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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Information Chaos? Analytics Governance is your only salvation

Most companies were founded in a time when there was a shortage of information. Getting the information was extremely expensive and not very useful since it normally came along late (normally just to justify a decision what was already made) . Today getting information is not expensive any more. Actually you have information everywhere and almost in real time for a very low cost. This avalanche of information instead of improving the decision making process is making it harder or in most cases impossible. Today’s managers and executives say that they are drowning in data. Most of they already attempted

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Understanding the Argentinian Market – A great video from Endeavor

Endeavor, the organization that transforms emerging markets by supporting High-Impact Entrepreneurs, just produced and published a video called “The Multiplier Effect: How a Network of Entrepreneurs Created a Tech Sector in Argentina” that allows you a very good understanding of our industry and my country. This is not directly related to Analytics but I really recommend you to take a look at it.  

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Asking the right questions to the right sources

We already talked about how important is asking the right questions before sitting in front of a particular data source. It makes easier your work since you only need to fill the blanks with information instead of sitting in front of a data source for one, two or three hours looking for “something interesting or useful”. Understanding what questions can answer each data source, it is as important as the question itself. As we talked about five years ago in the Analytics 2.0 model, you have several information sources, each one measure a particular type of interaction between users and

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Standard and non-standard metrics

If you are reading this blog you probably know metrics like Unique Visitors, Visit, Pageview, etc. Those metrics are Standard metrics, which means that the way those metrics are being measured is based on a definition made by a recognized organization (the Web Analytics Association), allowing comparisons among different projects. Actually when someone tells you “I have 10.000 unique visitors”  we all know the meaning of that (10.000 unique browsers being measured by a particular cookie). Standard metrics are very important, actually the Web Analytics Association have  a committee that works very hard trying to define those standards (The standardization

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