Digital Revolution winners and losers

The digital revolution has begun to show us its results, and the winner is… It’s incredible how everything had changed since I started writing this blog more than a decade ago and is not because the human is bringing some new behavior to the table, as a matter of fact there’s nothing new (really new) under the sun. It’s just basically that everything that we use to do in analogical way is getting digital, and it’s not just “a different way”. It’s actually way more than that, probably like a revolution and like in any other revolution there are winners

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The first native data driven company to the Fortune List in 10 years

This is the list of top 10 Fortune companies: Walmart: Founded in 1962. Berkshire Hathaway: Founded in 1839. Apple: Founded in 1976. Exxon mobile: Founded in 1870. McKesson: Founded in 1833. United Health Group: Founded in 1977. CVS Health: Founded in 1963. General Motors: Founded in 1908. AT&T: Founded in 1983. Ford Motors: Founded in 1903. Information was historically expensive until the following products were lunched. Google Analytics: Was launched in 2005. It was after 2009 that it added features to convert the platform into a Corporative Solution. Amazon Web Services: Launched in 20016. Apache Hadoop: Launched in 2011. Google

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Six habits of most successful analytics professionals

Whether you are an experience analytics professional, or you are just making your first steps in Analytics these are six habits that will definitely improve your performance. Planning vs implementation time distribution: The digital industry is definitely pragmatic and due its dynamism there’s normally no time for anything. However a common mistake is going from the idea to the implementation with no, or not enough planning. If I would have to put a number, I would say that it has to be 80% planning and 20% implementation. But why almost nobody invest 80% in planning and research? Because during planning

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Are you still struggling with data? Here is why

It’s been seven years since Meta Analytics was published. In that book instead of focusing on the technical aspects I wrote mainly about two main pillars on the insights process. 1) The object: The object is what the subject (the person) will analyze. Understanding the “substance” of what we are analyzing is key to generate a proper interpretation of what is been observe. The object in our case are companies. Companies are systems, a set of things that interact together with a common objective which is making money today (ie Ebitda) and in the future (ie Purchasing intention). The parts

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Holistic (reductionist) vs Systemic approach of organizations and its impact in goals and metrics

We were talking a lot about the importance of considering companies as what they are, systems. Years of an holistic (Reductionist) approach of organizations generated a huge negative impact. The holistic approach, the scientific attempt to provide explanation of complex things in terms of ever smaller entities, says that if you have a company (system) and you separate it into its parts, then you improve each of its parts and put them back together you will have a better company (or system). The result of this thought was: 1. Independence between departments: If we think that we can have a

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The illogical behavior is finally very logical

Norbert Wiener, who is credited with being the discoverer of cybernetics, called teleological systems to those that have their behaviour regulated by a negative feedback. Negative feedback occurs when some function of the output of a system, process, or mechanism is fed back in a manner that tends to reduce the fluctuations in the output, whether caused by changes in the input or by other disturbances. The first and fundamental revelation in this regard is the provided by Darwin with the theory of natural selection, showing how a blind mechanism can produce order and adaptation. In the case of the

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The hidden part of the iceberg

Has well as you can’t manage what you don’t measure, you can’t measure what you don’t understand or don’t know. That’s why I was writing in the past posts about systems, then about organisational systems. During last years companies were trying, without really achieving any interesting result, to implement data driven cultures as a way to combat the disorientation generated by the surfeit of information. The failure can be explained by the non-systemic view managers normally has about organisations. They addresses the problem in the same way they converted they companies in Green Companies, by adding an isolated area in

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Composing parts (Variables) of a Company and their impact in business results

In my previous posts I was talking about theories of systems and the “Meta Theory” called General Theory of Systems as a way of simplifying and studying organisations. In this post we will organise the parts of the Organisation Systems in general categories that can be also taken as “Variables” for its future “Flow Analysis”. INPUTS: Data. Money. Work. Technology. Energy. Capital Goods. Equipment. PROCESSING: Production Lines. Assembly lines. Management and skills. Generate interest in purchasing. Increase engagement. OUTPUTS: Products. Services. Results. Sales. Registered user. Dividends. Taxes. Information. Customer satisfaction. Employee satisfaction. CONSTRAINERS: Company internal lobby. User experience management. Change

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How to make a self explaining reports

The Digital Analytics Association defines Digital Analytics as the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimising digital usage. It’s not a minor thing that analysis and reporting are separated. Analysis and reporting are two really different things. 1. Analysis: Is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it. The technique has been applied in the study of mathematics and logic since before Aristotle (384–322 B.C.), though analysis as a formal concept is a relatively recent development. The word comes from the Ancient

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Marketing is about people buying intention. Conjoint Analysis 101.

We’ve already talked that companies have one main objetive, earning money. If we add the variable ‘t’ we can split this main objetive in two, present and future earnings. The present earnings is the Company’s current economic result, while the future earnings are determined by the buying intention. On the other hand the above mentioned buying intention it’s the result of several variables that occurs together like: 1. The person have the need or intention to buy something in particular. 2. The company have the product that can satisfy the generic need. 3. The person have the money to buy

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