'A man in China takes a bat soup and at the other end of the world you got fired.' (@laJuani_Crazy).

The Butterfly Effect has mutated into the Baterfly Effect, and confronts us with what some identify as a clear case of Taleb's Black Swan that companies cannot foresee. However I disagree with that interpretation.

Those who know me most intimately will remember my sermons warning of the 2008 crisis. My arguments were belittled even in my closest circle. It is not easy to be heard when you seem the only sober at a drunk party. So, even at the risk of being called Captain Hindsight, let's wash the Swan. Maybe we'll find out why it wasn't as black (unexpected) as it looked.

We have already said in the article 'The time machine' and 'The Star of the Unborn' that to identify and classify the elements and mechanisms of change in long-term prospective activity, we must take into account two factors: Impact and plausibility.

Last week I had the opportunity to participate in a work session to involve new analysts in the Intelligence Function digitized with mussol by antara. It was a pharmaceutical company, with a team distributed between Madrid and Barcelona.

A dozen people participated, including the leaders of the Intelligence Function, all women. I know that in the biopharmaceutical sector there is a high proportion of women in relative terms. But even so, the fact that 12 in 12 were women brought back to my mind an investigation that had been pending for months: Is the Competitive Intelligence Function becoming a women's led activity?

The most agile and advanced companies find it difficult to recruit qualified personnel for any of the so-called "new professions". Competitive Intelligence is not an exception. Companies feel the growing pressure to develop their Intelligence Function, and some projects are put at risk when appointing responsibilities to personnel without specific training.

To make it easier for companies to find trained professionals in Intelligence is one of the reasons why antara collaborates with universities in three continents, supporting the introduction of students in Competitive Intelligence, either as part of their career curricula, or as specific postgraduate training.

Throughout the past year a study on teaching methods of Competitive Intelligence has been developed, including the evaluation by the students. The Technology, Foresight and Management Research Group of the University of the Basque Country UPV / EHU (Department of Business Organization), and the Master in Creation and Management of Innovative Companies of the University of Valencia (UVEG (Faculty of Economics) have contributed to this work.

At Antara we had the unique opportunity to compare the results of two different strategies in the Digitization of the Intelligence Function, developed in two industrial companies. Let's see how these strategies differ, their results, and our conclusions.

According to Big Data, if the US government wants to reduce suicides, it must reduce investment in science. Strange? The following graph shows that both variables are correlated to 99.8%.

Of course, common sense tells us that something is wrong. Developing the trend analysis by ourselves can give us a great competitive advantage. But doing it from the pure data, without causal analysis, is dangerous. In a world with huge data available, Big Data allows us to discover "possible" correlations, even automatically. But this does not mean that there is a causal relationship. As Nassim Taleb says in his Black Swan, the human being is programmed to identify patterns and infer causality, since his survival has depended on it throughout evolution. But this generates inconveniences such as superstition, and also big decision mistakes when we apply Big Data in the company.

From Spurious correlations (Tyler Vigen)

On last Tuesday I attended the Digitalising Manufacturing Conference in Coventry and enjoyed it very much, because not in vain I devoted the first 15 exciting years of my career to what is now called Industry 4.0. In his closing speech, Ken Young, CTO of the MTC, focused on people. This is significant, if we consider that the Conference was dedicated to the latest advances in automation, which a layman could consider is "reducing the dependence on the human factor". However, without the contribution of people there is no possible success.

In Le Concert, I described the new paradigm of Collaborative Competitive Intelligence. With Collaborative Intelligence we can make the best tactical and strategic decisions thanks to the knowledge distributed throughout the organization. But the implementation depends especially on the people, and secondly on the chosen technical solution.

To implement Collaborative Intelligence we require at least one of the following two components:

• Corporate culture

Or, in the absence of the previous one,

• Discipline

Let's see what are Culture and Discipline, and a Simile to illustrate the difficulties when implementing a Competitive Competitive Intelligence Function.

As a candidate for "northern adoption", I try to look Londoners in the face and say good morning. Joking aside, I have had the opportunity over the past two months to interview people in the North and the South of the United Kingdom: Council representatives from Manchester, Birmingham, Nottingham, and London, managers of manufacturing companies with thousands of employees, a humble bicycle repairer from a small town, many directors of academic institutions, university researchers, representatives from DIT in London, people from the Spanish embassy, with high-tech entrepreneurs from UK and abroad, with  multinationals established in UK... Add to this some knowledge of the EU, after 15 years of collaborations with the Commission and some occasional relationship with Parliament, in the field of science and technology. Shake all that and...

Let's consider Brexit as an exercise of foresight. And let's use the method of Scenario Planning. With two years of negotiations, a more than likely transitional period of several years and a later adjustment, the horizon to study is about six years in the future. Not enough time for a pure foresight that should target at least 15 years in the future, but it is an event that will significantly influence our business in the medium and long term, so it is important to analyze.

"This present used to be the unimaginable future" (Stewart Brand)

If your organization has a vocation for long-term survival, or is a corporate group that must cope with impact investments also in the long term, we will deal here with a problem which interests us: Minimizing uncertainty about the future.

Almost all of us would like to know what is going to happen in our business environment. We cannot see into the future, but we can establish prospective methods for making decisions better informed now. Decisions that will affect our business, whether they are large investments, opening new markets, diversification of products...

When in a work session with a client I refer to "company analysts", there are usually some raised eyebrows and people look as though they’re thinking "we don't have any here"...

Of course. No one has the title "Analyst" on their business card. Well... almost no one.

However, I have only to ask each person how long they spend on monitoring the environment and drawing conclusions.
Everyone invariably says more than 30 minutes a day. Some even almost two hours. Significant. If we add up that huge amount of time, we see that it is much more than is spent on Quality management (which does appear on some business cards).

Two seemingly contradictory indicators have emerged in a past survey of the GIA on global trends in Competitive Intelligence. They will attract the attention of every professional in a Management position:

• Intelligence teams have been reduced by 7% in two years.
• Internal intelligence networks have grown by 15% over the same period!

How do we interpret these figures? Have we increased or decreased resources devoted to intelligence in the corporate world?