2019/10/06

10 Rules of Simplicity by Edward deBono

Edward DeBono is the world's leading "Lateral Thinker". An adjacent stream of work is "Simplicity". The rules still and even more so apply today
Rule 1. You need to put a very high value on simplicity.

Rule 2. You must be determined to seek simplicity.


Rule 3. You need to understand the matter very well.


Rule 4. You need to design alternatives and possibilities.


Rule 5. You need to challenge and discard existing elements.


Rule 6. You need to be prepared to start over again.


Rule 7. You need to use concepts.


Rule 8. You may need to break things down into smaller units.


Rule 9. You need to be prepared to trade off other values for simplicity.


Rule 10. You need to know for whose sake the simplicity is being designed.

My personal values as a business leader: honesty, clarity, simplicity


Sometimes I feel it is important to think about your set of values and revisit them once in a while by asking :


1. were these the right values for me ?

2. were these the right values for my peers, direct reports and managers?
3. if not what values should be replaced with what values?


Over the years, these values worked for me personally: 


1. Honesty

2. Clarity
3. Simplicity


1. Honesty

- Walk the talk as a leader
- do not have hidden agendas
antonyms: lying and hiding

2. Clarity

- provide a clear vision
- communicate where we stand
- be open with feedback
- always communicate concisely
antonyms:  ambiguity and obfuscation

3. Simplicity

- make things simple for customers, employees, stakeholders
- delegate and decentralize because big things move slowly and complacently
antonyms: complexity, complication, excuses

What are Management Heuristics ?

This is my very own definition of management heuristics

A management heuristic is a method by which managers try to come up with a solution based on cognitive short-cuts, rules and frameworks they have made up through past personal experience and inductive reasoning.


Examples are



  • "it is never good to be first mover in the market"
  • "trust your guts"
  • "I always talk to a couple of potential customers before I invest."
  • "you need to have strategic clarity as opposed to strategic ambiguity"
  • "You either become become Number 1 or 2 in the market" 
  • "New businesses should be profitable in year 3" 



Interesting questions to explore are.

1. what are the leading management heuristics ?
2. how are they formed ? what are antecedents?
3. are they helpful when it comes to managerial decision making in executive boards?
4. how important are they ?
5. how are they changing over time ? how and by what processes are they revisited?
6. how do they delineate against biases ?

Note: Oct 7th.
On particular bias that needs be removed is the Halo-Effect (opposite is the Horn Effect). It basically amplifies the positive attitude one has towards a brand/product regarding a distinct related brand/product. An example for a halo-effect would be: 
Apple cars must be of great quality ! 

Note: Oct 8th 
Path dependence, is a related concept . It explains how the set of decisions one faces for any given circumstance is limited by the decisions one has made in the past or by the events that one has experienced, even though past circumstances may no longer be relevant.

2019/08/21

Lateral Thinking in the movie Mindhunter


Holden: “So what are you teaching?”

Wendy: “I am teaching a class on the intersection of sociopathy and fame. People like Andy Warhol, Jim Morrison.. their celebrity becomes the only thing they need to sustain their ego.”

Bill: “Nixon was a sociopath”

Wendy: “Very similar.”

Holden: “How do you become president of the United States if you are a sociopath?”

Wendy: “The question is how do you get to be president of the United States if you are not?“


2019/06/26

Six Hats of Lateral Thinking by deBono

DeBono offers a very simple framework of applying lateral thinking to any problem
It is called the six hats thinking method


Blue 
- control
- process
- summarize
- overview
- conclusions

Green 
- creative thinking
- search alternatives
- PO : Provocative operations

Yellow 
- thinking positive
- constructive
- value / benefit

Red 
- Feelings/ emotions
1.Ordinary emotions:
2. complex judgements (intuition, sense, taste)

White 
- neutral
- objective
- facts
- figures

Black 
- caution
- risk
- should we follow





2019/06/06

Some Thoughts about new venture inspirations




Lateral Thinking 
Deliberate Creative out-of-the-box thinking by deBono focusing on possibilities and creative stimulus


Design Thinking 
Observe customers, understand needs and pain points. Define the problem. Come up with a solution


Duplication 
Observe successful business models that work in other industries and apply to your own


Pretotyping 
Have a Market Engagement Hypothesis but then go out and pretotype yourself by removing false positives one by one through 'skin in the game' experiments


Cloning 
Clone a successful model from another market and hope it works out here


Janitoring 
Do something which actually no one wants to do and is willing to pay a premium



Some quick notes on Lateral Thinking



How to escape existing patterns


1. Accident (by chance)
2. by Mistake
3. Humour (DeBono on Humour: Humour is on the most significant characteristics of the mind. )
4. Lateral Thinking

Humour is an asymmetric patterning system

Lateral Thinking
  • use 'movement ' instead of judgement 
  • PO (provocative operation) is a movement value 
    • Provocation: you can say something which is stupid 
  • idea is a stepping stone 
  • take something that we take for granted and escape from it 
  • come in from a random point 
  • Intelligence is like the horsepower of the car. Thinking is like the skill of the driver 

Vertical Thinking vs. Lateral Thinking 

  • towards a solution  vs. one moves for the sake of moving 
  • design experiment to show an effect vs. design experiment to provide an opportunity to change one's ideas 
  • some direction vs. without direction 
  • I know what I am looking for vs. I am looking but I won't know what I am looking for until I have found it 
  • analytical vs. provocative 
  • sequential vs. can make jumps 
  • selection by exclusion vs. welcomes outside influence for provocative influence 
  • fixed categories and labels vs. labels change 
  • most likey paths vs. explore least likely. 

Insights is brought about by alternations in pattern sequence brought about by provocative stimulation and lateral thinking provides such stimulation 



Pattern 
is the arrangement of information on the memory surface that is the mind 


Problem 
is simply the difference of what one has and what one wants 
1. avoiding something 
2. getting something 
3. getting rid of something 


Lateral Thinking Techniques 

Fractionation - very similar to Brainstorming

Reverse Method - basically revert your assumptions and see what other perspectives it brings

Example for Reverse method

Going on Holiday 


  • Holiday goes on ... maybe take one day of permantently ? Holiday is not a temporary thing but something which happens permanently in the mind 
  • Holiday One, mabybe together, as a family ? 
  • Holiday with uniformity of surroundings 
  • etc. 

Jesus lives 
  • Jesus is dead .. maybe for me personally in my life, so that I should reconsider my relation to Jesus 
  • Life is Jesus 
  • Jesus death ... makes me think of the cross and resurrection 
  • Jesus not live .. maybe we should do live music worship 


Random Stimulus 

the word is Holiday, now use a random word as a PO https://randomword.com/
  • Holiday PO bee --> maybe a holiday in the nature with a beekeeper 
  • Holiday PO  noctiflorous (flowering at night)







Some quick notes on PRETOTYPING

Notes from the Right-It by Alberto Savoia 
  • Avoid groupthink. Actually this is one reason why big corporations only seldom succeed especially if ideas come from your boss 
  • Hyperzoom: from Market Engagement hypothesis (e.g. Sleeptech will be the next big thing ) to XYZ hypothesis like 3% of male middle managers between 30 to 49 will by an electronic gadget such as Oura Ring to improve sleep quality. 
  • Get YODA (your own data) as opposed to OPD (other people's opinion) from THOUGHTLAND.  Remember: opinions are biased judgements 
  • YODA should have Skin in the game and not "will you buy it". Willingness to buy is the greatest sin of marketing research in my opinion. 


Law of Market Failure 
  • Punch 1 Most new products will fail in the market 
  • Punch 2 They will fail even if competently executed (about 80%) 

Flop Formula 
1. Failure due to launch (marketing) 
2. Operations 
3. Premis (no one cares) 

Make sure you build the right it before you build it right 

Right it = an idea for a new product that if competently executed 

Most Market Research is Thoughtland 
  • Lost in Translation ( an idea is an abstraction) 
  • Prediction problem (users will not know whether they will really use it) 
  • Skin in the game 
  • Confirmation Bias problem 

Data beats opinion 
  • relevant 
  • fresh 
  • your own 
  • significant --> look at p-value . As rule of thumb to 3-5 experiments 
MEH marketing engagement hypothesis identifies your key belief or assumption about how the market will engage with the idea 
XYZ Hypothesis "At least X% of Y will Z" 

2018/04/22

How to calculate LTV of a mobile App - easily and quickly



Step 1

Start with rough data
Day 1 Retention 32%
Day 30 Retention 11%

Step 2

Add diagram



Step 3

Add trendline





Step 4
Add formula and adjust for “potential”




Use resulting formula for calculating each day from day 1 to day 180 (for instance). Of course you can prolong the time period you are looking at 

Then multiply ARPDAU x number of days = LTV (Life time value)

2017/08/27

List of Management Theories

This is a list of academic management theories which I find worth mentioning.
(work in progress)


Strategy
  • Porter 5 Forces 
  • BCG Matrix 
  • Cost vs. Value Leadership 
  • Resource-based view of the firm 
  • Dynamic Capabilities 
  • Strategic Ambiguity vs. Strategic Clarity 
  • Strategic Renewal 
  • Coopetition Theory
Management Theories 
  • Scientific Management - Frederick Taylor 
  • Adminstrative Management Theory - H. Fayol 
  • Burocratic Management - Max Weber 
  • Behavioural Theory of Management - Elton Mayo 
  • Chaos Theory 
  • Systems Management 
  • Evolutionary Theory 
  • Stakeholder Management 
  • Contingency Theory 
  • Principal Agent Theory 
  • The Concept of Coopetition 
  • Knowledge Management - Nonaka 
  • Shareholder Value Management 
Organizational Behavior 
  • Missionary Organization 
  • Theory Z Organization 
  • Holographic vs. Ideographic Organizations
Motivation 
  • Maslow 
  • Mintzberg 

Innovation / Business Model 
  • Creative Destruction - Schumpeter 
  • Disruptive Innovation - Christensen 
  • BMI Canvas 
  • Explorative vs. Exploitative Innovation 
  • Pretotyping

Product Development / Operations 
  • SCRUM and Agile Development/Agile Manifesto 
  • Kanban 
  • Lean Management 
  • Complexity Management 

Leadership 
  • Transactional vs. Transformational Leadership 
  • Efficiency vs. Effectiveness - Drucker 
  • Upper Echelons Theory 
Management & Sociology 
  • Social Network Theory - Granovetter 
  • Network Effects 
Group Dynamics 
  • Irrational Exuberance 
  • Nash Equilibrium 
Group Psychology
  • Social Exchange Theory 
  • Social Interdependence Theory 
  • Social Identity Theory - Tajfel/Turner 
  • Social Comparison Theory - Festinger 
  • Competition & Collaboration - Morton Deutsch 
  • Group Think 








2017/08/20

reflective vs. formative models



Reflective Model 

Items <-- Construct 

e.g.
Construct: Drunkeness 

- uncoordinated walking 
- glossy eyes 
- vomiting 
(items are related) 


Formative  Model 

Items --> Construct 

- Beer 10 liter 
- Vodka 1 liter
- Wine 1 liter 
(unrelated )

Therefore, formative measures define, produce, or cause the construct rather than vice versa !

2017/06/17

Basic Statistical Concepts

data 
nominal - male vs. female/  frequencies , percentages (non-parametric)
ordinal - e.g. Likert scale / first,second, third (non-parametric)
interval - discrete, parametric , continuous (eg temperature)
Ratio level - usually interval data, zero point reflects absence of characteristic

Discrete - adult/ non adult 

Continuous - angry to super angry 

Test Statistic = Systematic Variance / Unsystematic variance

We are comparing the amount of variance created by an experimental effect against the amount of variance due to random factors (such as differences in motivation, or intelligence)

t-value 

what is the probability that our samples are from the same population . You basically compare the means of two or more samples
it is a measure of unsystematic variance or variance not caused by the experiment

r-value (Effect Size)

is simply an objective and standardized measure of the magnitude of the observed effect. 
Pearson Correlation Coefficient
r = .1 (weak effect) 1% of variance between variables is explained
r = .3 (medium effect). 9% of variance between variables is explained
r = .5 (strong effect) 25% of variance is explained

p-value 

Significance - Chance of Error (being wrong), in other words the chance of a finding being due ot error
The chance of the null hypothesis to be rejected where it is actually true.
in Business this is accepted

p < .05


z-value 

are standard scores. it states the position of a raw score in relation to the mean of the distribution, using the standard deviation as the unit of measurement
z = raw score - mean / standard deviation

Standard Error 

the  standard deviation (or variability) of sample means. The higher the SE, the more the sample means differ from each other
The lower it is the more it accurately reflects the entire population


Mean: Sum / n

Median: right in the middle of samples
Mode: the most occuring

Standard Deviation 

Average distance of the values from the mean

Variance Extracted 

Summary measure of convergence among a set of items representing a latent construct.
It is the average % of variation explained among items



Type 1 Error (False Positive) 

Accepting effects that are in reality untrue

Type 2 Error (False Negative) 

Rejecting effc├ęcts that are in reality true



Construct Validity (relationship betweeb measurement instrument and the construct)

Discriminant, Convergent, nomological validity

Discriminant Validity

Eg how good do the items of the construct of innovation differentiate from frome the construct of strategic validity

Convergent Validity

How good are the items for the innovation construct converging ?
If they do not converge the are likely not measuring the same phenomenon
- Cronbach Alpha, cut-off value > .70
- Composite reliability, cut-off value > .60
- AVE Average variance extracted, cut-off value AVE > .50
(AVE = average squared factor loading)

Indicator reliability / validity

- significant factor loadings of items >.70, t-values > 1.645

Multicollinearity

phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can be linearly predicted from the others with a substantial degree of accuracy

Solution:

Variance inflation factors (VIF) measure how much the variance of the estimated regression coefficients are inflated as compared to when the predictor variables are not linearly related.
Use to describe how much multicollinearity (correlation between predictors) exists in a regression analysis. Multicollinearity is problematic because it can increase the variance of the regression coefficients, making them unstable and difficult to interpret.


Parametric Tests 
Kolmogorov Smirnov Test 
if p > .05 distribution is probably normal 

Levene Test 

tests hypothesis that variances of two samples are equal
if p > .05 variances are more or less equal 

Anova 

Main Effect 
A “main effect” is the effect of one of your independent variables on the dependent variable, ignoring the effects of all other independent variables

Interaction Effect

A statistical interaction occurs when the effect of one independent variable on the dependent variable changes depending on the level of another independent variable



Independent T-Test of two samples 


Taken from https://statistics.laerd.com/statistical-guides/independent-t-test-statistical-guide.php

Independent t-test for two samples

Introduction

The independent t-test, also called the two sample t-test, independent-samples t-test or student's t-test, is an inferential statistical test that determines whether there is a statistically significant difference (variance in means for instance) between the means in two unrelated groups.

Null and alternative hypotheses for the independent t-test

The null hypothesis for the independent t-test is that the population means from the two unrelated groups are equal:
H0: u1 = u2
In most cases, we are looking to see if we can show that we can reject the null hypothesis and accept the alternative hypothesis, which is that the population means are not equal:
HA: u1 ≠ u2
To do this, we need to set a significance level (also called alpha) that allows us to either reject or accept the alternative hypothesis. Most commonly, this value is set at 0.05.

The concept of falsification is based on Popper's falsification theory. You cannot know scientific laws with absolute certainty. you can only falsify them --> Null hypothesis 



2017/05/15

Cycle time, Velocity, Lead time

Definitions 

In Scrum, velocity is pretty much the same as cycle time.

Velocity measures what a development team is able to deliver in terms of developed product backlog items within a sprint.

From this blog https://leanandkanban.wordpress.com/2009/04/18/lead-time-vs-cycle-time/ I got this nice definition


Lead time clock starts when the request is made and ends at delivery. Cycle time clock starts when work begins on the request and ends when the item is ready for delivery. Cycle time is a more mechanical measure of process capability. Lead time is what the customer sees.
Lead time depends on cycle time, but also depends on your willingness to keep a backlog, the customer’s patience, and the customer’s readiness for delivery.
Another way to think about it is: cycle time measures the completion rate, lead time measures the arrival rate. A producer has limited strategies to influence lead time. One is pricing (managing the arrival rate), another is managing cycle time (completing work faster/slower than the arrival rate).

Model 
Sprint Retrospectives do increase velocity over time. Knowledge, insights are shared which leads to team learning which affects the velocity in a positive manner.
Hence, retrospectives act as a moderator between developing software and output.






2015/12/28

Which KPI's should I focus on after a mobile app launch ?

These are some additional "quick&dirty" ideas around the question: What are the KPI's that I should take a look at after launching a mobile app (free-to-play in particular. btw, see article below on "Key Metrics for App Monetization." and "Healthy Retention Rates".


(free pic under CC)

1. Rolling Retention

In my short article on "Healthy Retention Rates", I primarily focused on rolling retention. This is: Take a look at a cohort and track their life time. Averaging this figure gives you the average life time.

2. DAU Frequency Retention
By that I mean a methodology which takes a snapshot from one specific day and takes a look at that daily cohort by measuring how many of those that have been active today have been active on a daily basis over the past 7 days. This also gives you an indication of recency. I have seen top mobile games achieve a 70% DAU Frequency retention. In other words, of that daily logged in users, 70% had logged each day for the past 5 out of 7 days! Of course, the DAU basis should be reduced by the number of new daily logins, so that you really have only loyal DAU.

3. Predictive LTV and Milestone Tracking

Define Milestones which could give you an indication as to whether your mobile game will succeed or not.
These two findings are from Tapjoys research on "predicting the future LTV of your your users."
  • "Reaching a critical point of 1,000 users who make > 3 purchases is a good indication that an app will ultimately top $1MM in revenue. 84% of the apps with 1,000 or more users who completed three or more in-app purchases within the first 90 days broke that $1MM threshold.
  • 35% conversion rate from 1st to 3rd purchase was the critical number for breaking the $1MM revenue threshold."
4. Recalibrate your own benchmarks constantly. 

I previously mentioned that D1 (40%), D7 (20%) and D30 (10%) is a good Western benchmark for midcore games. In my experience, East-Asians take a a different approach, which is  slightly more short term on this. I remember one Japanese executive mention the following retention rates as successful.

D1 > 50%
D3 25-30% !
D7 ~ 20%

In his talk, he stressed D3 which seems to empirically work for him to predict if a game is successful or not.

Anyway, these are just preliminary thoughts. Please comment below for further exchange.




2015/12/23

How to compute a doubling with percentages

What does it mean when someone says: We are going to grow revenues

14% every year ? 

10% every year ?

5% every year ?

There is a very simple trick that allows you to quickly translate it in terms of doubling.


(free pic under CC)


Just take 70 and divide by the percentage number:


70/14 = 5 yrs

70/10 = 7 yrs

70/ 5 = 14 yrs


So when someone says:

We are going to grow 14% every year, this person is saying that revenues will double in 5 yrs.

 in short:

14% every year ? --> 2x in 5 yrs

10% every year ? --> 2x in 7 yrs


5% every year ? --> 2x in 14 yrs


2014/10/21

Healthy Daily Retention Rates

What are healthy retention rates ? Below is a rolling retention benchmark.

(free pic under CC)


If your midcore f2p mobile title does not match any of these, forget it:

1 Day Retention: 40%
7 Day Retention: 20%
30 Day Retention: 10%

(for iOS 5.0 or 2.3 Android and higher)



Playstore Ranking and Revenues

Here are my guestimations for the Korean Market (Play Store)

Below figures reverse engineer the current mobile gaming revenue size of 1.5 billion US$ in Korea for Play Store (2013) figures.




 Rank    Daily Revenues    Annual Revenues    Total Annual  
 1-5   $ 300.000  $109.500.000  $ 547.500.000
 6-10   $ 100.000  $ 36.500.000  $ 182.500.000
 11-30   $ 20.000  $ 7.300.000  $ 146.000.000
 31-50   $ 10.000  $ 3.650.000  $ 73.000.000



 $ 949.000.000





 % of Total Revenues   66%

 Total Market Size    $1.437.878.788 

2014/06/05

Sounds Big

The sentence "sounds big" has a particular meaning to me.
 When I was 26 years old, Investment Analyst at T-Venture, I had the privilege to attend a Amadeus Capital Fund Board meeting.
 Pundits like Herrmann Hauser and Frank Bonsal (Founder NEA) were participating.
Someone was mentioning a new tech start-up (don't remember which) and Frank just said:

 Souunds BIIGG. (in a slightly southern accent)

(free pic under CC)



 So what was so particular about this comment in this particular context ?
It showed to me a lot about this gentleman:


  •  He is aiming for huge markets 
  •  He admits that he does not exactly know about the business/industry and is not ashamed of implicitly admitting it 
  •  He seems to rely on intuition (could as well have said: Let's analyze the market and the product) 
  •  It showed his positive mental attitude & optimism the way he said it.

2014/03/19

Mochi Media is shutting down its services

Before the site completely shuts down on March 31, I am copying the CEO's blog post below.

I will write about MochiMedia's model at a later point in time
(free pic under CC)




Some Final Thoughts from Mochi
First off, thank you for working with us all of these years.
Mochi Media was founded in 2005 by Jameson and Bob with the mission of fueling the creativity of indie game developers. You focus on making a great game, and we’ll take care of the rest. At that time, Flash was a platform that held a lot of potential if developers could find ways to track, monetize and build better games. Together, Flash and Mochi provided an on-ramp to a career or business in game development.
In addition to furthering our services and business, Mochi assumed a role in growing the category. We organized and hosted FGS (aka Flash Gaming Summit) for five years to get this community out from behind computer screens and in person to talk game development. We supported developer meet-ups like Mochi London. And we addressed the “state of the union” with the Flash Game Market Survey. Moving forward, we expect that others will pick up the baton in advancing the indie cause.
I think I speak for everyone who has been a part of the Mochi team over the years in saying that the innovation from you developers inspired us. We take great pride in currently seeing Ninja Kiwi’s Bloons TD5, and Flipline Studios’Papa’s Freezeria To Go among the Top Games Charts on iOS. We love that at one time we shared a desk with Casual Collective which is now known as KIXEYE.
Today, there has never been a better time to be an indie game developer in terms of the platforms and audiences one can reach: Flash, iOS, Android, XBLA, PSN, Steam, HTML5, and the list goes on. If Mochi had a more meaningful position today beyond Flash, then there may have been a different path for the company going forward.
Though we won’t (as team Mochi) be a part of your future growth, we cannot wait to see what you create next. Best of luck.

Thank you,
Josh

2014/02/07

LTV > CPI - a quick & dirty approach to calculate LTV

This is a five minute note about how to calculate mobile app LTV of a specific cohort








Number of total acquired users = 600

Number of churned users per day. This can be found out via Churnrate = 1- retention rate
Day 1 --> 100
Day 2 --> 200
Day 3 --> 300

We assume they churn at the end of the day and that every user that does not churn is active on each day.
         (free pic under CC)
Therefore number of days active or DAU is the following
Day 1 --> 100
Day 2 --> 400
Day 3 --> 900

Total days on which users have been active is therefore 1400 days (which equals DAU)

We assume that ehe sum of total revenues on those three days 140 €

Therefore ARPDAU = Revenues / DAU = 0.10cents

Average Life Time (LT) = Total days active / total users = 1400/600 = 2.3

LTV = average LT * ARPDAU = 2.3* 0.1cents = 23 cents

If we assume that 23 cents is excluding VAT (gross revenues) we have to deduct appstore fee
the net LTV is 16 cents

LTV > CPI (cost per install) is actually not quite ok, because we have to include a certain margin based on your costs

Based on current CPI's at ~ 2-3 $ or Euro, this seems unrealistic. What are solutions?

Virality
In case the game is viral or gets featured by Google / Apple by a factor of 6 , then LTV in theory goes to 1.40€. If you are able to meet a net LTV of 1€ then fine

Getting featured
This is a no brainer

Push Campaigns
Has been discussed many times. Problem is the incentivized installs f*ck your stats

Buying targeted
This means you are able to target those users which have a high LTV. There are certain companies that label this user acquisition strategy as "predictive LTV". We will see how it pans out