Storytelling con datos: no solo muestres tus datos, cuenta una historia. Parte I: contexto y visualización.

En la escuela aprendemos bastante acerca de lenguaje y matemática: en lenguaje, aprendemos cómo poner palabras en oraciones e historias, y en matemática, aprendemos a encontrarle el sentido a los números, sin embargo es bastante raro que estos dos campos se combinen: nadie nos enseña a contar historias con números. Actualmente, la tecnología nos brinda cada vez más grandes cantidades de datos y, junto con esto, nos plantea la exigencia de comunicar los descubrimientos que realizamos en estos datos para poder entenderlos, por ello, la capacidad de encontrar la más adecuada visualización para estos datos es vital para convertirlos en información y usarlos para tomar decisiones.

Muchas veces, los profesionales mencionan en su hoja de vida, su proficiencia en herramientas de ofimática, sin embargo, esto es lo mínimo deseable para cualquier empleador y ya no es diferencial para competir. De la misma manera, poner unos cuantos -o muchos- datos en una hoja de cálculo o en una presentación, implica para algunos que la visualización termina allí, cuando lo que muchas veces ocasiona es que la historia detrás de los datos sea difícil o imposible de entender. Y sí, efectivamente, hay una historia detrás de los datos pero las herramientas no la conocen, pues aquí es donde se distingue la capacidad de un profesional de traer la historia a contexto con la visualización adecuada. Esta, es la capacidad de contar historias con datos, o storytelling con datos.

La importancia del contexto:

Para empezar a entender la importancia del contexto, es necesario diferenciar entre el análisis exploratorio de los datos y el análisis explicativo de los datos. El análisis exploratorio es lo que hacemos para familiarizarnos con los datos, para esto podemos empezar con una pregunta o hipótesis para lograr entender qué puede ser interesante acerca de estos. En resumen, es la capacidad de convertir una gran cantidad de datos en uno o unos cuantos descubrimientos. Por otro lado, el análisis explicativo es lo que hacemos cuando ya hemos decidido qué descubrimientos vamos mostrar a nuestra audiencia, es decir centrarnos en el qué datos vamos a mostrar, a quién se los vamos a mostrar y cómo los vamos a mostrar. Esta parte es donde específicamente se centra la capacidad de contar historias con datos.

Para esto, empezaremos con un ejemplo: el jefe de un área de mesa de ayuda, ha tenido muchos problemas durante toda la mitad del año 2016, debido a que en el mes de mayo de 2016, dos miembros de su equipo renunciaron y desde ese momento su área no ha podido satisfacer la demanda de atención y, por ende, su calidad de servicio ha disminuido de manera crítica. Este jefe tiene los datos de atención de todo el año y va a mostrarlo al comité de productividad de su empresa, que son los encargados de aprobar las contrataciones de personal necesarias para cada departamento, pues necesita que el comité apruebe la contratación de dos nuevos miembros para su equipo. Finalmente, los datos a disposición son muchos pero únicamente necesita mostrar aquellos que ilustran la diferencia entre la demanda de atención y la poca capacidad de satisfacer dicha demanda partir de mayo de 2016. En este punto es importante recalcar un error muy común: decidir qué datos mostrar y, más aún, qué enfatizar.

Así como un museo es valioso no por las obras que muestra sino por las obras que no muestra -de lo contrario sería un almacén y no un museo-, una presentación debe ser valiosa por la selección de datos que incluye y, sobre todo, por lo tuvo que dejar de lado para armar dicha selección. En resumen, el contexto de este caso sería el siguiente:

  • ¿QUIÉN?:
    El comité de productividad de la empresa encargado de aprobar las contrataciones de personal para cada departamento.
  • ¿QUÉ?:
    Enfatizar la necesidad de aprobación por parte del comité para la contratación de dos nuevos integrantes para su equipo.
  • ¿CÓMO?:
    Mostrando los datos que ilustran la diferencia desde mayo de 2016 entre los tickets presentados y los tickets atendidos debido a la renuncia de dos integrantes de su equipo, poniendo énfasis tanto en el punto de quiebre en la diferencia desde dicha fecha.

Escoger una visualización adecuada:

Otro de los mayores errores que los profesionales cometen, es la mala elección de la visualización de datos. En la siguiente imagen, si pidiera buscar la cantidad de veces que aparece el número 3, probablemente me tardaría 15 a 20 segundos explorando la imagen.

 

Captura de pantalla 2017-09-13 a la(s) 18.28.13

Sin embargo, en la siguiente imagen, la misma búsqueda puede tomar 3 segundos como máximo y, probablemente, la mitad de esfuerzo. La razón es simple: hemos enfatizado la parte a la que quiero que mi audiencia preste mi atención, mediante el uso de negritas. De la misma manera, también hubiera sido válido el uso de color y elementos visuales adicionales.

Captura de pantalla 2017-09-13 a la(s) 18.28.33

En la siguiente imagen, podemos ver un típico gráfico de barras, donde se muestra la información descrita en el caso anterior que presenta los tickets recibidos y los tickets atendidos cada mes por el departamento de mesa de ayuda durante el año 2016. A primera vista, no es fácil reconocer el objetivo del gráfico, aunque después de unos segundos, es posible ver que la diferencia entre los tickets atendidos y los tickets recibidos se incrementa a partir de la mitad del año. Si bien se requiere observar bien el gráfico para descubrir esto, la razón de esta diferencia se desconoce por completo.

Captura de pantalla 2017-09-13 a la(s) 18.21.38

En esta imagen, usando los mismos datos pero con una visualización distinta, se muestra en un gráfico de líneas, la diferencia entre los tickets de atención recibidos y los tickets atendidos durante todo el año 2016, con una ayuda visual –barra vertical– que enfatiza la diferencia desde mayo de 2016 y añade una pequeña leyenda para indicar que dicha diferencia se debe a la renuncia de dos integrantes y, adicionalmente con mayor énfasis, una llamada a la acción; la necesidad de contratar a dos nuevos miembros para el departamento de mesa de ayuda.

Captura de pantalla 2017-09-13 a la(s) 18.24.53.png

 

Como conclusión, los dos puntos iniciales a tener en cuenta para empezar a contar una historia es empezar definiendo el contexto: tanto con el análisis exploratorio –qué quiero encontrar– como con el análisis explicativo –contar la historia–, que, a su vez, requiere definir tres aspectos importantes: quién es mi audiencia, qué les quiero decir y cómo lo voy a hacer. Posteriormente, es necesario elegir la correcta visualización para los datos así como enfatizar las partes del mensaje que deseo comunicar a mi audiencia. En siguientes artículos abordaré los factores adicionales que también son importantes para contar historias con datos. Asimismo, no puedo dejar de recomendar el excelente libro ¨Storytelling with Data¨ de Cole Nussbaumer, del cual aprendí y obtuve las imágenes para elaborar el tema sobre el cual trata este artículo.

 

What unlearning really is

To understand what unlearning is, first we need to explore the definition of learning:

  • The act or experience of one that learns.
  • Knowledge or skill acquired by instruction or study.
  • Modification of a behavioral tendency by experience (such as exposure to conditioning)

From the very definition, the act of learning requires not only obtaining new knowledge, either by studying or by experiencing, but also modifying our future behaviour according to the belief that an specific set of actions will allow us to solve an specific problem or successfully deal with a situation. 

We, humans, do not really learn, instead what we do is to look for a pattern, through trial and error, that can be deemed a good enough solution for a given scenario under our appreciation, which is also called experience. Then, in subsequent situations, we just basically apply the same pattern over and over until we stumble upon a, slightly or completely, different scenario that force us to start looking again for a new pattern to deal with this situation. Here is where the problem comes with what we have previously learned: the approach we take is commonly making the most of our own experience dealing with similar problems we solved in the past. From that knowledge on is where we start looking for a solution, since it would be less efficient to start over from a completely fresh and new approach to a problem that might be solved with a little tweak to our previous experience, because come on, we need optimal times and results, and doing it all over again is not a realistic possibility.

For example, if we are given a challenge to come up with a solution to find a cure to a disease, we might start considering several distinct components for an existing drug or maybe a completely new drug, but maybe the correct approach is not a drug to fight the disease but in preventing that an specific gene in humans reacts to a certain body condition which really causes the disease is manifested. That would represent a totally different schema for fighting diseases that would require to focus not in looking for a cure but rather in data to predict a possible scenario and, consequently, not using physicians to cure diseases but data scientists to predict possible situations and probabilities where the disease is manifested.  

If the example sounds totally out of logic is because our prior learning (physician cure existing disease in human using drug) prevent us from adopting a new frame of mind (data scientist find pattern in data to prevent future disease in human) to deal with a known situation. Today, usage of human data to find patterns to alert us of possible future diseases is more common everyday but without a mindset to leave behind the old -even the current and working- and to make way for the new then there is no possibility yo unlearn.

Unlearning is not about forgetting what we know -because sooner or later we unconsciuosly go back to our old ways- but having the capacity to freely choose a totally different mental model to replace our current one, is being able to look at the things we have known all our life from a totally different perspective to find them different or less logical purposes or reasons, that might even surprise us later.

Finally, both individuals and organizations need to be learning entities but innovation demand unlearning first so that -as stated previously- we can make way for the new.

El efecto de la inmigración y el verdadero acceso a la educación.

De la misma forma en que hoy leía cómo cientos de personas se quejaban, en la versión en línea de un diario peruano de negocios, sobre la inmigración de ciudadanos venezolanos a Perú, pensaba en las palabras de un destacado Premio Nobel de Economía, a principios de este año, donde mencionaba que si una persona tiene la capacidad de acceder a una red social para su entretenimiento desde un teléfono inteligente básico, dicha persona tiene la misma capacidad de acceder a toda la educación posible que la Internet le brinda de manera totalmente gratuita.

La inmigración casi siempre tiene efectos positivos en cualquier economia, pero no todos siempre se benefician de la competencia. La competencia, en cualquier campo, genera mejores precios pues hay mayor oferta, dado que el precio es un indicador de escasez. Esto es fácilmente visible todos los días cuando pagamos menos por productos importados en comparación con productos nacionales por los cuales antes solíamos pagar más, lo cual sin duda es beneficioso, sin embargo esa mayor competencia de precios también puede afectar al precio de tu trabajo, es decir puede afectar a tu sueldo. Siempre nos quejamos de que las cosas suben de precio y, de la misma manera, hacemos fuerza común y reclamamos para que las cosas bajen de precio, pero cuando se refiere al precio de nuestro trabajo, nuestra óptica nunca es la misma.

No voy a ahondar más en el tema de la inmigración, pero es cierto que ésta golpea, más que a los individuos con menor educación, a aquellos que no logran adaptarse a lo que el mercado laboral, tan cambiante, exige para ser mínimamente competitivo. Esto, pues el mercado laboral no es de suma cero, es decir si entre dos trabajadores, digamos, poco calificados, uno logra tomar un puesto no necesariamente se lo quita al otro, pues acá entra la innovación, que permite que un individuo usando su ingenio no solamente pueda prepararse de una manera distinta para acceder a otro tipo de trabajo que demanda distintas competencias sino que incluso, usando ese mismo ingenio, puede generar emprendimientos, que crearán muchas más plazas laborales.

Esa misma educación que sólo unos años atrás podía ser accedida solamente por una élite privilegiada, ahora se ha democratizado. Cualquier niño en un país en vías de desarrollo con acceso básico a la Internet puede comunicarse directamente con cualquier científico, presidente, deportista, artista del mundo usando Twitter, seguir las actualizaciones de los principales autores, grupos de cualquier tipo de interés o empresas usando Facebook, acceder a cursos de todos los idiomas en Duolingo, estudiar los programas de pregrado y postgrado de las mejores universidades en Coursera, absolver las dudas básicas en casi cualquier materia de educación elemental en Khan Academy, conocer los museos y calles más famosos del mundo usando Google Street View, generar una bitácora con contenido propio usando WordPress, leer artículos de prácticamente cualquier tema en casi todos los idiomas usando Wikipedia, crear y compartir su propio contenido en vídeo con millones de personas usando YouTube, traducir cualquier texto en cualquier idioma, incluso en tiempo real, usando Google Translate, leer las editoriales y artículos de los mejores economistas del mundo en la versión en línea de The Economist, leer las últimas ediciones de las mejores revistas y publicaciones del mundo usando Issuu, llevar cursos de programación y tecnología de las mejores universidades y empresas del mundo usando Edx. Podría seguir y seguir enumerando ejemplos pero, vamos, el problema no es el acceso a la educación, el problema es la mentalidad. Si todos los días toco temas de educación, innovación, Internet, etc., es por algo muy obvio: ya me di cuenta de que el mundo está cambiando.

Cuando alguna vez le pregunté a un famoso economista, en su visita a Lima, acerca de cómo la Internet está cambiando la educación, me respondió que la educación no había cambiado mucho, pues ésta no es una etapa de la vida sino una experiencia de vida y la Internet únicamente la ha hecho más accesible y democrática. Sí, esa educación a la cual muchos dicen no tener acceso, hoy en día, es más accesible que nunca, sobre todo si, en este momento, estás leyendo este artículo desde una red social, desde tu teléfono o computadora ¿no es así?.

El valor de compartir lo que sabes

Junio de 1999, no sabía qué hacer aún con mi vida. Tenía 17 años y lo único que sabía bien era que religiosamente debia estar despierto antes de las siete de la mañana para escuchar a un argentino de apellido Giacosa, que tenía un programa en una radio de no mucha audiencia pero que, para mí, a esa edad era, de lejos, lo más interesante de mi día. Recuerdo que soñaba hablar francés como él y que me dejaba impresionado todo lo que conocía sobre tantos temas y tantas personas de tantos países. Recuerdo que lo acompañaba en su programa un tal (Renato) Cisneros y que en sus conversaciones del programa matinal de dos horas, maldecía a la susodicha radio por no darles una hora más para poder seguir escuchando sus tertulias.

Recuerdo aún sus historias sobre las novelas clásicas, sobre el origen de algunas palabras, sobre política internacional, sobre personajes históricos. Deseaba tanto poder leer todo lo que él había leído que aprendí a renegar conmigo mismo cuando caía en la cuenta que no sabía el por qué de algo. Aprendí escuchándolo que lo apasionante son las personas que saben contar las historias y no las historias en sí. Aprendí que puedes conocer a una persona sin conocerla en persona solo escuchándola o leyéndola. Aprendí que uno puede ser mentor y ser maestro sin conocer a alguien, solamente compartiendo lo (poco o mucho) que uno sabe. Aprendí que lo que quería hacer en la vida era saber y saber tanto como él.

Hace unos años cuando publicó su autobiografía (no autorizada), corrí a comprarla y la leí toda el mismo día. Hoy, por esos golpes de suerte en la vida, tuve la oportunidad de conocerlo personalmente y conversar con él, le pedí que me firmara su libro que conservo hace casi una década e incluso nos tomamos una foto en mi oficina. Hoy le conté historias, que el contó hace casi dos décadas en la radio, que no he olvidado y que incluso él mismo ya no recordaba. Las recuerdo como si fueran de ayer. Todo pues una de las personas a las cuales le debo mi pasión por la lectura y por lo bonito que es aprender es a Guillermo Giacosa.

Gracias por tanto, gracias por compartir lo que sabes, maestro.

 

dav

La paranoia constructiva y el sentido de urgencia 

Si existe algo que es vital para que una empresa o individuo se mantenga vivo en el competitivo mundo en el que hoy nos toca vivir, ese algo es definivamente sentido de urgencia. El sentido de urgencia viene de un propósito más grande y relevante para hacer que algo bueno suceda.

El sentido de urgencia es, más que todo, una forma de pensar donde asumimos que el cambio rápido y constante es tanto normal como necesario, siempre en la búsqueda de que un objetivo superior positivo sea alcanzado. Algo similar a la llamada paranoia constructiva que Andrés Oppenheimer menciona en países como China y Corea del Sur en su libro “Basta de Historias”, donde cuenta cómo funcionarios de esos gobiernos asiáticos siempre están pendientes de cuánto avanzan sus pares en cuanto a educación, innovación y temas afines, pues todo el tiempo sienten que van a quedar relegados y fuera de carrera por lo que están siempre buscando nuevas maneras de seguir siendo competitivos a nivel mundial y, especialmente, en comparación con dichos países. Esto deviene en países tremendamente competitivos en cuanto a educación e innovación se refiere, pues el estar en constante competencia, naturalmente eleva el nivel de estos países lo que los lleva a ser líderes mundiales en estos campos.
Ahora bien, un concepto muy distinto pero que puede ser confundido es sentido de emergencia. Una emergencia, por definición, no es positiva. Mientras con el sentido de urgencia el enfoque es proactivo, con el sentido de emergencia el enfoque es totalmente reactivo, pues si bien uno puede estar preparado para afrontar una emergencia, lo que se busca al final del día es eliminar o controlar dicha emergencia. Es más, lo que cualquier individuo desea es nunca verse ante una emergencia.
Asimismo, un reto igual de grande es evitar el llamado falso sentido de urgencia, donde todo lo que se hace durante todo el tiempo se vuelve urgente, quitándole lugar a lo importante, que es el propósito que se quiere alcanzar al implantar el sentido de urgencia en nuestras acciones. Esto es fácilmente reconocible en todo tipo de comunicación que lleve la palabra urgente, generalmente en el título, al final de una oración, etc., pues cuando algo es urgente es consecuencia de un mal planeamiento previo e incluso el usar esta palabra es dañino para un genuino sentido de urgencia.

En mi experiencia, en una empresa es absolutamente necesario tener una visión clara de hacia dónde se quiere llegar y qué se quiere lograr para poder recién aplicar un sentido de urgencia a lo que se hace. Justamente lo más complicado de todo esto es que la empresa tenga visión y con esto no me refiero a una frase escrita en papelería corporativa que en la práctica es letra muerta sino que tenga la capacidad de ver -o imaginar- algo que todavía no existe pero que al poder verlo, le permite enfocar sus esfuerzos hacía ese lugar que aún no existe pero dónde muy probablemente se estará en un tiempo.

Si uno le pregunta a un trabajador de una empresa, elegido de manera aleatoria, sobre la visión de la empresa y éste no sabe respónderle, entonces es imposible imbuirle un sentido de urgencia a lo que éste hace, pues probablemente termine preguntándose a sí mismo la razón por la cual hay tanto apuro en hacer las cosas, lo cual termina disrumpiendo su calmado, nada cambiante -y ya de por sí estresante para él- día a día laboral. En conclusión sin una visión clara de un objetivo superior a alcanzar no es posible tener sentido de urgencia en lo que se hace.

Finalmente, en una empresa muchas veces existen visionarios: individuos que no se conforman con aceptar el estado actual de cómo funcionan las cosas y que constantemente cuestionan el por qué debe algo ser de una manera que quizás está sujeta a mejora. Estos individuos, denominados intraemprendedores, no siempre ocupan los cargos más altos pero gran parte del tiempo marcan la pauta de las acciones que la organización emprende y usan su influencia, habilidades y conocimientos para no solamente lograr que algo pase sino para imbuirle sentido de urgencia a la organización completa. 

What follow your passion means to me: letter to the 15 year-old me

I have recently turned 35 and right now I still feel I have so much to learn. In 1997, I was 15 years old and I dreamed of too many things, but as almost any teenager I did not know what to do. I clearly remember 1997, it was a great year, I  had my first official girlfriend. I could make end meets with so little money. A new cinema arrived to my neighborhood. I really had a great time that year. It was pure happiness. Now in 2017, things are different. My personal life has changed in many ways. I am really happy doing what I do, but I also dislike some other parts of my life, which I work hard to change. So in 1997, I had the privilege of owning an e-mail address, almost no one of my school mates had any idea of what that e-mail address thing was. So this letter, would actually be an e-mail address to my 15-year-old me, hoping he (or should I say, I) can thoroughly read it and learn from 20 years of future experience.

Hey Alan

For clarity reasons, I will refer to you as dear 15-year-old me, you know, to tell each other and avoid confussion. So dear 15-year-old me, life is good, isn’t it?. I have found you kissed that girl and you are officially a couple, that’s great. She’s hot and funny, so be nice to her. I heard that you are having a great time at school, aren’t you?. Make the most out of this time, because it passes by so quickly and moments like these will not be back again. You are still a teenager, so do not worry so much about anything right now. It is not that important. Really.

So dear 15-year-old me, I am you, but 20 years older and with much more experience and mistakes, life has been nice to us many times and others, has been very rough as well. Times can be so hard many ocassions, but you will make it in the end. I will make sure of that. I am going to give you an advice, it is something very simple and direct, that maybe not many 15-year-old kids get to know. I hope you always keep it in your mind.

My advice is: create something. Yes, use your brain to start something. Focus obsessively on creating something. It does not matter if you fail through the process. I am sure you will fail anyway. It is necessary. People will laugh at you. They have no better job than making fun of other people because they have nothing important in their own life. You will study in the university and be a good professional, maybe not in the university you always dreamed of and maybe not the career you always wanted to but it will be fine. Listen, do not forget what I am going to say: what I have learned is that most people, almost everyone is afraid to create something new, they do not want to do it, simply because it is harder than anything else in life.

So, dear 15-year-old me, you do not need to create the new Facebook (you and the whole world will later know what Facebook is) or Microsoft, but you need to start something. It is perfectly fine if you work in a company and start new solutions or projects, then you would be an intrapreneur. If you go by your means and start something, then you would be an entrepreneur. Both are great and will make you equally proud of yourself.

My point, dear 15-year-old-me, is that most people prefer to follow the crowd. Simply following the rules and try not to break anything by the end of the day and with the money they earn, consume as much as they can. In the end, you can live a decent and happy life, but to me consumption does not mean fulfillment. For me (and you), only creation, starting something new will mean fulfillment.

So, dear 15-year-old me, that explains why my (I mean, your) personality reflects that urgency of not compliance with the dogma, the necessity of improving the current state of things. I strongly believe that it is reasonably impossible to live a happy life with no money or with debts. Lack of money means unhappiness, period. But once you start making money, consumption does not make you proud at all. Money is the leverage you need to create something. That is why I (or you ) admire people not for what they own but for what they have achieved or created in life.

When people talk about following their passion, they really need to be serious about it, they simply cannot play video games and eat chips all day, that would not be sustainable at all and it would be impossible unless someone pay your bills permanently. But if you play video games to create something valuable for other people, for example a YouTube channel (again, you will one day know what YouTube is and you will definitely love it), then you are really following you passion.

So, dear 15-year-old me, focus not on consuming with the money you will earn in the future but on creating something you will be proud of. Never let anyone, not even your dad, to tell you that you cannot do something, I know you always feel bad about not doing what people expect you to do, but really try not to give a fuck about it. You will regret not what you did but doing what you did not want to and eventually did to please other people. 

You will love technology as you do right now, you will devote considerable time to this field. You will love learning as you do right now, but you will realize that you can learn by yourself by hanging around with you best mates: books. You will love books, soon you will realize.

You will pass through rough times. I bet right now, at 35, you will realize things are not pretty easy at all. But do not worry, this time will also pass and you will be fine again. But please never ever forget the most important thing in your life: always follow your passion, because passion never fails. I only wish I had known all of this 20 years ago. 

Looking forward to meet you in 20 years.

Alan

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How does Netflix know what movies I like?

What does Statistics have to do with Netflix knowing what movies you will like? A lot. Specifically with something called correlation. In Statistics, correlation allows us to measure the degree in which two different phenomena are related to one another. It is certainly possible to find correlations everywhere, for example:

  • Temperatures in the summer and sales of ice cream.
  • Completed years of education, the higher your potential to earn.

When one of them goes up, so does the other one. These types of relationships, for example the one of the temperature and ice cream sales, can be represented by a graphic called scatter plot, like the one below:

But then, how does Netflix know me so well to know what movies I will like?  The answers is that it does not know you but it can predict what you will like through the usage of complex statistics using the data of the films you have liked in the past based on how you —and other customers— have rated them.

Netflix estimates that 75% of user activity is driven by automated recommendations that the service provides to its users. Back in 2006, Netflix launched a contest called Netflix Prize in which any person was invited to came up with a new algorithm that improved the existing Netflix recommendation system by at least 10 percent (that is 10 percent more accurate in predicting how a customer would rate a film after watching it). The individual or team that accomplished this feat would obtain one million dollars.

Using what they called “training data” —more than 100 million ratings given to 18,000 films by 480,000 Netflix customers— thousands of teams from 180 countries developed improvements to the existing algorithm to accurately predict the actual rating these customer will give to a selected group of films. After three years of perfecting the algorithm and thousands of attempts by the participants, Netflix declared a winner: a team of seven people conformed by statisticians and computer scientists from several countries.

What this algorithm does is an automated version of what we have been doing for several years to pick a movie to watch: find somebody with a taste in movies that matches yours and ask for a personalized recommendation, knowing that if that person’s likes and dislikes closely approach yours then that person’s choice will be similar to yours. In Statistics this is called correlation.

We can say that two specific variables are positively correlated if a change in one is directly associated to a change in the other one, always in the same direction, this could be the case for the relationship between height and weight. This is because people who is taller generally weigh more (on average); and people who is shorter tend to weigh less (also, on average).

The reason why I emphasize that these associations are not exact but average is because not every observation fits exactly an specific pattern. In some cases, short people weigh more —much more— than tall people,  and in other cases, people who don’t exercise at all are slender than people who frequently exercise. 

One interesting characteristic about correlation as a statistical tool is that it is perfectly possible to express an association among two specific variables in a simple but very descriptive statistic called the correlation coefficient, which features two interesting points to notice. Firstly, that coefficient is just a simple number whose range goes from –1 to 1. When a correlation coefficient is 1, also known as perfect correlation, it implies that an alteration in one of the variables is directly linked to an equivalent change in the other variable in the same direction, and when the correlation coefficient is –1, also known as perfect negative correlation, it implies that an alteration in one of the variables is directly linked to an equivalent change in the other variable, but this time, in the opposite direction. When the correlation coefficient gets closer to either 1 or –1, then it is said that the correlation is stronger. Plus, when the correlation coefficient is 0 or close to 0, then it is said that there is no correlation between the two variables, to make this point clear, we can use the example of the —ridiculous and non existent— correlation between the number of shoes a person owns and the weight of that person. Secondly, when the correlation coefficient is expressed no units are involved, no matter what the nature of and how different each of the variables is, such is the case of the correlation between a variable expressed in units (number of shoes) and a variable expressed in kilograms (weight of a person).

Finally, the most important feat that, in Statistics, a correlation coefficient allows us to do is to simplify what could be very complex relationships among tons of pieces of data —which would require several different charts and tables to express— using an extremely simple descriptive statistic, the same one that Netflix uses to give us an extremely accurate recommendation of the next movie we will watch.

We all are experts in something (and why you should make the most out of it)

Yes, we all are. This affirmation might seem a little odd but I am absolutely convinced that you do not need a master or doctoral degree to become an expert. 

First, I wanted to make clear what, academically, means to be an expert, to achieve mastery in a topic or field, and that led me to look for the definition of a master degree. By definition, those individuals who obtain a master degree are considered experts in one (or more) specific topic(s).

According to the portal Top Universities this is the definition of a master degree:

A master’s degree is an academic qualification granted at the postgraduate level to individuals who have successfully undergone study demonstrating a high level of expertise in a specific field of study or area of professional practice. Students who graduate with a master’s degree should possess advanced knowledge of a specialized body of theoretical and applied topics, a high level of skills and techniques associated with their chosen subject area, and a range of transferable and professional skills gained through independent and highly focused learning and research.

While this definition makes complete sense, according to Malcolm Gladwell in his best seller book “Outliers”, to really achieve mastery, there are a number of factors to consider, but one of the reasons individuals become not only proficient at something but real experts is an insane amount of hours of practice under the appropriate conditions, which is also called delivered practice.

Formal education is definitely useful to achieve mastery at something but without the required hours of delivered practice, it is definitely not possible to become an expert. In the same way that children learn to speak a language —even a difficult language as German, for example— through continous trial and error, if formal education or even self education delivered for a determined period of time is added to the learning process, any given person might perfect their skills to acquire the expert status. 

Therefore, we can assert that when an individual has devoted countless hours of practice to an specific activity, be it part of their regular work or a personal hobby, under an specific context, that individual might have developed skills and knowledge that an average person does not possess. That is to say, that an expert is not necessarily someone whose knowledge and skills are absolutely the best in a field, but someone whose knowledge and skills are even slightly superior to those of the average person and is capable to use them to solve a problem or to help someone else to solve a problem.

Every person we know could be an expert in something, even when that person is not conscious about it. For example, we all know somebody who knows a little more than we know about technology and gadgets. This person is the first one we think about when we experiment a technology problem, that person might be 13 years old or 50 years old, male or female, no matter who that person is providing that they can help us to solve an specific problem, that person is an expert to us.

A single mother who has raised four children will definitely have a lot of tips and knowledge about upbringing in her YouTube channel that can be highly valuable to any new mom looking to raise her first child. A carpenter with no formal education who owns a workshop and has been in the business for two decades could possibly write a 500 page e-book on  carpentry that a Fortune 500 CEO with a passion for woodwork will possibly find extremely interesting. A 11 year old high school student who is passionate about Minecraft could write a daily posts in his blog about tips and techniques for the videogame that many grown-up gamers might find very useful. Again, formal education for these individuals will definitely create more value for them but without devoting hours and hours of practice, mastery will be just an illusion.

Every one of us is an expert in something we have probably been doing during some time of our life, but then real goal is finding what of all that we know might bring value to the lives of other people, because we know a little bit more about it than everyone else and can use to help others.

The reason we want the latest gadgets

Did you know that according to a neuroimaging research Apple products have the capacity to activate the same parts of the brain in its fans as religious images trigger in a religious person?. Well, that is no surprise since last september Apple announced it had sold more than 13 million new iPhone 6s and iPhone 6s Plus models, a new record, just three days after launch. Every time a new iPhone model is released, we see scenes from around the world of hysteria and insane competition for being in the privileged first group of people to possess this gadget.

According to a research by Dr. Sundeep Teki, a Sir Henry Wellcome Postdoctoral Fellow in Neuroscience based at the Ecole Normale Superieure, Paris and the University of Oxford where he investigates learning and memory for natural sounds like in speech and music, the real reason why certain individuals show this behavior when exposed to these stimuli is tightly related to the human brain and not so much to the magic of Apple products. Initially we might assume that it is the magical effect that Apple products entail because of their superb product design, exquisite attention to detail or something more difficult to describe. Maybe we are wrong and it is actually something else. The human mind is biologically set to seek fulfillment of several basic needs such as: shelter, security, affection, status, etc. Basically, as Martin Lindstrom affirms in his book Small Data, the main reason why humans do everything we do is desire. It is what motivates us to make every decision either explicit or autonomous, in our life.

The moment we obtain what we desire,  a mechanism in the striatum, the reward network of the brain, is activated, which as a result produces a chemical called dopamine, with a neurotransmission role in the brain,  that leads to demeanors of several types depending on which of the brain’s pathways it is operating in. Dopamine actually has a lot of functions in the brain, from movement to control of attention, but at the same time it might be involved in addiction of any nature as well. That could be the reason of a shopper’s compulsive behavior, which is only satisfied when the reward is obtained with the associated increase in the level of dopamine in the brain.

But not everything with dopamine is related to pleasure but also with an attempt to obtain that pleasure, which can involve certain feelings of stress, such as the case when gamblers play lottery or casino games and experiment excitement when they are close to win and that feeling lead them to keep trying. These feelings are not pleasurable at all but more related to distress for those individuals, but due to the release of dopamine in the brain, they feel some pleasure in a certain way, because when they undergo this experience the feeling of mastery of the game is high when in reality it is confused for acquired skill. But dopamine is not only related to the search of pleasant or exciting experiences but also to the rejection of certain experiences, such is the case of war veterans that cannot stand gun sounds or any sort of reference that reminds them of armed struggle.

Modern society nowadays has to our disposal all the necessary to satisfy not only our basic needs (biological, safety needs) but also our higher level needs (love, esteem, self-actualization needs) through a variety of products and services which we can access more easily through the Internet, and by mixing two disciplines such as neuroscience and marketing, we have developed a new discipline called neuromarketing which makes smart use of psychology, biology and neuroscience to identify patterns in human behavior and to undestand consumers needs so that they can properly satisfy them even before the consumers are conscious of their desire. Marketing has always tried to understand what consumers want to try to satisfy their needs, but it is even better -through neuromarketing- that someone tries to satisfy our needs before we even know what we want, isn’t it? .
 

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The old pair of sneakers that saved Lego

If there is a catchphrase in the corporate world lately, that is definitely Big Data, which can be defined as the storage of huge amounts of data from every possible source and its use for determining repetitive patterns. Personally, I believe that the correct term should be A lot of Data because we are not talking about how big every piece of data is but the massive amount of data we are handling.

For this reason, Martin Lindstrom, author of the international bestseller, Buyology, in his latest book Small Data says that “Big Data is data and data favors analysis over emotion” and also states that it is difficult for him to imagine data capturing many of the emotional qualities that we -humans- most value, such as: beautiful, friendly, sexy, awesome, cute, etc., and this is because if data itself could only express the purest emotional decisions humans make, then accountants, and not poets, would be the cultural prototype for great lovers in history.

Saatchi and Saatchi CEO, Kevin Roberts, indicates: ”great brands have two advantages: (1) they evoke respect for their technological performance, durability, and effectiveness; and (2) they evoke love because… we love them”. This could be the case of brands like Disney, Lego or Apple. They are both respected and loved and this exactly at what Big Data is not proficient at: measuring certain aspects, such as love.

And here is where the interesting story develops: it was the the first half of the decade of the 1990s and Lego’s sales were declining which had executives of the company worried about studies that indicated a trend in which children were beginning to migrate to another type of games that more easily provided them with instant gratification. In response to these trends showed by those reports, the company executives were considering making Lego game sets easier to complete, in other words: dumbing the toys down. At that time, Lego started to move on towards different business lines -theme parks, children’s clothing lines, video games, books, TV programs, etc- and, at the same time, thinking of manufacturing bigger bricks for the ease of use of its toys by children. All of this because the future seemed to be doomed: future generations would lose interest in LEGO.

But, in an unexpected turning point, everything changed as a result of a visit Lego marketers paid to the home of an 11 year old boy in Germany by early 2004. That same day, Lego executives realized that everything they though they knew through studies and reports was completely wrong.

This boy was not only a Lego enthusiast but also an assiduous skateboarder that when asked which one of his possessions he was most proud of, did not hesitate to signal to a pair of Adidas sneakers with ridges and nooks along one side. He explained proudly to them that they were kind of a trophy, gold medal or masterpiece. In fact, those frayed sneakers were the evidence to his friends that he was one of the best skateboarders in the city, because one side of the sneaker was worn down right when the grip tape of the skateboard scratches it. It all fitted perfectly.

At that very instant, it all made sense for the Lego marketers. They realized that children acquire social status among their peers through the mastery of a skill, no matter what skill that is. The same occurs when this kid receives a Lego game set for his birthday, which causes he wakes up at 4 am and stays until midnight to try to build it no matter how long it takes. The satisfaction lies in the fact of having something tangible to show his mastery, in this case it could be a finished Lego model or even a pair of worn down sneakers.

Until that moment, all the decisions that Lego made were based on Big Data, but that small insight caused that Lego did the opposite to what the reports and studied suggested. They made their toys even more difficult to assemble and more thematic -Star Wars, Minecraft, etc.- to attract more children. Almost ten years later, Lego released a super successful movie and surpassed Mattel to become the world’s largest toy maker.

All of this is the opposite of Big Data, according to Martin Lindstrom it is called Small Data, and it means treating humans not as a number but as humans. You can buy the book from Amazon in the following link:

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You can also watch a shot video for an interview to Martin Lindstrom about his book