Sunday, February 16, 2014

The danger of mega trends ...

I recently read this McKinsey post on digital mega trends by Willmott Paul. Ok, to be honest I rarely read McKinsey reports or posts because they're not often relevant to my particular line of work but occasionally I do as general background (same with Gartner).  Normally I wouldn't respond but in this case I feel the need to because it's potentially dangerous despite its obvious attempt to be helpful.

The premise of the work is that 'Large digital players (e.g., Amazon, Alibaba) can create cost, talent and data advantages, which in turn can be used to price competitively, innovate rapidly and acquire further market share'. Whilst that's perfectly true it goes on to miss how this occurs and in this are the dangers.

To explain why, I'm going to need to cover some fairly basic stuff and for those of you who've read my blog extensively then this is the point to jump to the conclusion.

The Basics

Point 1) Activities, practices and data don't just diffuse but they also evolve through a common pathway (see figure 1) due to supply and demand competition causing multiple waves of diffusing and ever improving examples. As they evolve their properties change from uncharted to industrialised (see figure 2).

Figure 1 - Evolution (in this case applied to activities).

Figure 2 - Changing properties

Point 2) Organisations consists of many value chains built from multiple components whether activities, practices or data.  Those value chains constantly evolve but you can map out an organisation by examining value chain vs evolution at a point in time (see figure 3).  Such maps are effective in communication and you can use them to not only determine how you should treat something at a point in time but also for strategic gameplay and learning of economic patterns.

Figure 3 - Value chain vs Evolution map for HS2

Point 3) There are many core economic patterns. One of these is componentisation and how the evolution of a component not only increases efficiency but also can enable higher order systems to appear - see figure 4. This pattern (along with many others such as economic cycles, inertia, relative importance of strategy vs culture, creative destruction, co-evolution of practice, how new organisational forms appear) occur throughout history.

Figure 4 - Evolution begets Genesis

Ok, so our organisation (and competitors) consist of value chains built from evolving components (activities, practices and data) and as they evolve then not only do their properties change but they can enable new higher order systems (and new value chains) which become new sources of value but are highly uncertain by nature.

Point 4) The interplay of these forces creates an issue in competition called the Salaman and Storey Innovation Paradox.  As components evolve they become more efficient and you have to adapt to this in order to effectively compete today i.e. if you're a car manufacturer then you have to use common components like standard nuts and bolts, headlights, wheels, airbags and modular PCB's (exploiting the value chains of other providers in this space) rather than building your own from raw ingredients. However, at the same time that you have to efficiently treat certain components in order to be cost effective and survive today, you also need to differentiate with the novel in order to survive tomorrow by creating those future sources of perceived value e.g. self drive, automatic parking etc. Naturally past novel items - electric windows, seat belts, airbags - have become today's standard components.

This combination of efficient treatment and differentiation requires polar opposite styles of management in the same organisation, hence the paradox.

”Survival requires efficient exploration of current competencies and ‘coherence, coordination and stability’; whereas innovation requires discovery and development of new competencies and this requires the loosening and replacement of these erstwhile virtues”

So whenever you examine your value chain (or chains) which define your business then you have to compare with competitors and adapt to both more efficient provision and the creation of the novel (see figure 5).

Figure 5 - Efficiency and Differentiation.

From the above, for a value chain within in an industry (consisting of components A to F), a company is compared to its competitors. The competitors have a differential B which the company lacks and also more efficient provision of C. The company has an efficiency benefit in D. 

The company needs to consider both an efficiency drive around C and examine the inclusion of differential B into its offerings in order to remain competitive.

Point 5) The map can be manipulated. When comparing a company with its competitors you can accelerate the rate of evolution of a component through open means or de-accelerate the rate through limiting competition (e.g. patents, regulation, acquisition, use of constraints). You can also take a deliberate position and exploit competitors inertia to change. In the above example, you might choose to drive component C to a more utility service (C'), exploiting competitors inertia to change (due to exiting models and practices) and enabling more rapid development of higher order systems built on this component (see figure 6).

Figure 6 - Changing an Environment

Whenever you compare your value chains with competitors, you often find multiple opportunities and points of 'Where' you can attack either adopting of novel activities, removing inefficiencies or deliberate manipulation of the environment and exploitation of competitors constraints and inertia. Understanding 'Where' you can attack is essential for determining 'Why' as why is a relative statement (why here over there). Once you have determined where you can attack and from this derived why you would choose one course of action over another then the how, what and when become relatively trivial exercises.

Point 6) Predictability of what to do varies which makes management complex.  One of the major issues with scenario planning is the issue of predictability. For example certain changes (such as the evolution of a component) are highly predictable in terms of what is going to happen. i.e. you can say the shift from product to utility is involved with; disruption of past industries that are stuck behind inertia barriers, co-evolution of practice if the evolving component is an activity, reduction of potential barriers to entries in secondary industries and rapid increases in higher order systems and un-modelled data. 

This is how back in 2005, many of us were able to clearly and precisely predict the changes of cloud computing, the growth of devops and big data, the rapid increases in novel systems built upon this and disruption of past h/w vendors. More importantly, many of us were able to game this to our favour.

Unfortunately whilst what was going to happen is highly predictable, when this change will happen depends upon competitors actions and whether the component is suitable for provision in the next stage (i.e. ubiquitous and well defined enough), that technology exists, that the concept exist and that a prevailing attitude of dissatisfaction with the current mechanism of provision exists. Fortunately there are a range of weak signals you can use to determine this.

When it comes to the genesis of novel components then by their very nature they are highly uncertain and unpredictable. There is an inverse relationship between future differential value and certainty which means we always have to gamble. When examining a value chain you have to bear in mind that predictability varies with state of evolution, I've summarised this in figure 7.

Figure 7 - Predictability and Evolution.

This leads to a question of should we be a fast follower or first mover to change?  

Point 7) Should I be a first mover or fast follower? Being a fast follower to the genesis of a novel component has certain strong advantages in allowing others to expend research and development on the uncertain and then cherry picking only that which is starting to evolve and become successful. But should I be a fast follower to a component that is evolving from product to utility?

In direct contrast to novel components, there is a strong advantage in being the first mover to shift from product to utility due to componentisation effects. This is exemplified by a model known as ILC (innovate - leverage - commoditise) or what I call the 'Wardley Thompson Technique'.

By being a first mover to industrialise a component to a utility then assuming you allow for public consumption of this then you enable other companies to build higher order systems on top of it. Those higher order systems will contain many novel components and the more efficiently you provide the utility service then the more you will encourage others to build on it by reducing cost of failure and experimentation.

These other companies are your ecosystem. Fortunately for you, as examples of those novel higher order systems start to diffuse and new improved versions appear then you will be able to detect this through consumption of your utility service. This enables you to get others to innovate for you (i.e. deal with the uncertain) and then leverage consumption data in your ecosystem to spot success. Once success is spotted then you can then move to industrialise the new components to a utility service.

For example, if you provided utility services for infrastructure (such as Amazon EC2) then as others built novel big data systems on top of this then you could leverage the ecosystem to spot success and commoditise to a utility services (such as Elastic Map Reduce).  Whether Amazon uses such a model we won't know but the model has some profound impacts which are detectable.

Under the model your rate of apparent innovation, customer focus, efficiency, ability to maximise future opportunity and stability of revenue will all become dependent upon the size of your ecosystem rather than the physical size of your company. Effective exploitation of the model which requires extensive data analysis of your ecosystem, speed of data feeds (i.e. utility consumption data is far more effective than marketing surveys) and an ability to act means you can create a company which continuously and simultaneously appears to grow in terms of innovation, customer focus and efficiency at faster rate than physical size. Of course, the process of running the model does mean you will occasionally feed upon (or harvest) your ecosystem either through acquisition or copying. See figure 8.

Figure 8 - Innovate, Leverage and Commoditise

As a rule of thumb you always want to be a first mover to industrialise but a fast follower to the uncharted (i.e. genesis of the novel and uncertain).

Point 9) - Gameplay is not uniform. Despite many talking about the importance of strategy, the level of gameplay and situational awareness varies wildly between companies. In an examination back in 2011 of 160 different companies, the Players (which demonstrated high levels of situational awareness, strategic gameplay and action) and to a lesser extent Thinkers (demonstrated high levels of situational awareness and gameplay but less prone to action) significantly outperformed the Chancers and Believers (both show low levels of gameplay) in terms of market cap growth - see figure 9.

Figure 9 - Strategic Gameplay vs the Use of Openness to compete (action)

More details on this can be found here.

Point 10) - This is the tip of iceberg.  I've spent the past decade researching into this field and either using the patterns in anger within companies or teaching members of the LEF (a private research group) to manipulate their environment. There's a whole range of highly predictable patterns from economic cycles (e.g. peace, war and wonder) to how new organisations evolve along with a mass of different gameplay (from sweat and dump to tower and moat) and common economic effects from punctuated equilibriums to the Red Queen. There are also some very good game players out there along with a number of companies who have shockingly poor situational awareness at the executive layer. 

Even basic questions like the different forms of inertia (see figure 10) to 'culture eats strategy for breakfast' turn out to be complex and often vary with evolution (see figure 11).

Figure 10 - Different forms of inertia

Figure 11 - Culture vs Strategy


We operate in a highly complex environment where situational awareness is critical. Our companies are comprised of value chains consisting of masses of evolving components (from activities to data). The means by which we manage, how we govern and even strategic gameplay varies with how evolved those components are. Even the importance of strategic gameplay relative to culture varies with how evolved the components are.

Understanding both your position, the position of your competitors and where you can attack is critical in today's economic climate but the reality is that many companies appear to have poor situational awareness which is why these Chancers and their industries are quickly overwhelmed by more skillful Players.

Situational awareness requires an understanding of your environment and this is not something generic strategy advice can give you but instead it is something you have to acquire through an understanding of your industry. You have to learn to play the game, it is a skill like playing a game of chess.

The McKinsey post is a generic list of useful stuff e.g. digital firms have a cost advantage, large digital firms have better access to talent, digital leaders are amassing vast quantities of data, digital firms require fewer people to operate and consumers tend to use fewer brands online. 

Yes, it is absolutely correct that there is a difference between traditional and next generation firms (see figure 12)

Figure 12 - Delta between Traditional and Next Generation (2011)

However, the problem with the post (and the same problem with the above list that I produced) is that it might tempt companies to go - 'we need to be more like these digital firms', 'we need to be more like Silicon Valley'.

Don't get me wrong, I'm not having a dig here at Willmott as the post sets out a reasonable set of changes. The issue is that companies might just adopt it and here's the rub. By blindly attempting to emulate 'Amazon's example' and without good situational awareness then you're just as likely by implementing such actions to encourage evolution of components in your value chain, undermine barriers to entry, reduce constraints protecting your industry, make yourself a more attractive target for a player to attack by laying down groundwork for a utility model and potentially hasten your decline. Playing a game of chess without looking at the board and just copying others actions is a disaster in the making - it's like a general bombarding a hill because some report says that '67% of successful generals bombard hills'. 

You need to think very carefully about your environment before embarking on such actions. There are some extremely skilful players out there, it's easy to get massacred with poor situational awareness - be warned.