Tuesday, February 19, 2013

Differentials, Barriers and Constraints

We now need to turn to those maps and identify specific roles and constraints for the various components before we start to attempt manipulate the environment through some form a strategy.

The first role we need to identify are those visible top-level components that act as differentials i.e. they provide to the consumer a qualitative difference between our offerings and most of our competitors. Such components will be in the genesis or custom built stage and in the case of the Fotango service, this was image manipulation.

You also need to identify those components that act as a barrier to entry into your value chain through high levels of capital (either physical, financial, knowledge or social). These tend to be hidden further down the value chain and are mainly invisible to the consumer. In the case of the Fotango service, our engineering skill and knowledge in building large-scale distributed systems capable of coping with millions of registered users was such a barrier.

Finally, you need to identify constraints and in particular the balance of power between consumers and suppliers. I tend to use Porter’s five forces here. For those unfamiliar with five forces, these are:-

Rivalry within industry: this can be assumed to be a given though the type of competition changes e.g. from relative competition in the peace phase to a fight for survival during the war phase.

Threat of New Entrants: increases as an activity evolves from the peace stage of competition to the war stage.

Threat of Substitution: often the most difficult to spot and manage, tends to occur in the peace phase of competition e.g. replacement of cable excavators with hydraulic.

Bargaining Power of Suppliers Vs Consumers: the balance of power between the groups affects a range of areas from pricing to dependency to strategic control. For example, in a value chain if one supplier provides one component, then that supplier can exert considerable pricing pressures on your entire value chain.

The balance between these forces tends to change as anything evolves. It also isn’t static within a stage of evolution. For example, when an activity becomes more of a commodity or provided as a utility we will often experience a yo-yo between centralization and decentralization (with a corresponding yo-yo between Supplier and Consumer bargaining power).

With commoditization (i.e. evolution for activities), it is often assumed that the shift towards utility provision means centralization but this is not the case. Whilst the interaction of ALL consumers (demand competition) and ALL suppliers (supply competition) drives the process of evolution, the question of whether a specific activity or data set centralizes or decentralizes depends upon the actions of individual actors (suppliers and consumers) in this market. 

Hence for example, with Cloud Computing and specifically Infrastructure as a Service (IaaS), the shift from product to utility is simply a process of evolution driven by market competition (ALL Supplier and ALL Consumers). 

On the question of centralization, it would have been relatively trivial for the hardware manufacturers to create a price war in the IaaS space around 2008-2010 in order to fragment the market by increasing demand beyond the capability of one vendor to supply.  The fact they didn't is their own fault and also one of the major factors why we might see centralization in the IaaS space. Hence centralization depends upon the actions of specific actors (in this case the inaction of hardware suppliers and hosting companies).

In the future, this may in fact yo-yo from centralized to decentralized or find a balance between the two (as with electricity provision and self generation). Of course this is a change in the means of production and the interfaces themselves are unlikely to change i.e. a shift from central to self-generation does not mean a change in voltage / frequency for domestic power provision.

The interface can often hide a complex market. For the average home consumer of electricity you have sockets and a power supplier. You could be forgiven for thinking your home electricity supplier actually generates the power. However their value chain includes components such as the National Grid where they consume and purchase power from multiple power generators (their suppliers) through a complex market including spot and derivatives. There is no reason your actual home electricity supplier has to own any actual power generation capabilities themselves and they can instead act more like a broker. In the UK, such distinctions are licensed through OfGem with suppliers, generators and non physical traders.

Hence, you should always be careful about assuming that as an activity evolves to more of a utility it will centralize into the hands of a few suppliers. There is a danger that this will happen but it all depends upon the individual actions of specific players in the market. In figure 50, I provided an example of some general changes in the five forces.

Figure 50 – General changes in the five forces

During the Peace phase of competition then substitution tends to be something to watch for but new entrants are relatively rare, competition is often relative between big suppliers and a yo-yo between supplier vs consumer bargaining power can exist but is often relatively minor.

As the activity evolves to more of a utility, hence the shift from peace to war, then competition becomes more of a fight for survival as new entrants appear. The balance of power can shift towards suppliers (centralization) if other potential suppliers such as past product vendors fail to act appropriately. Beyond peace and war, the state of wonder also tends to be an aggressive fight for those new activities but in this case it is more a case of a fight to become established, to prevail over other equivalent attempts to provide the new activity by many new entrants. 

All competition is a fight but it’s worth emphasising (and repeating) the different economic states for any component.

Wonder: New activities appear and a fight to become established occurs in an uncertain and un-established market. Consumers hold the balance of power and you’re competing against other entrants with no idea of whether any will be successful. Everything is a gamble and a huge risk with rapid change.

Peace: Activities are provided in a relatively well-defined, widespread and established market. Large competitors jostle for relative positions and to maintain profitability. Inertia to change builds due to pass success. There is often a balance between consumer and supplier bargaining power. New entrants see an almost impossible mountain to climb and must look to substitute and disrupt existing suppliers often by changing the value chain. Whilst difficult, this can be achieved by adding to or altering the visible components associated with a product (e.g. smaller hard drives, more energy efficient) and then establishing these components in an alternative market. The occasions were the giants are disrupted are relatively few as sustaining change tends to exceed disruptive, however disruption can occur due to changes in the value chain. This is hard to predict and hence defend against and is compounded by inertia.

War: Activities evolve to more of a commodity (or utility), new entrants take up the charge into the space with past giants having inertia to the change. For these giants a fight for survival for their massive established business occurs, many will be disrupted by what is entirely predictable and could be defended against. Due to the speed of change and depending upon how well the game is played, the balance of power can shift to large centralized suppliers. 

At this point, I tend to mark up the map with the following legend (see figure 51) covering differentiators, barriers to entry and five forces. I also include future changes i.e. what happens as activities (or data or practices) evolve and add inertia barriers to change (i.e. caused by past success).

Figure 51 – Legend

Using the above legend, I’ve updated the Fotango Map (see figure 52). From the map, the reader should by now be able to read that Fotango had a value chain of many components at different stages of evolution. The Fotango service itself was building an ecosystem of end users and was in a maturing field that was moving from a fight to become established towards more relative competition. Consumers currently held the power and substitution was a threat.

The provision of image manipulation was a differentiator though we had no idea whether it would be successful. Consumers again held the bargaining power and new entrants providing image manipulation services were common.

Figure 52 – Map of Fotango, 2005

Platforms, which were used to build the Fotango site, were in a relatively peaceful state of competition with well-established platform players and the only main threats being substitution. This activity (like all) was evolving and becoming suitable for utility provision (PaaS). New entrants were likely to take up the charge and establish broad ecosystems that also led to a danger of centralization. Past players were likely to suffer inertia barriers to the change.

Infrastructure was even more of a commodity and was also suitable for provision as a utility (IaaS). It currently existed in a relatively peaceful market of large players with the only main threat being substitution. Those players would have inertia to the change and the new entrants could build broad ecosystems and potentially centralize if the existing giants failed to act.

The future IaaS world could power the PaaS world.

One of the barriers to entry in Fotango’s space was the ability to build large-scale architectures dealing with large volumes of users. This was a highly skilled engineering task and such knowledge could be considered a barrier to entry into the business. 

Writing these maps is a big undertaking. A fully-fledged map for a value chain can take up to two hours of efforts and it's not strictly necessary to go into the detail of mapping out forces, value can be gained just by doing a simple map of value chain vs evolution and just thinking about the above when reading the map is enough. However, I thought I'd at least show you this for completeness sake.

Given 40 or so value chains in an organization, you could be looking at two weeks effort to get a really clear understanding of the environment. But it’s worth it because now that we can write and read maps then we’re finally getting ready to start playing the strategy game.


Post 21 on the Management and Strategy series.

Next post in series ... The Strategy Game

Previous post in series ... Mapping a Company

Beginning of the Management and Strategy series ... There must be some way out of here


Andrzej Łączny said...

Dear Simon,
I must admit, that for 2 weeks now I've been heavily thinking about some articles/speeches on your blog/youtube regarding the strategy, battle maps, value chain and evolution cycles. What I really like about your approach is that you focus (but not completely) on later stages of the evolution lifecycle (maturity, commoditization), where a great majority of researchers tend to look into the innovation, inception side and forget the other one.

For the purpose of better understanding, I try to bridge your model with technology adoption lifecycle (Geoffrey Moore) and phases of industry lifecycle (after Robert Grant and his “Contemporary Strategy Analysis”). However, some things do not quite fit, therefore I allow myself to post some of my points and questions:

1) Moore introduces the “laggards” phase which could fit to the phase of war (commoditization) in the evolution model.

Question 1: However, this would mean that Moore’s phase does not only consists of “laggards” but also “innovators” (creators of higher order systems based on commodity) as customers, wouldn’t it?

Question 2: It also means that the “laggards phase” does not have to imply product/industry decline. Demand created by higher order systems would keep it alive, wouldn’t it?

2) I have troubles matching the your “Peace” stage with Moore’s model. As I understand it, the peace starts when the market slows down in terms of growth (you also mention the “growth” phase before “peace”). “Peace” would be the phase of “cow milking” for market leaders and established players. It implies the mapping to the stage of a product entering the “main street” - at the end “early majority” till the end of ”late majority” phase in the Moore’s model.

Question 3: In one of your posts, you map the peace stage to the evolution phase. It starts already in the “custom built”. This does not fit, because Moore’s model requires the “whole product” in order for the industry to start growing. Furthermore, also the growth phase is not peaceful (especially for hyper-growth-markets). You also seem to support it by placing the product stage on the evolution curve where ubiquity grows at the fastest (also implying the growth phase, not peace).
For me, this places the peace phase starting, let’s say, in the in ½ of your product phase (evolution lifecycle) and ending at the end of it (where you place inertia), just before commodity (in Moore’s terms - at the end “early majority” till the end of ”late majority”). Do I miss something here?

3) As I understand you are not keen on mapping Gartner’s Hype Cycle to the evolution cycle, but I still find such exercise useful for better orientation. The easy part seems to be the fit of differential value. I like the mapping suggested by Mike Slinn’s Blog (http://mikeslinn.blogspot.com/p/combining-technical-marketing.html). In terms of evolution, this would mean (highly simplified, of course):

Genesis: Technology trigger
Custom built: Peak of Inflated Expectations, Trough of Disillusionment,
Product: Slope of Enlightenment (just after crossing the chasm), Plateau of Productivity (when the growth starts).

For operational efficiency, the mapping is different. It starts during the peace stage (“late majority” in Moore’s terms) and possibly reach Plateau of Productivity at the beginning of commodity/war phase.

Question 4: Would you agree?

Question 5: It would mean that we have a second chasm for operational efficiency initiatives (data, practice or products) providing input for value chains in mature industries moving towards commodity. This chasm would block further movement towards commodity based on initiatives that did not gain wider acceptance. On the other hand, does the movement towards commodity require broad acceptance of operational efficiency initiative? Perhaps, there is a need only for one player to introduce it in order to commoditize the market?

This things are bugging me for the last couple of days ;-) Would you care to comment on them?

Best regards,

swardley said...

Hi Andrzej,

Moore's work (crossing the chasm) is based upon Everett Roger's and the diffusion of innovation. This is adoption of a change over time i.e. how that change diffuses.

Evolution is NOT about diffusion. Evolution is about how any activity matures. It is measured over Ubiquity vs Certainty and there is no time axis.

So for example, the first electric power generation system appear (the parthian battery) ... it diffuses.

Then better, custom built systems appear (Hippolye Pixii etc). They diffuse (early adopters to laggards).

Then products (electric generators) are introduced and they diffuse (early adopter to laggards). Each subsequent improved version growing the market but each version having early adopter and laggards.

Then utility provision of electricity is introduced. It diffuses (early adopters to laggards), each improved version goes through subsequent diffusion processes until a massive scale, volume operation based, widespread and now mature market is created.

Diffusion covers how each individual change "diffuses" through society from early adopters to laggards - whether a better phone or utility provision of something or some product.

Evolution covers how an activity evolves from the genesis of something (e.g. archimedes screw) to commodity provision (e.g. standardized nuts and bolts)

Don't confuse diffusion with evolution - the two are different.

What you appear to be doing is you seem to have assumed that the evolution curve (because it happens to be an S-Curve shape) is the same as the diffusion curve. They are entirely different on different axis and measuring different things.

swardley said...

Hi Andrzej,

Mapping Evolution to "Gartner's hype cycle" is a non trivial exercise, depends upon some extensive modelling and huge assumptions.

I provide a generalised view of this here

The conclusions of which are that the hype cycle overlaps multiple areas of evolution and is also subjective (i.e. not based upon a physical measurement of a characteristic of what is being examined).

swardley said...


I these days use the term Genesis to refer to the novel and new because Innovation can mean Genesis, Feature differentiation of a product or the shift of a pre-existing activity from one stage of evolution to another.

Hence, in it's current usage, the entire process of evolution is buried under the term innovation - which is why I don't use it much anymore.

It's a pretty useful term. Genesis is much more apt.

Andrzej Łączny said...

Hi Simon,
Tasty food for thoughts. Much appreciated! However, It was not the S-curve that attracted me to combine adoption/diffusion and evolution, but relation between ubiquity and diffusion. It is a matter of definition, I suppose, but I would be expecting diffusion to support growth of ubiquity. It seems to me they ubiquity depends on diffusion....

Following your line of thinking, let me go further and suggest:
1) Ubiquity is the sum of diffusions of related sub-activities in various stages of evolution. Growth in ubiquity comes from more and more products diffusing among bigger and bigger customer base. Correct?
2) Ubiquity (as the function of certainty or evolution) mirrors the size of an industry (containing many products that diffuse). Correct?
3) Moore introduces various customer types along the lifecycle of technology adoption. However, if the ubiquity for custom built activities is smaller than that of products and commodity, it means that eg. late majority adopting custom built activities is smaller than late majority adopting products. I could mean that late majority adopting custom built activities differs from the late majority adopting products. Is Moore wrong mapping customers types only to diffusion and not both, to evolution and diffusion?
4) if 3 is correct, where is the chasm?


PS. I know your post on Gartner’s Hype Cycle, but I’d rather clarify my understanding of diffusion vs. adoption first and leave comments on Gartner for a while...

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