Scaling-up scaling-out: lessons from exponential organisations

The recent emergence of exponential organisations

Scaling up can be extremely quick nowadays as demonstrated by start-ups reaching the status of unicorns (i.e. being valued more than $1bn) in a few years only. These companies have been called exponential organisations (ExOs) by Salim Ismail , Michael Malone and Yuri van Geest who investigated the recipes for success of these. They published their results in the book “Exponential Organisations”. What did they learn and can it apply also to scaling out?

Exponential evolutions are new to humankind and our planet. Since we have entered the Anthropocene (i.e. since about 5 decades) however, such trends have become common as shown by many growth curves in population, greenhouse gas emissions, fertiliser application rate, consumption or water use. These are very recent developments posing a real challenge. We have indeed been used to reason in a linear way and there are several examples of prediction errors of renown experts linked to their difficulty to anticipate the consequences of exponential evolutions. A famous example of this is the failure of the Iridium venture, a Motorola spin-off convinced that cell phone towers would not compete with satellites in telecommunication. They planned to launch 77 satellites (77 is the Iridium number in periodic table) but had to stop implementation due to the rapidly dropping costs of the other technology.

Interestingly, a number of organisations have shown remarkable capacity to ride the wave of exponential evolutions. What is fuelling this new trend is the increasing speed and scale of information transfer capacity that follows an exponential law i.e. doubles at a regular pace as does the computer performance which follows the Moore’s law. This capacity irrigates today many sectors such as artificial intelligence, robotics, medicine, 3D printing, neuroscience or the media. On top of this the number of connected devices, that mimics the billions of connected cells of our brain, is also following a similar trend. In 2005, there were 500 million computers connected to the Internet; in 2015 there are about eight billions; by 2020 they should be over 50 billions.

Exponential organisations (or ExOs) build on this fast changing environment as well as on this global interconnection and ease of information transfer. But they have understood that to tap this abundance, they need to abandon several features of the previous linear world. In particular, they need to abandon the top-down and hierarchical processes, the linear product development approach, the internally driven innovation mechanisms. They also need to outsource their human resources and avoid owning and controlling too many assets. In other words they need to become lean.

The result is impressive: while it used to take 20 years at least to most Fortune 500 companies to reach the billion-cap value, it takes the new champions only 1 or 2 years to do so.  And the pace of growth keeps increasing.

After examining the top 100 fastest growing startups in the world, Ismail and colleagues came to the conclusion that ExOs rely on a common approach and on 10 key features.

10 key features

ExOs also have a number of common characteristics in the way they manage their resources and interact with their environment. These characteristics can be arranged in two groups, one describing the way ExOs function and one how they interact with their environment.

Relations with the environment

Staff on demand: the idea here is to outsource as much as possible the competences required for the company. The permanent staff of the company needs to be reduced but the number of outsourced competences increases the flexibility and capacity to adapt permanently to a constantly changing environment

Community and crowd: beyond their staff and competences, ExOs have managed to create big communities around them. They aggregate people motivated by the challenge of their MTP and most of the time they develop “platforms” where this community can exchange and create in an open manner

Algorithms:  Managing huge data flows is part of the DNA of many ExOs. This can only be achieved through powerful algorithms able to extract relevant information from these data. Artificial Intelligence has even become the new frontier of these algorithms as visible in Deep Learning and Machine Learning tools that are rapidly disrupting old business models.   

Leveraged assets: many areas have a lot of assets already and the art of ExOs (at least in the initial part of their existence) is to extract value of assets in which other people or companies have invested. They build on the “sharing economy” momentum and prefer to maximize/optimize the use of these assets than to build and own new ones. This strategy obvious for Uber or Airbnb is a generic tendency of many ExOs  

Engagement: ExOs actively manage their communities using engagement tools. These tools include instant feedback mechanisms (Like, evaluate) but also gaming tools or loyalty cards. These tools manage to transform crowds into real communities and are very useful as marketing mechanisms.

Internal engine

Interfaces: ExOs rely generally on platforms that provide the interface with their communities. A typical example of such an interface is the Apple Store which contains more than 1.2 million apps and involves more than 9 million developers. These platforms are essential for the scaling of ExOs and in particular to their leveraging of external assets and talents   

Dashboards: Management of fast growing ExO is a challenge and has triggered the development of new tools. These tools are based on dashboards and on new types of KPIs, named Objectives and Key Results (OKR). OKRs are about the company’s goal and how the employees contribute to these goals. They are mostly determined in a bottom-up way. They tend to be set for for short periods of time i.e. month or week and need to be very ambitious (and not reachable).  

Experimentation: The lean start-up approach is at the heart of the management. Acceptance or even willingness to fail are key. It is important to experiment and learn from the users and consumers in order to adjust very quickly in a fast changing environment.   

Autonomy: Because adaptability needs to be high, the processes are decentralised and bottom-up. Holacracy, where authority and decision-making are distributed and not concentrated at the top, allows quicker reactivity and responses to customer demand. ExOs demonstrate that holacracy is relevant even in large organisations.  

Social: in an ExO, the relationships between employees also changes. A “sharing culture” is required to adapt to the delocalised, bottom-up processes. New file sharing, telepresence systems, task management tools support the organisation. The emotional intelligence is also critical to the new working environment.     

All these key features do not need to be present in ExOs but the more they are present, the more likely it is that the ExO will be successful. Within the 100 ExOs examined, at least 4 of these characteristics were represented.

Main lessons

To summarize, successful fast-growing companies ride the information wave, adapt themselves very quickly by test and error approaches, are highly decentralised to increase their employee’s autonomy, externalise their resources and assets and finally adopt a massive transformative purpose that help them aggregate a big community around them.

If these features are important to scale-up a company quickly, they could also be applied to scale out and deploy new solutions for the welfare of humanity and planet. Indeed all of them seem to apply also to the replication of good solutions. A Massive Transformative Purpose is not specific to a company; decentralised functioning and autonomy of the people seems obvious for a replicated entity as is the leveraging of external assets and competences.

The important difference is probably elsewhere. A company is in essence an “existing thing” in which everyone can believe in (see Sapiens), that has institutionalized its functioning and created a recognized brand. In other words trust in its efficient functioning is at the core of its existence and this trust is materialized by e.g. the value placed in it by investors or the size of its community.

But could we imagine a completely decentralised body, made of small separated entities functioning in a similar way that would generate trust among a large community and in the investor’s community? Probably yes, because we observe today the development of disruptive “decentralised trust engines” that do not depend on a central function. The bitcoin is such an engine that created sufficient trust among a global community to become a virtual currency independent from a central bank. It uses the blockchain technology itself based on powerful encryption methods. The bitcoin was just a pioneer. The blockchain technology is currently giving birth to many other tools aiming to create trust among communities independent from any central body.  

The future of decentralised scaling out has perhaps already come!