customers. That is why one of the most important success factors in achieving growth is to prioritize exploration over exploitation.
In the past, we could innovate linearly, from idea to final product, and push it into the market in a commonly used waterfall approach. This doesn’t work anymore and we need to adopt a trial and error approach, with continuous customer feedback processes put in place. We need to change our mindset to assume we’re wrong, to then create multiple hypotheses and work in small increments that are immediately tested.
What do we need to digitize?
Now that we’ve figured out why we need to transform, the question arises of what it is you are needing to digitize. In order to illustrate this, we would like to use a practical case from Safi Bahcalls book “Loonshots”
Imagine a middle manager at a great company and (s)he has to evaluate a new important project. This project can bring major new revenue streams for the company in the long term. But the project is messy. It’s still in its infancy, there are still many open questions, and success is not assured. This manager now has 2 options:
- Defending the project: this will mean a multi-year battle, with unsure success, defending the project in every evaluation meeting. Innovative projects need to pivot various times on the way up, which are all moments where the project can get killed by the organization, often hungry for budgets.
- Not supporting the project, but instead using all her/his skills in showing its flaws, and why it will not work, making sure her/his direct boss can see how smart (s)he is. Instead (s)he proposes a “safe” project, a small improvement of an existing product, with a neglectable chance of failure and very aligned with everybody’s interest.
This example illustrates perfectly the tension that exists between new growth initiatives, and core business innovation. Our organization is a well oiled, high performing machine, set up to deliver a product or service in an efficient, predictable and repeatable way. Anything that deviates from that will be seen as a threat: the general manager will worry about cannibalization of existing product lines, marketing is worried about brand damage, manufacturing will worry about small, inefficient production for small batches, legal will worry about non-compliance, sales will not want to push a product with unclear performance, etc.
However, if the organization can make something more efficient or introduce something new in line with existing procedures, it will embrace the effort.
With this, we have the first 2 opposing sides of our framework: efficiency vs growth.
How do we digitize?
When we look at our well oiled, high performing machine, we basically have 2 levers delivering the value: people and technology. Technology includes all the tools and systems we need to deliver the value.
With the 2 goals for digitization, growth and efficiency, and the 2 levers, people and technology, we can set up our 2×2 digitization framework.
The 4 quadrants of the framework should not be seen as independent quadrants, as will be explained below.
If the Goal is Efficiency: Culture and Processes & Systems Transformation
The first step is putting the right conditions for this transformation into place, in other words digitizing processes and preparing the internal IT infrastructure for future demands: the transformation of processes & systems. This usually means a cloud-centric infrastructure, enabling data to be accessed by everybody, anytime, from everywhere.
Data is the most critical asset that modern organizations possess. As a second step, we need to create a modern data foundation by aggregating and cultivating clean, connected, and authoritative data that is cataloged and easily discoverable in a common location and any team can understand how to use it to create insights and intelligent experiences, as described by Microsoft.
On top of this, we need to augment and accelerate human decisions using trusted intelligent models built on the wealth of available data and use analytics services to understand user journeys, processes, behavior, and insights.
Many automation initiatives turn out not to be as easy to implement as initially thought because they face internal resistance. That’s when many organizations realize that there is also an important aspect of a cultural transformation to digitization. Hence, they start to “work on” their culture, e.g. through management tours through Silicon Valley, the hiring of agile coaches, the introduction of scrum methodologies, and the like. Often with the intention to become more “startup-like” or “agile”.
However, before trying to change their culture, organizations really need to be crystal clear as to why they want to do that. Referring back to the two goals for digitization mentioned above, most cultural change initiatives should be focused on efficiency, not growth. This is because the parent organization’s goal usually is also efficiency and hence neither the managers nor the people can deal with substantial exploration efforts that will always lead to digital diversification in consequence.
If cultural change attempts are directed towards “making the organization more agile” and are thereby trying to turn an exploitative organization striving for efficiency into an explorative one striving for growth, they are doomed to fail. It’s because culture is a complex beast: It’s not only about changing individuals’ behaviors, it also comprises all the explicit or implicit rules, codes, management systems and behaviors within an organization. In fact, it’s so terribly difficult for human beings to change substantially that this is the most difficult aspect of a digital transformation.
In most organizations, this is not a feasible target state. The prerequisite for launching successful explorative endeavors in a true digital culture is therefore primarily a governance topic, not a transformation issue. This means in particular that digital ventures/products must be kept structurally independent from the legacy business. In particular, the legacy business must not be allowed to determine either business modeling or strategic priorities or operations of digital models. This leads us to the 3rd step of the innovation framework.
If the Goal is Growth: Business model and Technology innovation
Once organizations start to have an internal awareness of the fundamental changes going on through digitization, they start to look outside their walls (e.g. through “Open Innovation”) and discover that there are alternative ways of thinking about their own business.
It’s usually startups or products of large tech companies, which start to directly attack parts of the legacy business and by doing so in a completely different manner, they question the status quo. Hence, the incumbents move into questioning their own, old business models and try to develop them further or to develop entirely new ones. This is what we refer to with business model innovation.
Business model innovation is driven by the ongoing pursuit to constantly identify and solve customer problems using the technology progress of the day.
It is either aimed at developing new businesses, products, or services or at transforming existing ones around an evolving understanding of a customer opportunity. Business model innovation requires technology but mostly doesn’t drive technological innovation in the first place. On the contrary: Most business model innovations are entirely built with off-the-shelf technology that has just become available, at least for their first iterations.
Examples: Food boxes (e.g. Blue Apron), UBER, Flixbus, AirBnB, Instagram.
Technology innovation is driven by exploring what is technologically just feasible at a given time. It often stems from fundamental research in any field of science, without use cases in mind in the first place. Technology innovation is not the defining element for succeeding in a digital environment, but it’s a prerequisite making the evolution of new digital models possible.
Technological innovation is the first step of digitization when it comes to new technologies that enable new business models altogether. Think about blockchain, which enables entirely new, decentralized business models, which fueled many companies’ digital visions. But it’s also the last step of digitization in a way: When new business models are developed, they ultimately start to realize that there is a technological gap between what technology can buy on the market and what they need to develop that business model even further. At that point, digital business models often start to develop entirely new technology at some point as part of their constant evolution. Hence, technological innovation is where the digital circle closes and restarts again.
Examples: LiDAR, high precision computer vision, blockchain, deep learning neural networks.