The Fast Follower Conundrum

I was asked a really odd question recently - "Should a company be a first mover or fast follower of innovation?"

I responded "Both!"

To explain why requires a long post covering value, perceived value, componentisation and evolution. This won't be an easy ride for those new to my work but manageable for those who are familiar.

An idea is something with social value and the implementation of that idea as a new act can creates economic value, if that act provides a differential between companies and if it is useful. This process of transformation from social to economic value is known as commodification.

As that activity evolves, the various iterations will individually diffuse through society until the activity becomes commonplace, well understood and its differential benefit reduces to close to zero i.e. what started with a high differential value due to its scarcity ultimately evolves to have little or no differential value because it is commonplace. It has become a commodity and when discussing activities then this process of evolution (see figure 1) is commonly known as commoditisation

Often the two terms are confused but commodification and commoditisation are separate.

Figure 1 - Evolution (aka commoditisation when dealing with activities)

At the same time that an act commoditizes and its differential value declines, it also becomes a necessity and a cost of doing business. For example, the once wonder and differential of a mobile phone has become a cheap necessity for most. This creates a situation where the unit value of something maybe declining as it becomes more common (i.e. less scarce) but the total value is increasing due to volume. This is summarized in Jin Chen’s “Entropy Theory of Value” and the relationship between value and scarcity is provided in Figure 2.

Figure 2 - Total and Unit Value variation with scarcity.

From the figure above, as the act become increasingly more common (moving from left to right along the scarcity axis) then the unit value declines but the total value (volume multiplied by unit value) reaches a maximum before declining. Along with a change in value, we also see the cost of production of each unit reducing with volume. For example, the cost of production per unit for a standard mobile phone is vastly less than the cost of production of the first ever mobile phone. As a result the Transitional phase (the domain of custom built and products) also tends to be associated with the most profitable with the highest total value and declining production costs. In practice, this area of highest profitability tends to extend further than anticipated because the economic value associated with an activity tends to exceed the differential value it actually brings us due to effects such as branding, confusion of choice, poor information and our inability to determine actual value. Even today we tend to view systems such as financial ERP (Enterprise Resource Planning) as providing some form of differential value despite the commonplace use of ERP systems and wide spread copying of customization. Hence we often associate more economic value to ERP than we should i.e. our perceived value often exceeds the actual value something creates. This effect is quite common.

Notwithstanding the issue of perceived vs. actual benefit, the general form of how benefit (e.g. total value minus cost of production) varies with evolution for a new activity is shown figure 3. A similar pattern also occurs with changes that provide operational improvements and are hidden behind the interfaces of standard components.

Figure 3 - Benefit vs Evolution

From the figure above, the genesis of an activity is normally associated with a negative benefit due to the burden of research and development costs, however these are quickly overtaken by rapidly increasing sales volume for a relative high margin product. As the activity evolves the unit value declines along with production costs to achieve a minimum plateau.


Summing the area under the benefit graph can provide us with a total future benefit. Obviously, we have no idea whether a novel activity will succeed but assuming it does succeed and evolves to more of a commodity then we can estimate an anticipated future benefit.  It is anticipated, as the actual future benefit will depend upon the act in question, whether it succeeds, how useful it is, whether it diffuses and crosses the chasm, whether it is substituted by another act, and ignores interference in the market (e.g. intellectual property rights).  The general form of anticipated future benefit vs. certainty is provided in figure 4

Figure 4 - Future Benefit vs Evolution

So for any act, the future benefit grows in the initial stages to a maximum i.e. the impact of research and development reduces. Once this maximum has been reached then the future anticipated benefit has an inverse relationship with certainty and as the act becomes widespread and well defined its future benefit hits a minimal plateau. Alas, for any specific act, since we have no way of peering into the future and those things with high future value are equally those things we are less certain about then gambling is a necessity.  However, since there is a maximum, Fast followers who make custom built examples of the act and then go onto productise it will gain the maximum advantage. In general: -

The Chaotic phase (for activities, genesis of the novel and new) is associated with high costs, high levels of uncertainty but potentially very high future values. Being first is not always the best option though.

The Transitional phase (for the activities, custom built and products) is associated with reducing uncertainty, declining production costs, increasing volumes and highest actual benefit and hence profitability. Whilst the environment has become more predictable, the future anticipated benefit is also in decline. This accelerates, as the activity becomes more commonplace, more defined and more of an expected norm.

The Linear phase (for activities, the domain of commodity and utility services) is associated with high certainty, high levels of predictability, high volumes, low production costs and low unit margin. The activity is not seen as a differential but an expected norm, it has become commonplace. Those activities that have evolved to this state (e.g. nuts and bolts) are seen as having minimal differential value and the perceived future benefit is minimal. However, despite this they also provide a regular and sustainable source of revenue.

If we take these different areas of value and superimpose on a figure showing how evolution enables the rapid development of higher order systems (see figure 5) then we see that the new higher order systems are also associated with highest future benefit whereas the underlying components are associated with minimal future benefit (in terms of differential).

Figure 5 - Evolution, Componentization and Value

As a result, when an activity evolves to more of a commodity we not only see higher levels of efficiency and increased agility in building higher order systems but we also tend to see a flow of capital from past industries to these new industries because they are perceived as the source of future value or wealth. This flow of capital to the “new” is part of the phenomenon that we know as Creative Destruction by Joseph Schumpeter.

The future benefit curve applies equally to differential value with the creation of novel and new things as it does to operational improvements and provision of a more evolved component. However, the fast follower method is more appropriate when we are discussing the creation of something novel and new rather than a more evolved means of providing an existing activity. In the latter case, being a fast follower to a more commodity means of provision has an additional burden in terms of a company’s ability to create and extract benefit from higher order systems.

Figure 6 provides a future benefit curve for both the creation of something novel and new (e.g. computer infrastructure in 1943) and the provision of a more evolved method of providing an existing act (e.g. utility provision of computing infrastructure in 2006).

Figure 6 - Future Benefit and Evolution

From the above, in 2006, the act of using computing infrastructure can be considered as having little or no future benefit in terms of differential value and instead is simply a cost of doing business. The shift towards utility provision in 2006 does provide some operational impact that quickly declines and a maximum benefit is always possible by not being the first to adopt due to the cost associated with changing practices.

However, in the case of utility provision there is also the impact on creating higher order systems (componentisation) to be considered. In other words, being a fast follower for utility provision of computing infrastructure might maximise operational efficiency but it will incur an additional opportunity costs in building higher order systems. In which case, depending upon how widespread the component will be, the act of being a fast follower may prevent a company from being a fast follower in those higher order systems that represent future sources of wealth (see figure 7).

Figure 7 – Impact of Fast Following on higher order systems

From the above, as the activity evolves from a product to utility provision, both consumers and past vendors have inertia to the change.  The more evolved method of provision offers some benefits through operational efficiency and being a fast follower maximises this benefit due to any changing practices associated with the act. However, the more evolved act also enables new higher order systems to form that in turn are new sources of future value. Being a fast follower in implementing the more evolved activity may impact a company’s ability to be a fast follower in implementing these new sources of future wealth.

A general rule of thumb is therefore provided in figure 8. Being a fast follower generally creates the maximum advantage when we’re talking about the genesis of something novel and new (i.e. an act which has not existed before). However, being a first mover can create the maximum advantage when dealing with the evolution of a pre-existing activity from product to utility services due to componentisation effects.

Figure 8 - Evolution and Fast Follower

Ideally a company wants to be a first mover when it comes to commoditisation but a fast follower when it comes to genesis. This is also why ecosystems are incredibly powerful models, as the approach of ILC (innovate-leverage-commoditise) creates a constant position of being a fast follower to genesis (i.e. others innovate, you leverage the ecosystem to spot diffusion) whilst at the same time the act of commoditising means you're a first mover (see figure 9 & 10)

Figure 9 - The ILC model

Figure 10 - Example operation of model

The original question also highlighted why the general use of the term “innovation” to cover multiple things (genesis, feature differentiation, utility provision of an existing act) is so confusing because the answer to  “should you be a fast follower or first mover with innovation” is “both”. 

Ideally, you want to be a fast follower to Genesis but a first mover to Utility provision.

12th August 2015

These days I use the term uncharted for the chaotic phase (the appearance of chaotic like properties is just one of many characteristics for that phase) and industrialised for the linear phase (the appearance of linear like properties is just one of many characteristics for that phase). The chaotic and linear terms (ones I had used since the mid 2000s) didn't amply describe the phases.

I still call the transitional phase ... transitional. It amply describes the "in-between" state.

Thatcher's Legacy

Controversy still surrounds the "not quite" state funeral of Margaret Thatcher. A ComRes poll of 2,012 found strong opposition to state funding with 60% against and 25% for. So, it really isn't that controversial - the public don't want it, the Government isn't listening. Even the Bishop of Grantham (the Iron Lady's home town) has called the funeral a mistake. Unless you're in the midst of a swelling of the rabid right, you're unlikely to find support for it.

The DailyMail (a wet rag of a newspaper more commonly associated with picture book Victoria Secret's exclusives than journalism) continues its "witch hunt against the living whom might speak ill of the dead". Two teachers, a policeman and a student so far. It naturally has forgotten its own disgraceful character assassination of the opposition Leader Michael Foot, two days after his death. Well, it happened in 2010 ... that's like ancient history. The DailyMail, a staunch fighter for press and media freedom, has also been ranting against the BBC for allowing the DingDong song to be played.

Under political and media pressure the bumbling BBC has decided to cut short Judy Garland's song 'Ding Ding the Witch is Dead' in the chart show. According to the DailyMail the failure to censor  the song hands victory to the 'Trots and Loony Left'. Iron Lady supporters have their own anthem with the bizarrely co-opted anti-Thatcher song 'I love Margaret Thatcher'. The BBC has decided not to cut this latter song despite the song's success representing exactly the same sort of political gesturing that some wanted the previous song censored for.

Glenda Jackson has also been castigated by many of the rabid right for speaking her own mind in an attempt to stop Margaret Thatcher's history being re-written. Glenda has received overwhelming public support for this. The DailyMail called her "demented".

Will Hutton has asked a perfectly reasonable set of questions on the legend of the Iron Lady saving Britain and whether all that happened was a set of short-term measures (selling national assets, credit de-regulation) to fuel a debt driven boom. I'm sure shouts of controversy with demands for censorship, persecution and castigation will follow in short order.

... and so it has continued.

Now, we could talk about the economic and political policies of Lady T's reign. Some were fine, others were not. But you have to understand that to some of the right, Lady T was their deity. Hence all the hostility against those who doubt her and the desire to worship such a divisive idol. In their world, you're either a paid up member of the rabid right or you're a demented member of the loony left. There is no shades of grey (oh, and just in case you're in doubt then there are some on the left who are just as equally blinkered of the other side).

So any discussion of Thatcher's legacy is bound to be fraught with trouble. The reality is there was some good and bad, depending upon who you were. The longer term effects were all cultural - the shift towards short-termism, brutal individual self interest and a focus on economic dogma over society. Again, whether you think those are a good or a bad thing will depend upon your perspective.

However these demands for censorship, persecution and castigation for failing to worship a specific groups' idol are disturbing. Though there has been talk of 'pre-emptive' arrests, we haven't stooped so low as to arrest people for 'insufficient sobbing' but that's because we still have some fragments of civil liberties left (bleeding heart liberal that I am).

Expect more name calling, rabid ranting and persecution of the living. 

For whom the bell tolls ...

As a sign of respect for the passing of another life and a probably much loved member of another family, I'll keep this simple. Margaret Thatcher was probably one of the most divisive individuals in UK politics in the last hundred years.

However beyond the hum drum of her refusal to allow sanctions against Apartheid, the labelling of the ANC as a terrorist organisation, the violence brought against miner's and their community, the abolition of free school milk, the poll tax, the decimation of our industrial and manufacturing base, the loosening of credit and financial de-regulation providing the background to today's lamentable financial position, the introduction of monetarist policies and Friedmanism, the support for Pinochet, the privatisation of infrastructural services and natural monopolies, the destruction of our culture, the pursuit of wealth for wealth's sake and the growth of casino capitalism, the erosion of education, the bombing of Libya, the demonisation of teachers, reduced expenditure on social services such as housing, the increasing social tension leading to the riots, significant increases in unemployment, reduction of the power of trade unions, the rise of social problems related to poverty and rapidly declining social mobility, her work as a geopolitical consultant for the tobacco industry ... she didn't do that badly.

Tonight, I'll raise a glass to the Iron Lady for whom the bell has tolled.

The passing of an era.

Why I don't worry about climate change

I used to work in the environmental field back in 1990s. I used to worry a lot about the field, I gave up worrying about it. It wasn't because I didn't believe it's an important issue worthy of study, it is. The consequences are likely to be catastrophic but there's no point worrying about it.

Our technology, economics and nature is full of punctuated equilibriums. Periods of gradual change, followed by a rapid divergence. In technology and economic systems the interplay between evolution of the system and inertia creates this. In this case they create cycles of change that we call ages.

The problem is always with prediction because in this case we can often know why it will happen and what will happen but not when. The when is always imprecise. However that's the problem because the past time (and we are prisoner's of our past experience) will tend to lull us into believing the change will be gradual and things aren't going to suddenly go all crazy on us.

An examination of financial systems, technology and economic systems, biology or nature will tell you that's a false assumption. On a trivial sense, the move towards cloud computing was a highly predictable change in terms of what almost 40 years ago. Companies will still die as a result of this predictable change because they failed to prepare, to move themselves out of the way of the storm. This is an issue of leadership.

I used to work in the financial sector in 2000. I can honestly say that I didn't met a single person who didn't believe a major economic crash was heading our way. Everyone pointed to the excessive debt, the OTC instruments but no-one knew quite when it would all unwind. They all hoped it wasn't going to be on their watch. Higher up the organisations this hope was more denial, everyone was ignoring the issue.

The same can be said with climate change. We knew back in the 1990s of numerous tipping points, we knew that the consequences were likely to be dire and the cycle of change would be rapid. There's plenty of past data for this (just look at ice cores). We could strive to explain the why it would happen (and people do, good for them) in ever more detail but it will almost be impossible to say the when. 

We'll only be able to say the when when the weak signals scream now and by which time the change is upon you.  A decade ago the weak signals of economic collapse were screaming now, people ignored it, we got the collapse and companies went bust. Just less than a decade ago the weak signals of cloud computing were screaming now, those with inertia ignored it, we got cloud and companies are going to go bust. I could ask my friends in the environmental field what are the weak signals screaming but I don't want to know. I already know that they're no longer talking in social circles about when but instead how to survive, so I can guess it's coming soon.

There's no point in knowing because we won't react in the way that we need to until it's upon us. Our leaders have always been too weak to move us away from the storm, trapped by the economic and other systems we have created. Climate change will hit at some point and the population of this world may well be decimated twice over as it has been before. When? Who knows. Even if you model the change (the why and the what) then the when is always going to be imprecise and probabilistic and for that one reason alone, through a tragedy of the commons and our past experience we will do nothing until it is upon us.

If we're really super unbelievably lucky then climate change will somehow turnout to be linear, the models will be wrong or we'll get a lucky break and some novel technology will resolve the problem, well that's what we're going to tell ourselves anyway. Actually we're going to convince ourselves that this is the case until we find out it's not. Maybe we will imprison some scientists for not being right, as if they had any chance. They tell us what they think and we call them alarmist. They give us the more "reasonable responses" that we desire and then we send them to prison when they're wrong. Well it's always more comfortable to point the finger somewhere else.

So climate change will probably hit us, it's impact is likely to be dire, the change is likely to be rapid and no, we don't know when (we will never know precisely when) but you can guess it's not far off - five years, a decade, a few decades, a hundred years - who knows. If I said to you that there's a chance the vast majority of people reading this blog will die as a result of climate change, you would shout alarmist and it won't happen. Nothing has changed since the 1990s except our understanding of how many tipping points there are and how the model works. But we will ignore it or at least pay it lip service until it hits us and so there's no point in worrying about it. No different with how we reacted to the looming financial crash in the early 2000s ... we pretended it wasn't going to happen.

And I suppose that's the point, if something worries you then you should do something to stop it but if you're not going to do anything ... why worry? Instead we could plan for what we should do when it hits us. There's lots of thorny and tough questions that need to be discussed - how many do we think we can save, how many do we need to save, what should we aim for and who gets saved? We might not make a serious effort to prevent the change but at least we can plan for it.

Four Domains of Prediction

This is currently part of a piece of work that I'm writing up on prediction tests but due to a conversation with Florian Otel on the role of actors and the aggregated effects of actors then I thought I'd put up a rough diagram. There appears to be four different domains of prediction (see figure 1)

Figure 1 - The different domains of Prediction

There are the :-

Known (what) Known (when) : these are modeled and predictable trends for both what and when such as the trajectory of a canon ball. The what (i.e. its path) and the when (i.e. where it will be on its path) are predictable to a high degree of certainty. This is not absolute, it never is just that there exists a high degree of certainty. In economics, price elasticity of a mature system or diffusion of an already established product in the market is in this category - you can predict both the effect (the path) and the time.

Known (what) Unknown (when) : these are modelled over what will happen but the when is imprecise and uncertain. You at best have to look for weak signals. The evolution of activities from genesis of the novel and new to commodity is in this category. We can say what is going to happen (hence Parkhill was able to predict the cloud computing industry in 1966) but not when with any precision until we get very close to the time of it happening (e.g. with Cloud computing the last decade). 

In the case of the evolution of business activities, the path is dictated by competition between all actors (consumers and suppliers) and hence the overall trend is predictable, however the shift from one economic domain (such as products) to another (such as utility services) depends upon the actions of a specific actor (i.e. someone setting up a utility service) and this is the unpredictable part. The best you can know is it is more likely to happen now through secondary signals. Much the same way that a military of the past could look for weak signals, such as sailors of the opposing force hanging out their clothes on drying lines to anticipate the opposing forces fleet setting sail.

Unknown (what) Known (when) : these are modelled over when but the precise what is uncertain. For example, the commoditisation of a set of pre-existing activities initiates a "war" in that industry and a punctuated equilibrium when the past is destroyed. If those activities can be components of higher order systems (e.g. computing infrastructure as a component of other systems) then the "war" will result in a time of "wonder" with the rapid creation of new higher order systems and un-modelled data. You can predict when the time of wonder will occur but not what new things are created. Hence with cloud computing the rapid growth of new higher order systems, explosions of un-modelled data (Big Data), the co-evolution of practice (DevOps) and the rise of a Next Generation of company was all predictable in terms of time just not what those things would be in detail.

Unknown (what) Unknown (when) : the genesis of the novel and new is in this category because of its uncertain nature, deviation from the past and its dependency on actors actions. We cannot say what will be created or when it will be created with any precision.

Now these divisions appear fairly permanent because of the underlying mechanics involved. In some case we might mis-treat a change such as treating something as an Unknown Unknown because we do not understand the underlying mechanics e.g. the orbit of the planets before we had any concept of gravity, planetary movement etc. Today, it's more of a Known Known but that is because of the existence of a model of understanding.

In other cases, such as how business activities evolve we have a Known (what) Unknown (when). This is because the Known (what) is driven by competition of all actors but the Unknown (when) depends upon the actions of specific actors. We cannot improve beyond this without somehow predicting the actions of individual actors which as Hayek would have pointed out is not currently possible. Hence at best you have to resort to weak secondary signals i.e. act is suitable for provision in this state, the concept exists, the technology exists, there is a willingness for consumers to adapt due to "grumbles over the cost of the existing model" etc.

The Model of Understanding and Why
That "model of understanding" is our best answer to Why something occurs and the pursuit of science is fundamentally concerned with the shift of this Why from unknown to known, from uncertain to more certain. Hence in the flight of a cannonball we have a pretty good understanding of Why and What and When i.e. you can describe it as Known (why) Known (what) Known (when).

In other cases, such as the evolution of business activities we have pretty reasonable understanding of Why and this gives us a model of What not When. Even if the evidence behind the model develops to a point that we are fairly certain of Why the model works, it will still only give us What not When. Hence we're heading in a direction of Known (why) Known (what) Unknown (when).

You should never assume that scientific pursuits (whether natural sciences or economics) will ultimately give us a Known (why) Known (what) Known (when) for everything because in many cases the mechanics prevent this. For example if they depend upon actions of individual actors then the underlying probabilistic nature simply becomes more pronounced. Our best model of understanding might only ever be Known (what) Unknown (when). 

It's also worth emphasising that we can only ever get to best models of understanding. Even our most cherished scientific theories, which we're usually fairly certain about, are nothing more than best models. When people say they know how this works, they're actually saying we've got a pretty good model of understanding.  It's never absolute, there are no absolutes, there is no absolute truth.  Even the beloved field of mathematics only has trivial truths or ones that we define as being true (See Bertrand Russell's paradox and Goedels' Incompleteness theorem). Known is just a short hand way of saying "a very high degree of confidence that this is correct and we will be really surprised if it isn't."

I also emphasise this point of Why because of a pet dislike of mine within management studies - the use of backward causality and the curse of the case study. The fundamental premise is that if successful company X does Y then by doing Y it would mean that I too will be successful. This is normally presented as a case study of Y from a big and successful company which encourages you to follow suit. In my view the bible of this approach was Tom Peter's "In Search of Excellence".

The problem with this popular approach is that it does nothing to improve our model of understanding, it does not give us the Why and it tell us nothing about where we maybe heading. Many examples of those "Excellent" companies such as Kodak and Polaroid are hardly companies most would aspire to today. Unfortunately, the pursuit of Why is often dismissed as too theoretical, too academic and not practical enough. Well, I'll happily agree that the pursuit is difficult but as for being too academic a pursuit ... no.

It's that lack of understanding Why which will almost certainly be behind the highly probable and unnecessary disruption of once great companies such as HP, Dell, IBM, Oracle and SAP by a predictable market change such as cloud computing. These companies by right of their position should never face disruption by a predictable market change. They should only be disrupted by an unpredictable market change as in product vs product disruption such as cable vs hydraulic excavators due to an unexpected change in the value network.

However people talk about cloud computing as though it was unexpected, it wasn't. The What was known, just the When was imprecise but this could have been planned for a long time in advance and weak signals monitored. The issues of inertia, cultural change and the impacts of changing practice could have been managed well in advance. Disruption in this case was entirely preventable. The most interesting thing about these economic states of "war", the punctuated equilibrium where past companies are destroyed is that these are predictable changes and these companies should not have failed. But fail they do, and in general it appears to be because they do not understand the why. They actually think this an unexpected market change. It isn't. It's simply one they failed to prepare for.

Cloud computing wasn't an Unknown (why) Unknown (what) Unknown (when) i.e. an entirely unpredictable change but instead it was a Known (why) Known (what) Unknown (when). 

Other changes are however unpredictable, we cannot foresee genesis of the novel and new as it is uncertain by nature.  Hence we cannot know that some unpredictable characteristic such as physical size in storage disks will become important. These are cases of the "Innovator's dilemma" where a focus and pre-occupation with existing customers (i.e. our inertia to change) and the unpredictable nature of the change leads to our downfall. But cloud computing is not this.

The probable failure of many of these great companies is due to a predictable change, a preventable disruption combined with the failure of past and in some cases present executives to predict the predictable and plan for it. To put it mildly, many great companies will fail and continue to fail because their executives are out of their depth. They either do not or did not understand the why.

The storm that is cloud computing was foreseeable and was foreseen a long time ago. Companies could have been moved out of its path despite their desire to stay put. This is the role of the CEO and the captain of the ship - to see the storm, to move out of its way and to take advantage of the change. This is the art of strategy. Destruction in this case is lamentable. It's not the employees, it's not the culture, it's not inertia, it's not some random unpredictable change that's to blame but an utter and miserable failure of strategy.

The understanding of Why things change is far from just an academic pursuit.

On Naked Capitalism and the Meme Hustler

Beyond all the vitriol, the essence of the argument put forward by "New York Times guest columnist" Evgeny Morozov in the "Meme Hustler" is that economic and technological development is not the same as the progress of a society. This is a perfectly reasonable point as progress requires some concept of where you are heading whilst economic and technological development are simply a means to an end. 

Unfortunately the author fails to acknowledge that the target of the article Tim O'Reilly has made the same point on numerous occasions in the past with his discussions on what is the system that we are creating. Rather than dealing with this, the article has been selective in its facts to suit its own pursuit of being a source of "truth" and portraying O'Reilly as a ruthless propagandist of commercial and political interests. 

The article, written by an author of a recently published work with their own commercial interest would appear guilty of conducting the very same acts they would accuse others of. It is at the least unwittingly hypocritical. The accusation that it will help Morozov sell a few more books resonates too loudly and is bound to be repeated. 

In 2006, I wrote on my concerns of our continued development of a Stentorocracy (from the greek hero with the big lungs) - a society based upon who shouts loudest - rather than a true meritocracy. If Morozov's article does one thing then it highlights how discussion, debate and enquiry are replaced by shouting, trolling and propaganda and his article is simply part of this rather than the solution. 

I highlighted the quote "New York Times guest columnist" because for me this is akin to the issue of "You can't expect to wield supreme executive power just because some watery tart threw a sword at you". The arguments need to stand on their own merit, the references to credentials as though this provides some authoritative weight has always been at the heart of the problem whether it's the New York Times, The Edge or any other group that professes to be a fountain of truth. 

I would argue that O'Reilly was right to be concerned about what is the system or machine that we are creating and Morozov has clearly pointed out a path which I don't believe we should be heading down. More the pity is the questions Morozov raises are worthy of discussion just not in this manner. Strip out the vitriol and the ad hominem attacks and underneath is the basis of a good and worthy article. How cheaply such discourse and enquiry has been sold.