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PREDICTING BEHAVIOUR INTRODUCING ‘GAME ONTOLOGY’ PRESENTATION AT HONG KONG GENERAL CHAMBER OF COMMERCE MARCH 17 2016 PATRICK A. MCNUTT FRSA VISITING FELLOW, MANCHESTER BUSINESS SCHOOL, UK & SMURFIT BUSINESS SCHOOL, DUBLIN, IRELAND. WWW. PATRICKMCNUTT. COM FOLLOW @TUNCNUNC
PREMISE: PREDICTION DEPENDS ON FINDING A PATTERN STEP 1. SEQUENCE 2, 3, 5, 8, 13, 21, 34… FINITE ORDER [STRING] STEP 2. DIGITAL SELF [REPEAT BEHAVIOUR] STEP 3 CODING BINARY 7 = 111 ALPHA-NUMERIC: WORD = 9673
PREMISE: APOPTOSIS [DEFINED FOR A DATA PATTERN IN A GAME] A PROGRAMMED SEQUENCE OF CHOICE EVENTS LEADING TO THE ELIMINATION OF INDIVIDUAL CHOICE PATTERNS AS A FINITE ORDER [STRING] CREATED BY DIGITAL SELF [REPEAT BEHAVIOUR] AND BEHAVIOUR IS CODED B
WHEN YOUR BEHAVIOUR ADAPTS & ADOPTS YOU ARE ENVELOPED BY A GAME UNFOLDS WHEN THERE IS BOTH MUTUAL INTERDEPENDENCE AND RIVAL INTERACTION A RATIONAL INDIVIDUAL (. ) PLAYS THE GAME (WINNING STRATEGY ) OR (. ) OBEYS A RULE (DOES NOT THINK) => ABANDON UNILATERAL DECISION MAKING & AN INHERITED OR ACQUIRED GAME DNA
PREDICTION VS FORECASTING PREDICTION Patterns Repeat Patterns…. due to: Avoid errors & Habit Disbelief in fate Possibility of ‘nudge-averse’ Signals & Semi-structured Data [tweets, newsfeeds] => Patterns and Rules Find the Rule. FORECASTING An ‘odds ratio’ What is the probability of an event? Republican in the White House? € = 1 US$? Noise & Structured Data [sales reports] => Patterns and Beliefs Influence the Belief
AT THE LEVEL OF INDIVIDUAL: FIND THE RULE + INFLUENCE THE BELIEF = DECODING THE PATTERN ‘A BEHAVIOURAL PROCESS, A SEQUENCE OF ACTIONS AND REACTIONS AT TIME PERIOD T WITH CONSEQUENCES AT TIME PERIOD T+1’ LETS TAKE AN EXAMPLE: THE DAILY ROUTINE
PROBABILITY: OBEY THE RULE. IS IT INERTIA OR HABIT? EXAMPLE: DRIVING ON LEFT OR RIGHT SIDE OF ROAD? EXAMPLE: YOUR DAILY ROUTINE
Coffee stop 8. 25 Leave the house 725 am NFC at coffee shop 825 Smartphone Wake Up 7 am Check text messages Social media ‘Latte to go’ NFC payment at 832 am walk to office At office Log in PC 845 Texting, FB and ‘Googling’ the weekend plans. Transit Smartcard at 745 am At desk: 845 am Log On PC, search web. & texting 925 Receive text message confirm lunch 1230 for lunch, CC payment 13. 45 1730 Log off PC; Returning home, smart card 1814; send text; at home by 1855 surf the net, final texts, web browsing. Texting, surfing ‘lights out’ by 23. 55
PROBABILITY: OBEY THE RULE => DON’T THINK => DAILY ROUTINE WHAT IF? POISSON SEQUENCE OF EVENTS WITH EXTERNAL NUDGE [EXAMPLE: A PREFERRED COFFEE-HOUSE] CHAIN OF EVENTS FOLLOW A PATTERN AS A RULE OOOOO
5 0 134 123 925 832 825 7 am
Δ IS THE NUDGE PARAMETER Patterns have a ‘game’ dimension - to make someone do something they would not otherwise do Δ is the nudge parameter. . it is an individual’s change parameter The future is t+1 and if the change from t to t+1 can be framed as a loss/gain it creates a change (loss) aversion effect. Individuals learn from observing the behaviour of others. Individuals also learn from private information …I thinkyou think-I think loop
DAILY ROUTINE ALGORITHM
PROBABILITY: OBEY THE RULE => DON’T THINK => DAILY ROUTINE WHAT IF? POISSON SEQUENCE OF EVENTS WITH BESPOKE NUDGES [SPECIFIC COFFEEHOUSE] CHAIN OF EVENTS: INFLUENCE OR NUDGE THE PATTERN
E DG NU 845 E DG NU 745 725 0 5 134 123 925 832 825 7 am
POISSON SEQUENCE 1. YOU AND YOUR FRIEND’S DAILY ROUTINE ARE INDEPENDENT EVENTS. 2. YOU ARE [EXTERNALLY] ‘NUDGED’ TOWARDS COSTA. 3. YOUR FRIEND PHONES YOU FOR LUNCH TOMORROW, YOU PERSUADE HER TO GO TO COSTA. SHE GOES TO COSTA. 4. YOU AND YOUR FRIEND’S DAILY ROUTINE ARE NOW CO-DEPENDENT EVENTS.
DG E 845 DG E NU NU 745 725 134 5 123 0 925 832 825 7 am
SELF AS A PLAYER IN A GAME Information is embedded in observed behaviour Bt during the time continuum from t to t+1. . may be due to inertia or habit. Bt+1 = Bt + Δ Δ is the nudge parameter that policy makers, management, algorithms and strategists can influence. RANDOMNESS-(NUDGE)-PATTERN-(CODE)SEQUENCE-PREDICTION
PROBABILITY: OBEY THE RULE (DON’T THINK) = BEHAVIOUR CODED WITH A NUDGE 1 = COSTA, 0 = NO COSTA (SBUX) 11010100011 6, 5, 2, 4, 3 BECOMES (14 DAYS): 1111110000 7, 7, 0, 6, 0 (14 DAYS):
11111010110001101000 7, 6, 5, 4, 3, 2, 1, 0
NUDGE…… …. NUDGE…… ……. NUDGE PREDICTABLE BEHAVIOUR
DAILY ROUTINE ALGORITHM
A PATTERN EVOLVES FROM MONDAY, TUESDAY, WEDNESDAY, THURSDAY… THEN FUNNEL INTO FRIDAY? CAN WE PREDICT FRIDAY? PATTERN EVOLVES WEEK 1, WEEK 2, WEEK 3. . THEN FUNNEL INTO WEEK 4? CAN WE PREDICT WEEK 4?
NUDGE…… …. NUDGE…… ……. NUDGE PREDICTABLE BEHAVIOUR
FIND THE PATTERN: WHY? IT IS THE COGNITIVE KEY THAT DECODES BEHAVIOUR BT+1 = BT + Δ IN THE DAILY ROUTINE WE HAVE PRE-8. 25 A. M IN BUSINESS ALSO FIND THE PATTERN IN SONY VS MICROSOFT WE HAVE PRE-2004
PATTERN – 2000 -2006 PS 2 launched at $299 PS 2 at $199. 99 PS 2 at $179. 99 14 May 02 13 May 03 26 Oct 00 PS 2 at $149. 99 11 May 04 100 million PS 2 shipped Announcement PS 3 production schedule to ship 6 million units by 31 Mar 07 at $499 PS 2 at $129. 99 20 April 06 1 Nov 05 8 May 06 15 Nov 01 15 May 02 14 May 03 29 Mar 04 22 million Xbox shipped Microsoft Xbox launched at $299 Xbox at $199 30 Oct 05 Xbox at $179 Xbox at $149 22 Nov 05 6 Feb 06 27 April 06 Xbox at $179 Xbox 360 launched at $399 Revised production schedule for Xbox 360 to 5 - 5. 5 million units by 30 th June 2006
OCTOBER 2000 – MAY 2004 OBSERVABLE PATTERN EX-POST 299. . 199. . 179. . 149. 99. . 149 OPENING SYMMETRIC MOVE……. …………. . 50% PRICE DECREASE REPEATED IN 2010 AND 2015
Cognitive Business Strategy Cognitive dissonance: Why strategy does not work? Who is to blame? More leaps than steps LG Prada smartphone 2006 Yoghurt shampoo
DECODING STRATEGY Decode Bt behaviour Untangle the type tapestry in The Daily Routine as consumers outsource memory and leave smart ‘breadcrumbs’ or smart ‘footprints’. Audience/Group or Consumer Inertia Audience/Group or Consumer Habit
BUSINESS STRATEGY EXAMPLES If Δ is inertia: => Sunk-cost investment Nudge-averse Strategy ‘what-if? ’ is to move before a competitor Δ = price promotion [income response].
Cognitive Business Strategy Cognitive association: Why doesn’t it work? What should I change to make it work? Less leaps more steps Apple i. Phone 2007 Faber-Castell Smart Pencil
BUSINESS STRATEGY EXAMPLES If Δ is habit: => Network or group effects Situation-specific Strategy ‘if-then’ is to facilitate consumer’s choice Δ = stripy toothpaste [asset response]
SIGNAL/NOISE RATIO SIGNAL/NOISE > 1 [FIND THE RULE] CONSUMERS ARE NUDGE-AVERSE (DO NOT LAUNCH A NEW PRODUCT) NUDGE STRATEGY [YOU CAN INFLUENCE BELIEF] SIGNAL/NOISE < 1 CONSUMERS ARE NOT NUDGE-AVERSE (LAUNCH A NEW PRODUCT)
SIGNAL/NOISE < 1 IN A TIME CONTINUUM Engage with consumers: don’t underestimate future gains in t+1: When individuals are asked to choose between a piece of fruit and an unhealthy snack for a meal tomorrow, the choice is influenced by (i) the preference today; (ii) observing others as a norm.
WITH SIGNALING EVERYTHING IS CHANGING What should I do? With all the chaotic information available ‘what you are’ and ‘who you are’ defines your Daily Routine and converts it into information = a valuable tradable asset, so Stop and Think. Know Your Pattern Observe but do not judge.
PROBLEM: HOW TO BRING A 5 FEET LONG FISHING ROD ONTO A LONDON BUS REGULATION HEIGHT = 4 FEET SOLUTION: FIND A WOODEN BOX OF DIMENSIONS 3 X 4 INSERT ROD ACROSS THE DIAGONAL BRING BOX ON BOARD THE BUS WITH ROD INSIDE THE BOX
Game Ontology At 7 am the choice is between: sunglasses or an umbrella? Game theory is observational. People filter signals and would act or behave accordingly. But what if an external influence could be introduced into the filtering process? The purpose is to nudge behaviour. In 1950 s there was subliminal advertising and in 2016 there are smart nudges – cognitive business strategy. The pattern is a repeated action but what is the action? Is it voluntary or habit? What is the metaphysics behind an action or the philosophy of conduct? An answer requires the receipt of intelligence, the appreciation of the situation, the invocation of principles, the planning, the execution of the action and the excuse provided for not doing an action at a moment in time.
Poisson sequence: Suppose the coffee house already knows by decoding patterns that on average 60 customers walk by 12301330 each day => one customer arrives per minute. In order to find the probability that exactly two customers arrive in a given one-minute time interval between 1230 -1330: Let µ = 1 and x = 2: P(2) =e-1/2!=0. 3679÷ 2 = 0. 1839 The number of times a smart card is used at 1230 -1330 has an average rate of 10 times per hour then the coffee house would like to know (i) the probability no more than 10 times occur at the 1 hour lunchtime break and (ii) more importantly, the probability that the number of times will exceed 10 during the 1 hour lunch break: P(x≤ 10) = Σ 10 i · e-10 ÷ i! = 0. 58 (i = 0…. 10)
THANK YOU FOR LISTENING……… ‘Habit is a great deadner’ Samuel Beckett Waiting for Godot Act II