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Bargaining & Dispute Resolution

Recently, at the Manchester Business School we introduced bargaining as a solutions methodology for use in alternative dispute resolution (ADR). It was the central theme of Day 2 of a three day residential Workshop on the broad theme of ethics and responsibility in business (ERB) a new elective available to all MBAs. The material from Day 2 and the case work reviewed during the Workshop have now being assembled into a Masterclass offering. If you are interested in finding out more about the bargaining process and how it could be adapted for your particular needs then please do contact us on this webpage.

The Conversation

The parties to the dispute need to have ‘a conversation’ so they meet with the arbiter in a neutral location. The approach focuses on an inherent ethic of responsibility as the centre piece of any conversation or dialogue between the conflicting parties. Throughout the conversation the arbiter by observing the parties extracts a latent code of ethics and begins to influence the parties’ belief systems. The approach complements the structural analysis of negotiation recognising the bargaining power of both parties.

Negotiating, however, is a party-specific power-centric approach whereas bargaining is more subtle – it has a power base that rests with the arbiter’s influence over the belief systems’ of the conflicting parties. The premise on which the bargaining approach is built is simple:  that the parties can reach a better outcome – called a bargain – by contracting or bargaining. The methodology is expressed in terms of converging towards a resolution – called a payoff or a bargaining set – in which neither party to the dispute is worse-off.

patrick mcnuttChina2015

Taking Responsibility

The pedagogy is grounded in a Kantian ethic of responsibility – this allows the parties and the arbiter to transform the priorities into a value set of duties so that the dispute can be ascribed by the arbiter to the lack of commitment to one’s duty. Our integrative analysis divides the methodology into ‘off-contract’ or dispute and contract or resolution stages, wherein each stage represents a sub-game. In the off-contract sub-game each party will learn the priorities of the other party and observe a trade-off pattern of conflicting priorities. For example, workers may have a right to a living wage or a minimum wage in many jurisdictions but it is the duty of the employer to pay it. However it is the duty of the employer to pay the wage and by not fulfilling duty, the wage is not paid and an off-contract dispute occurs.

The objective of the conversation is to move the parties to a contract point. Starting from an off-contract point a bargaining set is established which is equivalent to an ADR agreed resolution of a dispute. In theory the set is obtained by moving the parties on to an Edgeworth contract curve. In practice the bargaining process is sequential; it follows a stage-by-stage process moving the parties forward from initial consultation at time period t to final agreement at time period t+1.

Bargaining builds on the conversation. We applied the approach in 2010 to enable senior partners at a leading UK law firm come to an agreement on office relocation and new areas of specialism. Earlier the approach was adopted by the Board of Directors of a payments system company to reach an agreement on allocation of shared capital costs in the roll-out of new payments technology. Like the opening move in chess the off-contract steps follows a sequence:  Step 1: meet with the parties to extract the material facts. Step 2: elicit the duties expected of each party by the other. Step 3: identify the lack of commitment, the off-contract point, around which this dispute occurs. Step 4: assess both the threat values and the opportunity sets available to each party within the contours and parameters of the bargain. Step 5: define the trade-off function in terms of threats v opportunities for each party to the dispute.

The contracting steps have to be choreographed by the arbiter. Central to the bargaining is the payoff-constant trade-off. This is Step 6. It is a critical step. A good example is provided by Caffé Nero’s response to the recent increase in the living wage to £7.20 per hour. They offer to pay the increase but suspend the staff’s entitlement to free lunches At Step 6 the payoff-constant Pareto move for each party is assessed. Step 7: introduces the bargaining set in terms of justifying the payoff-constant move from each party. Step 8: initiates the bargaining process by moving the parties towards an agreed contract position, a unique position, so that no-one party is worse-off post-agreement but one party is better off.

Playing Not to Lose                 

This facilitates bargaining as an inclusive process with a positive focus and an emphasis by all parties on playing not to lose. For example, when Kraft HQ in 20105 signalled a decision on factory closures and job losses at the Dublin plant and at their plant in Bourneville, outside Birmingham, the workers responded by improving productivity to ensure the long term viability of the plants. A deal was agreed. The trades union Unite commented it was a good deal for the remaining workers Once the parties realise that neither party can do better unilaterally than the arbiter’s bargain they have reached a resolution. The arbiter’s bargain is the best they can do given the reaction of the other party. Quintessentially it is a Nash bargaining outcome obtained by the good offices of an arbiter skilled in the reasoning tools of non-cooperative game theory.

Key Take-Away

Participants are introduced to a range of bargaining tools as a form of reasoning that has its roots in non-cooperative game theory. The tools are an aid to reasoning during the conversation as the conflicting parties move towards a dispute resolution or bargain. Duration is a one day attendance at a residential Masterclass. Participants will be introduced to a set of invaluable tools in finding a resolution to a dispute viz. opportunity costs, value net, bargain, payoff-equivalence, Nash equilibrium, indifference trade-off, belief system and payoff-constant Pareto improvement.

Raw War: Google ∧ Apple = 1

Google and Apple are like chess players in a smart game – their war is raw. They are as thran as a pair of cloth galluses. Both players attack: they have developed a cognitive awareness of each other as competitors and like[1] Radar O’Reilly they always know the rival strategy before the rival does. Players ought to know their weakness in a game[2]. Their weakness, paradoxically, is their rivalry. It is rational now for Apple (White) to defend iOS with selected roll-out of iNext smart pawns supporting iCloud to Apple Pay to e-SIM to iCloud Voicemail to MVNO in 2016 and beyond. But with Google (Black) in attack allowing its King’s Knight (Android) to be positioned across the chess board so as to weaken White’s centre pawns both players could be worse-off. Maybe Pushkin[3] had a point in preferring a bad peace to a good quarrel.

In this essay we try to argue that they should lose the competition and collaborate together in a partnership. Both players would be better off. Their individual success lies in the creative technologies and innovations they have created unilaterally. From the recent iPad Pro launch to Google’s voyage into wireless. Their future success, however, in the evolving complex market of artificial intelligence, cyber-genetics and autonomous devices, is mutually interdependent. Maybe Apple will buy Tesla. Maybe Google will navigate successfully the unchartered technical land of the wireless Sirens. Who cares?

Google throws the gauntlet down at every opportunity but Apple remains secretive, playing a Fabian[4] strategy of delay. Apple products can fail: who remembers Newton, Apple’s personal digital assistant? Or who remembers the Pippin game console system? Or the befuddled roll-out of its mapping service? Or that Apple TV does not support 4K? Or that Apple lags behind in the evolving complex market of artificial intelligence, cyber-genetics and autonomous devices. Covertly, Apple may have the upper-hand. Even if Apple does not have the latest device or innovation once it decides to enter a market, any market, competitors find themselves[5] in Apple’s line of fire. Who cares?

Chess Analogy

Apart from investors, twenty-first century consumers, and businesses, care. As the ipso-centric generation[6], we, as our own[7] ‘photographers, broadcasters, cinematographers, chanteuse, matchmaker and funeral director’ do care because of the impact the new innovations and technologies will have on our daily lives and in the creation of new services.

Integrating the narrative of Fred Vogelstein’s book[8] with chess strategy provides an interesting canvass on which to paint the competitive rivalry between Apple and Google. Guided by the brush strokes of non-cooperative game theory we discuss the strategy choices as moves on a chess board, Apple (White) v Google (Black) with Google (Black) as a player on the counterattack since the launch of the first iPhone in 2007. A game where it will be challenging for Apple (White) to hold on to the centre as Google attacks its Queen (iOS) quickly and swiftly, faster than any counterattack from Apple. In the discussion of a best reply for Apple (White) to counteract any perceived weakness in the game we have argued before[9] that Apple as a player should stop defending its pawn line of iPhone-iPad. The recommendation then for Apple in 2013 was to reshape strategy by playing not to lose rather than playing to win – simply, launch a[10] nano-iPhone for $100-150.

Google (Black) is intent on attacking the pawn line. So, what is Apple’s best reply today? The recommendation for Apple playing not to lose today is to acquire or develop wireless. Google (Black) has already moved into wireless, launching ‘Project Fi’ an alliance with Sprint and T-Mobile. Google’s entry into the mobile virtual network space (MVNO) has changed the game dynamics to the very core of the rivalry, the ecosystem iOS v Android.

Alekhine’s defense

The ecosystem is a zero-sum game. It is a game of attack in the style of Alekhine’s defense where Google (Black) attacks Apple’s broad pawn base with Google (Black) allowing its King’s Knight (Android) to be positioned across the chess board so as to weaken White’s centre pawns as Black continues to play vigorously.  It is a game of uncertain technical standards and software development that facilitates the arrival of spherical competitors[11] from anywhere at any time in the game.

What would a playbook look like as Apple (White) defends pawn line of iPhone-iPad against a Google inspired Android alliance with Black allowing its King’s Knight (Android) to weaken White’s centre pawns.  In the ‘I-think-You-think-I-think’ reasoning of non-cooperative game theory we could translate the Apple (White) v Google (Black) game into a payoff matrix with strategy sets S1, S2, S3 and S4. The Google payoffs (S3, S4) are in italics so best to read Table 1 as if you were an Apple executive with (S1, S2) and Google is your near-rival[12] competitor.

Attack is a Dominant Strategy

In the classic game theory of Prisoners’ dilemma both players prefer the outcome (3, 3). However attack is a dominant strategy and if both players behave rationally they will end up at the equilibrium payoff (2, 2). This is happening now in an action-reaction sequence of product launches and software updates toggling towards a point of balance in the game where both players independently of each other decide whether a new product is too geeky for it to be commoditised for the mass-market.

Payoffs (iOS, Android)

Table 1[13]: Attack Strategy for Apple (White) & Google (Black)

  S3: Defend  Android


S4: Attack


S1: Defend iOS


3,3 1,4
S2: Attack with Pawns –




4,1 2,2


The players’ secrecy, for example, in artificial intelligence may be hurting its software development. So we have to ask: are the strategies realistic for 2016? Yes. Apple (White) will (and does) continue to move pawns to centre stage, launching new smart products including the recent iPad Pro and Google (Black) will continue to engage with Nexus smartphones, AI, IoT and MVNO as re-shaping strategy set S4,.

Unbeatable Strategies

The technology game is changing. Early denials by Apple in 2010 on MVNO have changed to signals on trial and camouflage[14] allowing for a more realistic and nuanced interpretation of likely future strategies, so we include e-SIM and iCloud Voicemail in Apple’s S1 strategy set in Table 2 and ask: what if Google (Black) is looking at a payoff column in Table 2 with payoffs (2, 4) and (1, 2) with an S4 attack strategy? Why would Google think like this? Firstly, there have been plausible denials and camouflage from Apple. Also the facts speak for themselves: in the commoditised market like smartphones and tablets Apple is unique and a brand leader commanding 28% of industry profits.

Payoffs (iOS, Android)

Table 2[15] Attack Strategy for Google (Black)

  S3: Defend  Android S4:Attack


S1:Defend iOS

With e-SIM

iCloud Voicemail








S2: Attack with pawns –









It would be rational for Google to believe that Apple would defend with iPhone-iPad pawns under a sustained attack from Google. Or does Apple have MVNO plans but delayed due to the early innovation cycle of MVNO? Probably – Apple filed patents for MVNO IN 2006.

Fabian Strategy

The Fabian delay in roll-out of MVNO would be equivalent to a Fabian strategy of avoiding a frontal attack with a sequence:

Step 1: observe the future of Sprint under Softbank management[16].

Step 2: orient strategy and then

Step 3: attack with a MVNO product offering.

This is a classic OODA feedback loop[17] in play here by Apple (White). This is a rational ‘hold-back’ play by Apple in an evolving smart innovation technology[18] game where its competitor Google (Black) castles queenside and attacks Apple (White) pawns. If Google believes that Apple believes that Google thinks like this then we recommend for Apple to play minimax[19]  strategy in order to minimise the maximum gain of Google in the zero-sum ecosystem game.

If Apple plays minimax it should continue the pawn attack because Google will play maximin in order to secure a second win[20] by forfeiting larger payoffs of 4 for a 2 in smartphones and smart products. Google will attack with S4, for example, a wireless strategy and (1, 2) is the likely outcome. Knowing this, it is rational for Apple (White) to prefer the payoff (3, 3) in Table 2. Apple (White) should not over-extend. It is rational for Apple (White) then to defend iOS now with selected roll-out from iCloud to Apple Pay to e-SIM to iCloud Voicemail to MVNO in 2016 and beyond.

Lose the Competition

Albeit, both players know that if Google (Black) MVNO strategy fails to take off or if Apple (White) is prepared to sacrifice its Queen with open source iOS the game could careen towards the Nash equilibrium. The war as described so vividly by Vogelstein might just result in significantly higher payoffs in the short term but lower long term benefits. When both Apple (White) and Google (Black) realise that[21] in this war ‘the sweetest wine, it’s a witches’ brew’ they should lose the competition and collaborate together in a partnership.

Apple ∨ Google = 0 → Google ∧ Apple = 1

Regulators will catch up and their ‘soft law’ will not only satisfice the demands of the ipso-centric consumers but it will also facilitate the spherical competitors[22] arriving on the scene with new software developments and greater innovations – new businesses and new challenges.  A 2013 cover page[23] in Bloomberg Business Week, featuring Tim Cook, Jonathan Ive and Craig Ferderighi in a photograph had the tag ‘What, Us Worry?’ Yes, we say. Both players have developed a cognitive awareness of each other as competitors and like Radar O’Reilly they always know the rival strategy before the rival does. Know your weakness in a game. Their weakness, paradoxically, is their rivalry. Ultimately, a bad peace is[24] better than a good quarrel. So lose the competition and collaborate together in a partnership.

[1] Radar O’Reilly in the TV series M*A*S*H who always knew what his colonel wanted before the colonel did.

[2] From McNutt, P (2014): Decoding Strategy

[3] Extracted from Alexander Pushkin’s The Captain’s Daughter translated by Robert & Elizabeth Chandler.

[4] This is named after the Roman General Fabius Maximus who delayed decisions for tactical advantage.

[5] Think Roku and Spotify. Check Chanelle Besette’s article ‘Invaders from Cupertino’ in Fortune December 23 2013 Edition.

[6] Read 2012 Blog

[7] Comment from Will Self great article ‘The Book of Jobs’ in Prospect January 2014 pp58-60.

[8] Fred Vogelstein (2013) Dogfight: How Apple and Google Went to War and Started a Revolution

[9] Check Memo to Ms Ahrendts 2013

[10] Think of ‘nano’ in the dimensions of the Moto Razr. Processor speed – think of XiaoMi’s phones in 2014 such as Hongmi IS powered by 1.6GHz quad-core Snapdragon 400 as good as and cheaper than the Samsung S3 1.4GHz quad-core Exynos 4412.  Check WIRED Magazine August 2015 article by Andrew Huang. The ‘sweet point’ on price in order to capture the 6.5b people who do not have smartphones is US $100 or less.

[11] Spherical competitors arrive at any time. Ironically, Apple in 2007 with the iPhone was a spherical competitor to both RIM and Nokia. In 2015, Chinese players like Xiaomi, TenCent, Lenovo, Huawei fit the criteria as does Amazon and Google. Check McNutt Decoding Strategy

[12] As defined in Decoding Strategy as that competitor from the sum of competitors whom you believe is more likely to react first to your move in a game. However, this does not imply that Google necessarily identifies Apple as its near-rival.

[13] For both players attack strictly dominates since 4 > 3 and 2 > 1 and 4 > 3 and 2 > 1.

[14] Check out Business Insider August 2015 on a possible Apple MVNO

[15] In Table 2 attack for Google (Black) strictly dominates since 4 > 3 and 2  > 1.

[16] Softbank is a key investor in Sprint and there may be regulatory hurdles in the US

[17] The OODA loop refers to the military strategy of observe, orient, decide and then act.

[18] SIT games are like games of attrition and fall under combat competition requiring constant defence as in McNutt’s Decoding Strategy

[19] Maximin is more commonly used in non-zero-sum games to describe the strategy which maximises one’s own minimum payoff

[20] The winning move is at the point of second win where the best reply in a zero-sum game to a minimax is the maximin strategy play.

[21] Extracted from the lyrics of Ladybird by Natalie Merchant.

[22] Competitors from anywhere in Decoding Strategy book and also :

[23] Bloomberg Business Week Edition 23-29 September 2013.

[24] Extracted from Alexander Pushkin’s The Captain’s Daughter translated by Robert & Elizabeth Chandler.

Soft Law: Google & The Coffice

The EU regulators should settle the long running case[1] against Google. They should present Google with the opportunity to amend any alleged or putative anti-competitive practices. Markets are evolving eco-systems – contest, combat and scramble market systems[2] – and new markets are created by technology. The challenge for the law is how to handle technology not in terms of the application of black letter competition or antitrust law but in terms of how differences in company treatment can be justified. Technology impacts on existing markets, it creates new commodities, it displaces old commodities, and in some respects a sceptic could begin an economic analysis by disputing the very premise of a market as understood in this case. Is there an alternative?

Frozen Markets

Yes. In the book Political Economy of Law we introduced the concept of a frozen market.  If you are reading this Blog on a laptop or smartphone while sipping coffee conducting business in your favourite coffee house – you are in a ‘coffice’ – half coffee half office[3] facilitated by the smart technology created by Google and myriads of new and evolving companies. As an antitrust practitioner you can recognize a frozen market (empirically) as the market with zero prices, long-run marginal cost converging to zero, scope economies in functionalities, time dependent consumer preferences, aged competition, technology convergence and average fixed costs declining.

A frozen market is a market that evolves as companies like Google, Apple, Amazon, Microsoft, Baidu, Uber, Facebook, Airbnb, LinkedIn, Twitter, Spotify, Symphony inter alia, discover new products, new services, new production and delivery processes. Former beliefs about competing and innovating change as end-user coffice workers demand more and firms risk lagging behind the technology curve. In traditional markets monopolies were transparent and the impact of monopoly power, for example, was defined in terms of alleged higher monopoly prices. However the new architecture of the Internet and cloud computing makes centralised control of services going over IP technology almost impossible. Using IP technology information can quickly reroute around and within specific countries. Regulators will not be able to implement rules on products and services in the evolving frozen markets. EU competition and antitrust law runs the risk of lagging behind technology companies. The treatment of personal data and the owneship of the data is an equally important topic.

Legal Principles to Adapt

Google today, new start-ups tomorrow are companies in a frozen market, companies that evolve from a latent underbelly of technology struggling to meet new challenges and set new standards in a modern evolving economy. In disputing the very premise of a market as understood in antitrust a case could be made that Google is neither an abuse of dominance nor a monopolist case; the perfect ‘frozen’ market does not imply perfect competition – the bedrock of modern antitrust. Rather, Google is a data-driven platform, an information pharaoh facilitating new innovative firms in the sharing economy, start-ups touching every aspect of our daily life. It is the creator of a momentum effect across myriads of multiple goods and services. Start-ups search for growth in an eco-system as we breathe for life with the intensity and frequency of effort and investment to affect our eco-system of life both human and economic. Technology is of the essence. Legal principles are adapting to reflect both the concept of a market as an evolving sharing eco-system but more needs to be done.

Indeed the intricacies and entanglement of engagement that companies face with Google provide a network of unavoidable transaction costs and insurmountable gains and leverage. This allows start-ups to grow exponentially in a technology convergence type of competition where cooperation and joint enterprising is more the norm than competing as frozen markets ‘thaw’ out to create new and unimagined products and services. There appears to be some resistance in the inn of black law antitrust for an alternative definition of a market as an evolving eco-system despite the importance of evolving technology to economic activity and to the innovation process.

Soft law

There is also a need to redefine ‘competitor’ in an era of rapid innovation and technological change. Arguably there is no black letter law directly germane to Google activities in the 21st century nor should there be an unquestioning and unchecked progress of Google and others in the technology market – but every effort should be made to amend, adapt the black letter law to facilitate rather than retard Google and the leveraged industries it has helped to create. Regulators should benchmark Google against a soft law of zero prices, long-run marginal costs converging to zero, economies of scope in functionalities, time dependent consumer preferences, aged competition, technology convergence and average fixed costs declining.

We need a soft law approach to Google. There is a need for further integration of the economics of technology and information markets into antitrust and legal reasoning with less focus and emphasis on competition in the product market and more focus on market systems. In the nineteenth century Alexis de Tocqueville once remarked[4] that ‘only a newspaper can put the same thought at the same time before a thousand readers (p517)’. Today, in the 21st century, Google and the Internet are doing that and, at an alarming speed. Ultimately, in assessing the merits of any case centred on geography, frozen markets and the role of technology, cloud computing and Internet information, law may be as relevant as the colour of the judge’s eyes.

[1] Check

[2] Described in McNutt (2014) Decoding Strategy

[3] Read

[4] Alexis de Tocqueville’s 1841 classic text: Of Democracy in America, vol 1 and 2.

Agincourt 1415: Henry V vS Charles VI

Sunday 25th October 2015 marks the 600th anniversary of the Battle of Agincourt in 1415. It is an interesting battle from the perspective of non-cooperative game theory. It has elements of both imperfect information on how the game is played and incomplete information of player type. The optimal strategy for Henry V or Charles VI depended on what each believed to be the strategy of the other player. In particular, we believe that Henry’s playbook demonstrates a winning strategy with noise the purpose of which is to influence an opponent’s belief system. Noise occurs in a game when an opponent believes that you are going to do X but your real intention is Y. The French believed that the English would retreat. Henry V reinforced that belief. In the early morning of 25th October the English repositioned wooden stakes on the battlefield in full view of the French. Once the French committed resources to an English retreat, Henry V out-manoeuvred the French army by a surprise attack.

The Player’s Type

Some historians argue that the French believed that the English would retreat rather than fight, given the superior numbers in the French army. Also historians can recount that Henry V himself by 1415 had preferred a defensive play.  However, we believe that Henry V in 1415 and his trusted advisers, the Duke of York, Lord Camoy and the knight Thomas Erpingham were early practitioners of modern non-cooperative game theory tactics. They were strategic lateral thinkers[1] in the sense that they realised in 1415 that Agincourt was a zero-sum game and that winning was a function of noise. It created uncertainty.

They facilitated the French in their belief that the English would retreat. Henry knew that the French commanders were prepared to wait for nobles and knights to join the attack and crush the retreating English. Although not at the battle due to illness Charles VI believed that the French could defeat Henry V and historians recount how eager the French nobles wanted to fight the English against the advice of the more experienced and superior French knights. On good intelligence[2], Henry V knew this and allowed the French to continue to believe that they were retreating.

Game Dimension: The Terrain

With a hundred years of war, and a long campaign in France, by 1415, this was a battle that Henry V had to win to solve claims on the French throne and secure the English throne. Henry V was a committed player. In addition, Henry’s knowledge of the field of battle facilitated his strategy. He had marched his army across Northern France as the French had pushed him south and away from the port of Calais. Thomas Erpingham canvassed the terrain and assessed its suitability for cavalry and knights in full plate armour.

Shortly after sunrise Henry knew that he had influenced the French belief system – they prevaricated, they waited for noblemen. Furthermore they believed that Henry believed that the superior French army would defeat the English. So they believed that the English would defend and then retreat. A strip of open land between the woods of Tramecourt and Agincourt was chosen and Henry V deployed his army and made plans to form a battlefield. He initiated the first move according to historians by moving his army forward and re-positioning wooden stakes across the terrain to protect the longbow-men from a French cavalry charge. He was signalling an attack. The French observed this change of tactic but did not advance the cavalry. Historians are puzzled by this.

The Opponent’s Rationality

Choice is rational if it is optimal for some belief that you hold about your opponent’s choice. So it is possible that the belief system of the French, in particular the belief system and choices of Constable Charles d’Albret, the French commander, had been influenced by the English tactics. There are at least three answers to the puzzle from non-cooperative game theory offering some insight into the internal dialogue between the French commanders:

  1. Credible Threat: The French truly believed in an English defence: when they observed English tactics and manoeuvres in the early morning they had all the hallmarks of a defensive play followed by retreat.
  2. Reputational Advantage: The French dismissed an attack: they had a reputational advantage in greater numbers and Charles d’Albret believed that Henry V believed that in an attack the French infantry would have out-numbered the English.
  3. Noise and Uncertainty: Given the significance of 1 and 2 the French behaved like[3] Sisyphus pushing his boulder up the hill – only the boulder grows a little bigger with each delay by the French commanders.

Henry V’s Attack

In the early hours after sunrise the French commanders now believed that the English were retreating. So the French waited. But Henry V believed that the French believed that Henry believed that the French infantry would outnumber them. In retreat Henry V would attack rather than defend the English positions.

The English launched an attack from the flank positions. Surprise entered the game. However, the chosen field of battle was narrow and both English and Welsh archers and longbow-men took the flanks and placed sharp pointed wooden stakes at an angle in front of their archers in order to impale enemy cavalry horses. In addition the battle-field was narrow but recently ploughed land and as it had rained the night before so Henry V knew the significance of a very muddy battlefield.

The French cavalry were more anxious to engage, they were drawn into the battlefield, but as the battle ensued the French cavalry horses were slowed down, their advancing infantry and men at arms could not move forward, knights could not see in their muddied helmets – chaos and disorganisation in a muddy battlefield made it very difficult for French knights to fight in full plate armour. The narrow terrain made it impossible for the French to advance. Once the French army was dragged into the narrow muddy terrain the English archers and knights took victory. The ability of the French knights and cavalry to attack was greatly hampered by the muddy terrain.

Belief Systems

So arguably the most significant factor in deciding the outcome was influencing the belief system of the French, allowing them to believe that victory was inevitable, taking them by surprise and then drawing the enemy into battle on to a muddy field. History shows that the Apache may have displayed similar strategic thinking during the early periods of the American Indian wars of 1840-1870 in sporadic games of cavalry quick response posse groups Vs Apache raiding parties. Using solar signalling and Indian scouts and, with a backdrop of a Civil War, cavalry loss in the early years and the Apache gains could be attributed to intelligence gathering on belief systems. Similarly, Cortes, shortly after landing at Tabasco in the Yucatan peninsula in 1519, allegedly burnt all his boats as a signal to the natives observing from the hilltops of his commitment to stay and fight. They cooperated. In a classic betrayal of trust Cortez defeated the natives.

Henry V’s Playbook

In a game against an opponent that outnumbers you in scale and size, your first opening move should be a signalling move to influence the opponent’s belief system. Surprise provides a competitive advantage. The noise – should it be believed as a credible threat in the game – will confuse your opponent, create uncertainty and allow you seize the second win payoff in your subsequent moves. Regardless of what an opponent does influencing the belief system of your opponent is at least as good as not doing so.  So do it in any game, independent of player size.


We continue to research the second win and some discussion papers are available at for further comment. In our book Decoding Strategy, pp98-99 we discuss a product launch of a gPhone as a signal in 2006 that may have provoked Apple to launch the iPhone2G earlier than planned in 2007. The Apple executives believed the rumours of a rival smartphone so they moved quickly. Early reviews were not favourable and competitors had possesion of a new competing product.  The iPhone is less than 10 years old, but it stumbled in 2007-2009, it stumbled in 2013 with iPhone5C and the Android alliance in 2015 provides a formidable threat

A more intrinsic threat in the data is the commoditisation of the smartphone and the inevitable demand for lower priced full functionality smartphones in the sub-$100 price ranges. Once the Android alliance, Google and Samsung, commit resources to smart devices, smartphones and tablets, Apple could out-manoeuvre their rivals by a surprise attack. A nano-iPhone, for example, was one of our game theory recommendations in 2012 and we believe that it continues to be an optimal play for Apple in a time continuum game with noise wherein players exploit the belief systems of an opponent in order to secure a second win.

[1] Working from the research we could argue that Henry V and his advisers understood that an equilibrium is in a time continuum, requiring good intelligence on player type and intelligence on the game dimension (terrain in this case) and they believed that the French army under Charles VI and his advisers in 1415 were less than fully rational players in the battlefield at Agincourt.

[2] Shakespeare’s Henry V speaks in Act I Scene II of meeting the Dauphin, a messenger from Charles VI.

[3] Sisyphus in Greek mythology was condemned to repeat forever the same meaningless task of pushing a boulder up a mountain, only to see it roll down again. Read Albert Camus’s 1942 philosophical essay The Myth of Sisyphus. Also read Ashlee Vance in Bloomberg Business Week edition October 12 2015 in an article on ‘Smartphone Margins’ where rivals to Apple’s iPhone are compared to Sisyphus.

Wistful Economics

Economics of times past, of Adam Smith and Keynes alas! Has economics become an illusion? Yes. It is an accidental tourist in the political landscape. Economic policy making is[1] ‘but a walking shadow, a poor player that struts and frets his hour upon the stage’ of natural numbers, coupled with policymakers throwing[2] ‘sixes and fives in games of chance’ and ‘as wise folk know the conditions in every country’ – targets and trends, patterns and probabilities. All the policymakers are merely players; they have[3] ‘their exits and their entrances sans teeth, sans eyes, san taste, sans everything’. There are no hard lines of distinction. Deflation may be temporary if capacity is absorbed by the real economy. However, a finite measurable increase in sales (thus, output) cannot be secured by small marginal reductions in price. Some industries are depressed and household balance sheets are insolvent. Ah, there’s husbandry in heaven and ‘a heavy summons lies like lead’ upon[4] the ECB: US dollar strength against the Euro is due to deflation in Europe and deflation in Europe is driving up the US dollar. Policymakers ‘cannot sleep’; with their ‘eyes severe, and beard of formal cut, full of wise saws, and modern instances’ they are actors in a Shakespearean play of infinite length as big data, social media and the Internet of Things transform real lives.

In a deflationary period a mismatch in prices and quantities occurs as companies and consumers both fear to spoil the chance of getting a better price later. This fear in a moment in time creates a short period. Competition breaks down and imperfections – for example, short term working, poverty and inequality, exchange rate volatility, competitive devaluations and lower wages – emerge with lasting impact.

Without China’s continued growth, there is no economy in the world large enough to absorb further contraction in the EU and the US. Only those who believe that economic policy making is akin to a Shakespearean play ‘full of strange oaths’ will enjoy the summer recess. But action is required now if deflation’s short period is to be defeated, best illustrated by the life of the mayfly than that of an elephant. A menu of policies should include a return to managed global exchange rates for a period of time, fiscal stimulus in order to ease domestic debt burdens and a continuation of QE in the EU. Falling prices are little comfort for the indebted householders and unemployed. The policymakers[5] sentence all of us to the sentence: ‘there is to-morrow, and to-morrow, and to-morrow, to the last syllable of recorded time’. It is better to end austerity now than regret doing economics by numbers.

[1] Act V Scene V Macbeth spoken by Macbeth

[2] Chaucer’s Canterbury Tales The Man of Law’s Tale 1st Part 130-134

[3] Act II Scene VII As You Like It spoken by Jaques

[4] Act II Scene I Macbeth as Banquo enters.

[5] Act V Scene V Macbeth spoken by Macbeth

Edited Ethics: Mr ‘Three Eyes’

What you and I need is ethics redefined. Would you sacrifice the life of one man to save five? – check the debate at bit/ly/otfatman. What’s your decision? Your answer will reveal a philosophy, your sense of ethics. .Can we apply a philosophical reasoning to the business world? This is the challenge we set in a new module on ethics and responsibility in business on offer at Manchester Business School in April 2015:

Our focus will be on rationality and reason in ethics with a game theory focus on rational action. We are searching for a ‘tao’ in the epistemology of the ‘rightness’ and the ‘whatness’ of an action by arguing that Rawls’ reflective equilibrium’ is as close to Kant’s categorical imperative in a practical real sense. It also allows us to integrate altruism and fairness into the Prisoner’s dilemma as a counter-weight to selfishness, betrayal and cheating. Philosophers struggle but do indeed offer a common sense method of reasoning about morality, the ‘reasonable person’ approach at a moment in time.

Exploring a Kantian philosophy for ethics in business requires us to differentiate between business ethics as a ‘box-ticking’ exercise and ethics in business; the latter requires an ethical foundation that can be applied. Our arguments span a broad church of contemporary philosophy from a focus on Hume’s emotions and virtue ethics in the writings of Neo-Aristotelians like Martha Nussbaum to Derek Parfit’s philosophy of a non-religion based ethics to the philosophy of Neo-Utilitarians such as Peter Singer.

Hypothetical Case

Defendant: Restaurant owner

Plaintiff: Mr ‘Three Eyes’

Suppose you begin with an ethical judgment that denying service to a person simply because he has ‘three eyes’ unjust, and you proceed to account for this judgment by a principle which says that discrimination based upon nothing other than the ‘number of eyes’ is unjust. Rawls as a neo-Kantian may argue that the ‘number of eyes’ is a morally irrelevant characteristic of the plaintiff. But then suppose you have another morality about the justice of affirmative action. So you think that ‘number of eyes’ is a characteristic of a person that Manchester Business School should take account of in their admissions procedures. If your philosophy of justice is to become a Kantian categorical imperative, you will be forced to negotiate the trade-off between the principle of justice based on discrimination, and the judgement by Manchester to take account of [say] a ‘three eyes’ criterion in their admissions policy.

Kant (if he were alive today) as a Rawlsian would probably argue that there will be a further trade-off between a person’s first-order judgments about justice and the higher order commitments that take the form of Rawls’ principles of justice. Rawls called this a ‘reflective equilibrium’  – the ideal state [sic] ‘in which all of a person’s considered convictions about justice are in harmony with their more abstract principles of justice’. But a greater debate arises if the restaurant owner has a negative right to deny service to Mr ‘Three Eyes’ and the search for a categorical imperative is more challenging when philosophy is extended to a morality that supports a principle of justice that defends an employer’s right (or entitlement) to discriminate based on race, age, colour, religion or that allows someone in need of emergency care to die due to their inability to pay for treatment. A worker has a right to a minimum wage and safe working conditions; however, it is the employer’s duty to pay a wage and ensure safe working conditions. Any conflict gives rise to an ethical dilemma. A dilemma arises when someone is not fulfilling their duty. Would you sacrifice the life of one person to save five?

Further links




Whither the Euro? The Liar’s Paradox

Whither the Euro? The Liar’s Paradox

In Dickens’ Hard Times the character Mr Gradgrind can’t help but speak about Facts to his pupils: ‘Now, what I want is, Facts. Teach these boys and girls nothing but Facts. Facts alone are wanted in life. Plant nothing else, and root out everything else’. As we listen to Mr Draghi, to Mr Carney and to Ms Yellen, as we read the Financial Times or listen to business channels, isn’t it all about the Facts and the numbers? Analyst’s commentary coupled with an over-reliance on Facts and numbers has thrown economic policy making into the lion’s den of semantic incoherence. We forget that the real economy is about losing a job, going bankrupt, losing your home, personal and household debt.

Facts and Numbers:  Relevance of Godel

Sadly, economic policy making has evolved into a game of natural numbers. In addition to semantic incoherence – ‘numbers on the upside’ or  ‘targets below forecasts’ – we would argue that Gödel’s first incompleteness theorem may have a direct relevance to policy makers, warning them of the incompleteness of an economic policy, reliant on numbers alone.  Each time a new policy statement – boosting credit in Southern Europe, changing interest rates or QE – is added as an axiom, there are other true statements that still cannot be proved, even with the new axiom. If an axiom is ever added that makes the system complete, it does so at the cost of making the system inconsistent. His argument shows that any consistent effective formal system that includes enough of the theory of the natural numbers is incomplete: there are true statements expressible in the language of economic theory that still remain unprovable within the EU system of policy signalling. For example, what would happen if QE were introduced by the ECB? Thus the policy problem for ECB and for the EU is that no formal system, reliant on numbers and number predictions, satisfying the hypotheses of the theorem, exists. Instead we have noise and signals.  

Godel’s sentence

Economic policy today is transmitted as number signals into the financial markets. Any decision to change interest rates, for example, will have already been discounted by hyperopic analysts. Mr Draghi like Mr Carney will push the forward guidance to ensure a target natural number is met – an inflation level or a growth rate target. On a quarter-to-quarter comparison, EU growth averages less than 0.5%. It is but a number. The Fed sets an unemployment target number of 7%, however measured, and only when unemployment converges to that number will the Fed signal an interest rate change. However, Godel’s incompleteness continues with the austerity mess, and the game of number predictions.

Waiting for Economics

What has happened to macroeconomics in the hands of bureaucrats and politicians? Once there was a policy mantra, P: ‘low (high) inflation explains currency appreciation (depreciation)’ and ‘low (high) interest rates explain currency depreciation (appreciation)’. The US Fed added QE which contributed to a devaluing US dollar. The ECB has been anxious about the strength of the Euro v US dollar, but the Euro has depreciated against Sterling. Is the interest-rate differential between the US and EU so much greater in natural number counting than that of the EU and UK to explain a depreciating-appreciation Euro. If policy prescriptions, P, each represent examples of the Gödel sentence that each time a new policy statement is added as an axiom, there are other true statements that still cannot be proved. We have the liar’s paradox embedded in economic policy decision making: Nominate a P. ‘P is false’. But it cannot be true for then, as stated, it is false – nor can it be false, for then, it is true.

Signals and Noise

Interest rates and inflation figures are Facts, they are numbers. Natural numbers that are allowed to guide policy – it is a mess. EU faces a deflation trap defined by a long period of low inflation, below a target rate of 2%.  The Economist in its May 24th 2014 edition referred to this period as one of ‘lowflation’. Mr Draghi had signalled in early June 2014 how he intended to tackle the imminent threat of deflation – lower interest rates and a European style QE boosting credit by providing funding to banks on the condition that they lend to business.  Now we await the ECB meeting this week (September 4th). He will be reminded that the economic fundamentals are just numbers. Interest rates, exchange rates and inflation are natural numbers. The EU target inflation is 2%, ECB interest rates are now at 0.15%, falling from 0.25% and the Euro/Sterling rate of exchange fluctuates around 0.7911 and 0.8123. Natural numbers but with a potent impact on policies that directly affect everyday life.

1944-2014: Breton Woods to Brisbane

Did Mr Draghi signal at the Jackson Hole meetings last month that the Eurozone needs a relaxed fiscal and monetary policy? Will we see a signal from the ECB this week towards a purchasing of securitised assets? According to European Commission figures last month (August 2014) Eurozone inflation was at 0.3%, well below the target of 2%. In the real economy, however, bad banks dominate the landscape, unemployment continues to rise and growth remains stagnant. Yet our policy makers remain persuaded by Facts and data and numbers.

A reliance on Facts and numbers will continue to stifle policy making; it will ensure that Europe is at least a decade away from any numbered gains in productivity, any increases in real wages or any increases in growth. There is always hope. But in the reliance on Facts and data there is a great danger for policy makers sailing between the Charybdis of raising interest rates too soon and the Scylla of raising rates too late.

Analysts could be predicting a weakening Euro, strengthening US$ and Sterling as we end 2014. FX analysts will try to predict likely movements in the currencies but currency misalignment still continues. Indeed, in a world of numbers we will continue to ask: whither the Euro and Eurozone economies in an era of stagnant growth? But unless ECB engages with QE, Europe will continue to drift into debt-deflation cycle. Maybe there is hope that at the G20 in Brisbane later this year our policy makers will consider an interim regime of managed exchange rates across the world #tuncnunc to facilitate a return to economics. Earlier discussion on managed exchange rates on


Godel’s Theorem

Gödel’s theorem shows that, in theories that include a small portion of number theory a complete and consistent finite list of axioms can never be created, nor even an infinite list that can be enumerated by analyst’s computer programmes.


 € Appreciates: Low inflation and High Interest Rates

If appreciates expect lower inflation, and high real interest rates

€ Devalues: High Inflation and Low Interest Rates

Low and negative rates of interest € devalues


 € Appreciates: Low inflation and High Interest Rates

If appreciates expect lower inflation, and high real interest rates

Higher unemployment and downward pressure on wages

Internal Member State devaluation


Activist shareholders, Tobin’s q = Marris v

Investors generally over-react to good and bad times. Equity values are now increasing at a decreasing rate across the indexes as investors anticipate corporate earnings and begin to read the signals; many investors extrapolate past share price performance, and using an moving average or charting the trends in the share price are de rigueur in the search for a Fibonacci pattern. Management are in a signalling game with shareholders, especially the activist shareholders who are demanding changes in the execution of strategy. From Pepsi to Apple from Hertz to Red Lobster, activist shareholders are trying to break up companies, demanding change from management. In Chapter 4 of Decoding Strategy we define the activist shareholder as Bayesian – seeing what they want to see at a point in time. As Aristotle observed in Rhetoric it ‘is a matter of putting one’s hearers, who are to decide, into the right frame of mind’.  It becomes a constant exchange between activist shareholders and the management team of the targeted company. Most prominent today is Carl Icahn; he sees a pot of cash in Apple and is urging a share buy-back. The Apple C-suite management team are a player in a game of signalling and they should really engage in positive learning transfer [PLT], by signalling to shareholders how they intend to execute strategy, re-assuring them that further innovation will support a continued rise in the Apple share price.

All shareholders prefer high expected returns but they should also be concerned with the impact of signalling on share price performance.  Signals can be observed at any time: check the business feeds from CNN, cnbc or Bloomberg. Apple at US$554 January 24th 2014 9.37 ET is not the call – rather it is Apple at a sustainable US$800 by end of 2014. And that target price depends has a co-variance matrix that depends on (i) the outcome of market share zero-sum game with Samsung; (ii) Apple’s penetration in China with China Mobile and (iii) the launch of a nano-iPhone. The latter has been a theme of this Blog, notably in an open Memo to Ms Ahrendts: A nano-iPhone launch would signal innovation – the real challenge, however, is not just in the timing of a launch date but the price point. It should be competitively low priced with a volume throughput encroaching demand from low end smartphones across the world. We should be debating the sweet price for an advanced well specified nano-iPhone not the share price of Apple.

Mant of these issues are accommodated within the Marris methodology; for example, failure to re-invest the cash or any signals of lagged innovation can damage the long term value of the company. Bayesian shareholders are attracted to companies like Apple and Red Lobster’s parent company Darden Restaurants. They are unlikely to praise management. But as shareholders they are frustrated. In game theory language, they believe that management are bounded rational or limited in their decision making. A nano-iPhone signal to the market would be a better play for Apple executives now than a share buy-back. New product launch is a classic PLT signal, re-assuring investors that Apple executives are playing to win the game, not playing to lose. In addition, it could relax the constraint imposed by activist shareholders.

And the Marris v – probably better known as Tobin’s q – is a reliable metric in our game theory tool-kit where rational investors are also concerned with how their share portfolio co-varies with the signals in a signalling game. It is the ratio of market value and book value or the replacement cost of the firms’ assets. Combined with other metrics, the Marris v offers a guide to investors: if v > 1 consider a sell and if v < 1 consider a buy. Who didn’t buy ARM at 95p in early 2009? Taking a moving average of v, defined as v if v > v consider a sell and if v < v consider a buy.

Compare Intel v ARM share prices over the past 5 years. The relative high performance of ARM’s share price from less than £1 in early 2009 to £9.80 at 10.44 GMT January 24 2014 reflects management PLT, their innovation and their attack on Intel’s dominance in the chip market and Intel’s lagged response to getting its chips into smartphones and tablets. Intel management were bounded rational. They tried to acquire ARM but antitrust law prohibited the acquisition. Tobin’s q is interchangeable with Marris v. Both rely on market valuations; the Marris v, however, should be understood in terms of PLT. Management’s type, that is, their ability to define the game dimension and their ability to win the game represent an intangible asset in the Marris v. The Marris v by relying on market valuation avoids many of the descriptors of accounting profits wherein high profits often equate with a monopoly position. But it could also be the case that companies with high market shares earn profits not attributable to concentration in the market – they are more efficient and more innovative than their competitors. Observe the share price and the investment commentary but when v < 1 or v < v step back, read the signals, make a judgement call and consider a buy as a long term investment – do not look back and do not regret the decision once made.

Who Owns our Personal Data?

 Who Owns our Personal Data?

Personal information and data stored in the cloud have an inherent high ‘tradable’ value – they facilitate the discovery of patterns.  We trust the providers and processors and distributors of the data, they retrieve our personal data and they can and do use it. Our data is now a tradable asset. But who owns the information? In Chapter 12 of our 2010 book Political Economy of Law we had discussed property rights and consumer e-needs in an Internet era arguing for the integration of the economics of information into legal reasoning. There is a new challenge for the law, relying on ‘material facts at time period t when technology has already taken the market to time period t+T (pp306)’. Google believes that the information it is harvesting is its own by virtue of the harvesting. But you and I, as e-consumers, have claim rights to our personal data. Data exchange has become a transaction and we need to ask: who benefits from the trade in our personal data?

At the recent Midland’s Think Tank in Mullingar, Ireland, I raised this issue in the context of how we could use this market exchange to our advantage in Ireland? A cloud services free trade zone [FTZ] in personal data and data patterns was presented as worthy of consideration.

At the Think Tank a range of interesting presentations were outlined and provided a great platform to showcase the greatest technology advance since the 1980s digital revolution – the Internet and all its applications.  The Internet is part of our daily lives. Not only is it the screen in front of us but also the back infrastructure of wires and machines.  We were told that there is an exponential growth in data and a reliance on data. Individuals are outsourcing memory to smart devices such as smartphones and tablets; we are reliant on pre-authorised smartcards, buying tools and Apps to support basic queries and purchases. SEPA when rolled out will smooth electronic transactions. Companies are migrating from in-house IT to outsourcing data storage.

We have become datified…..

In the June 2013 edition of Foreign Affairs the authors Cukier and Mayer-Schoenberger argued that we have become datified – Google’s augmented-reality glasses datify our gaze, Twitter datifies our thoughts and LinkedIN and Facebook datify our professional and personal networks. Datification, we contend, is a pre-requisite for third parties as they begin to extract an inherent ‘tradable’ value in our data patterns. But who owns the information? Do Google and Facebook, for example, own our data?  The EU Commission in their definition of ‘personal data’ in the Internet era are debating the traditional rules of data protection viz 2014 General Data Protection Regulation. Commissioner for Justice, Viviane Reding, commented recently in Global Insight that ‘personal data is the currency of the digital economy’ and that by 2020 it will account for 8% of EU-27 GDP.

Our data is at least worth the equivalent of 8% of EU-27 GDP before exchange and trading. Tradable personal data is a good example of the frozen market concept introduced in Political Economy of Law. Frozen markets uniquely evolve from ‘a latent underbelly of technology struggling to meet new challenges and set new standards in a modern economy (pp312)’. We should recognise the frozen market and persuade governments to transfer the trade in personal data to a cloud services free trade zone in personal data and data patterns.  With so many start-ups and legacy IT companies in Ireland, there may be an opportunity to bring them all together under one umbrella – a cloud services free trade zone, providing storage solutions, security and surveillance capabilities. The cloud zone could be designed as a ‘special services’ zone similar to the Shannon FTZ.  All IT companies registered would enjoy a 3 -5 year sunset clause of special tax incentives for employing IT staff. Information would be stored and processed into data patterns in the cloud zone. It is only when the data is traded does it become subject to Irish value-added tax or custom duties.

Free Trade Zone in Personal Data…

Mixing a tablespoon of skilled labour with a dose of FTZ is a recipe for baking the projected 8% of EU-27 GDP into an employment cake of highly productive Stakhanovite workers in the age of automation, technology and innovation.

One way to integrate the complexity and potential of the cloud is the organisation of a cloud free trade zone, subject to legal, regulatory and environmental issues. It could be established under an Irish or pan-European variant of the US inspired 2009 Alternative Site Framework [ASF] initiative, by re-organising the Shannon FTZ into an alternative site framework in cloud services spread across ‘magnet sites’ from Mullingar to the Inishowen Peninsula in Donegal. In this the 50th anniversary year of the Shannon FTZ it could be part of planning for the next fifty years of economic growth in Ireland reliant in part on personal data as a tradable asset.  Data security is paramount and our reliance on the data-keepers is dependent on trust and on transparency in their use of our personal data. A cloud services FTZ in personal data could provide both trust and transparency. Questions may arise – do we really own our personal data patterns? Who benefits from any trade in our personal data? Answers should be diverted into exploring options that will create new job opportunities in an Internet age characterised by a shrinking role for human labour.

Memo to Ms Ahrendts


Re: Apple Inc: Play not to lose: Minimax strategy

Dear Ms Ahrendts

Congratulations on your recent appointment. We have been commenting on Apple for a number of years in this Blog, and from the perspective of game theory. You should challenge everything about the data – market share figures, consumer loyalty and the source of the competitive threat. Apple does need to refocus, to reshape its strategy in order to compete in an evolving game that exhibits both convergent technologies and rapidly changing set of consumer preferences. Are you a brand? Are you a design company or an innovator? Analysts look at Apple in terms of profit margins and a company trading on earnings estimates and revision of the estimates. With new product launches across the i-suite of products, coupled with an underlying iOS ecosystem, they look forward to new product launches, and endless queues by early adopters and loyal fans at different cities across the world. But from our perspective, observing Apple as a player in a game, we would adjudge that you are not winning the game.

Confused consumers

First of all, your product offerings are in danger of becoming nodoids: in other words, they come to represent nothing more than a roll-out across a common platform of a suite of not dissimilar products absent any innovation. Consumers are either underwhelmed or disappointed. Once they ask the nodoid question: ‘is an iPhone an iPad or is the iPad an iPhone?’ the game dynamic switches from a game of playing to win to a game of playing not to lose. This is happening. Secondly, the analysts expect the i-Watch – so what? Analysts continue to debate the next big thing. So what? Could it be IPTV or cloud solutions?  So what? You know that you are not in search, you know that you are not in digital mobile advertising, you are a late entrant into cloud services, you failed to acquire Twitter, SIRI failed, Newton failed in the 1990s and in 2013 you allow us to believe that you are not a player in IPTV.

We have argued this before #tuncnunc discussing a range of game solutions to consider: launch a nano iPhone or engage in a telecom alliance with 4G LTE providers such as China Mobile. The 5C launch is about maximising profit margins; a nano offensive play, however, would ignite a $99 ‘sweet price’ competition for full functionality smartphone devices. Forward guidance on the stock estimate above $500 may adjust for these events in 2014-15 but these events may now be too late from a game perspective to play to win the long game. In other words, no longer is it about how Apple is performing in 2013, it should be about Apple’s likely performance in 2023.



Second mover advantage: SMA & Minimax

So an alternative for you to consider in your new role is to secure the second mover advantage [SMA] by playing not to lose. First, recognise that your market shares are increasing at a decreasing rate. Correct that trend. The iPhone 5 delay, for example, created a zero-sum switch to rivals, notably Samsung, in the UK and possibly across the EU. Your smartphone market share is under threat in Asia as the convergent smartphone and tablet game evolves to become Apple’s game to lose. Start thinking like your competitors – reason like this: ‘I think-you think-I-think’: Apple thinks that Samsung expects it to defend the iPhone, so Samsung will attack the iPad. But Samsung believes that Apple will reason this way, and so assuming that Apple will defend the iPad, Samsung will attack the iPhone. But Samsung also knows that Apple will reason this way.

This line of reasoning suggests that some kind of a decision tree ‘what-if’ analysis will reveal which strategy is Apple’s optimal choice. But it is more complex than that – we argue in our new book Decoding Strategy that how either player does in the game depends on what each believes the other is likely to do. Apple has to choose to play a minimax strategy, that is, a strategy that minimizes the maximum amount Samsung can expect to get in the evolving smartphone and tablet game, and thus maximize the amount Apple can expect to win. It is for you to patch a minimax strategy into your strategic vision for 2014 and beyond. To quote T.S.Eliot: ‘What we call the beginning is often the end, and to make an end is to make a beginning, the end is what we start from’. With best wishes in t+1…..