What Big Data, what information dominance?


A new adage is blowing around in the world of innovation. According to Wikipedia, The term “big data” often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. Analysis of data sets can find new correlations to “spot business trends, prevent diseases, combat crime and so on”.
It is reminiscent of an early US Navy doctrine, as a codification of beliefs or a body of teachings or instructions, taught principles or positions, as the essence of teachings in a given branch of knowledge or belief system. As such, it is a thinking pattern, in which is stated that “information superiority permits the conduct of operations without effective opposition”.

However, in an electronic war game back in 2002 one aircraft carrier, ten cruisers and five out of six amphibious ships were sent to the bottom of the Persian Gulf in the span of just one hour, resulting in the virtual death of over 20.000 US service personnel.

It was the result of an asymmetric strategy by the opponent forces.

Red, commanded by retired Marine Corps Lieutenant General Paul K. Van Riper, adopted an asymmetric strategy, in particular, using old methods to evade Blue’s sophisticated electronic surveillance network. Van Riper used motorcycle messengers to transmit orders to front-line troops and World-War-II-style light signals to launch airplanes without radio communications.
Red received an ultimatum from Blue, essentially a surrender document, demanding a response within 24 hours. Thus warned of Blue’s approach, Red used a fleet of small boats to determine the position of Blue’s fleet by the second day of the exercise. In a preemptive strike, Red launched a massive salvo of cruise missiles that overwhelmed the Blue forces’ electronic sensors and destroyed sixteen warships (Wikipedia)It is the same kind of bold thinking we noticed in our blog Thinking outside the SeaMap:  “doing different things” or “escaping the temptation to do more-of-the-same but only better”.


Military strategists distinguish between symmetric and asymmetric warfare. Symmetric warfare is characterized by standing armies that follows more or less the same tactics and organized in the same way. Their standard mode of operation can be traced back to Napoleonic Warfare.

Guerrilla warfare is an escape from fighting according to the rules imposed by the often far more powerful opponent. Therefore, this strategy is often applied by less powerful opponents. The most famous form is guerrilla warfare, next to terrorism.

Asymmetric competitor strategies could be an effective approach in business. Basically, it is not playing the game similar to the other companies, that is selling and marketing the same products as competitors but cheaper and better. It is about disruptive innovation, changing the rules in the market, by delivering a complete different product than you competitor does. It is all about gaining competitive advantage by creating an unique niche in the market. Playing another race at a different circuit.

There is much more to say about the embarrassing destruction of the mighty US Navy, as the over reliance on technological superiority and information dominance. It’s all about big organizations and the neglect of intuition about the intentions and capabilities of the competitor.


There is much more to say about the embarrassing destruction of the mighty US Navy, as the over reliance on technological superiority and information dominance. Also, the neglect of intuition about the intentions and capabilities of the enemy.

Disclaimer: Now you have heard  about the advantage of disruptive innovation or step-out innovation and decide that your organization should do “some of that.” But most organizations are designed to do something else very well. Namely, what they are already doing. You may have a brilliant vision, you may have identified the next great idea, but organizational routines, standard Key Performance Indicators and existing organizational structures will prevent proper execution: The company will will continue to do what they are already doing succesfully: ” a tiny bit better and a tiny bit cheaper?” See “Why Big Companies Can’t Innovate” by Maxell Wessel.

See also the video: Disruptive Innovation Explained by Clay Christensen.

Making Sense of Data

The introduction of computers and the Internet combined with an explosion in information have led to an overabundance and in many cases confusion. Determining what is facts, false information, opinions are becoming increasingly more difficult.

Finding ways to use thinking to overcome problems with abundance and faulty information is vital. So is inventing tools to make sense of data.

Designing a system that makes sense of data in a way that is novel and specific enough so that insights can be gained without human involvement has proved to be a difficult task. The last decades has seen major breakthroughs in the collection and storage of data but few advances has been made in sensemaking systems.

Jeff Jones suggests that it is fundamental that the system recognises when multiple references to the same item are being made. The data may come from different sources and it is crucial to distinguish between one person making one bank transaction an two people doing one transaction. But is it not enough to count things, actions and people, sensemaking systems must also make statements and use these to determine what or whom to notify is the new evidence is important.

Imagine that you cannot use your eyes to catch a Frisbee. What would you use instead?

The flight of the disc is predicted when someone throws a Frisbee and we use our previous experiences mixed with the velocity and the direction to predict where the Frisbee will end up. Usually your eyes and brain collects and make sense of these observations. But imagine that a slow motion Frisbee is thrown towards you and friends using Twitter, photos , stories, heat maps to tell you where it takes place,  the velocity and direction of the Frisbee.

Would you catch it?

We try to make sense of even more complex situations than the motion of a Frisbee. For example, emergency service may receive five calls from people reporting that a child is being abused. There could be one child that they could hear screaming or it could be five different children being abused.

Below is an example of using numbers to make sense of complex movements. maybe this will inspire some great thoughts about other ways of making sense of information, data or the world in general.

business man with glass bubbles

Quantum Juggling

The world of numbers is often described as serious and linking it to brightly coloured balls and a person clowning around may sound strange. Yet juggling and numbers have more in common than the first impression may suggest.

Colin Wright is a mathematician who was frustrated that there was no way to write down juggling moves so he helped develop a notation system for juggling.

A juggling move called Mills Mess required two and a half sides of A4 to write down and Colin thought that there must be a simpler way of writing down the juggling moves. The system devise that was developed is called Siteswap.

The system encodes the number of beats of each throw, which is related to their height and the hand to which the throw is made. Throwing a three means the ball spends two beats in the air and one beat in the hand before it is thrown again, while a four means the ball spends three beats in the air then one beat in the hand before it gets thrown again. The height of the throw is taken into account and the bigger the number the higher the throw. Even numbers are used to represent balls being thrown straight up and caught with the same hand, while odd numbers represent balls being caught with the opposite hand.

The sequence 333 means that the three 3 ball are used – each ball is caught with the opposite hand and there are three beats between the throws. The Siteswap system means that jugglers can share tricks without having to meet in person or filming themselves. Sharing tricks involving five balls or different height is rather tricky and saying the numbers 51515252 52 52 is easier to understand. The coding system has also lead to development of new exciting tricks – the notation means that pattern emerges and this can be broken.

More, More Information, Yes, Sure, But Relevant?

In this blog post, as you can see in the upper left hand corner, we will focus on the quality of information, an essentially white hat thinking activity. Quality of information as a distinctive focus area or Area of Improvement (API) could be vital for many information intensive enterprises, but also for any other thinking situation, such as drafting a plan, preparing a decision, exploring a situation.

We will take you along the mindmap below to explain this – clockwise. A mind map is a diagram used to visually organize information. A mind map is often created around a single concept, drawn as an image in the center of a blank landscape page, to which associated representations of ideas such as images, words and parts of words are added. Major ideas are connected directly to the central concept, and other ideas branch out from those.

Caught up in social ties

Look at the top and right hand corner of the mindmap: In most thinking situations there is a need for information from outside the standard pattern of logic and perception. We have to look for unexpected information. In order to do that, we should enlarge our perception of the situation, looking for more aspects in the situation, to diversify our thinking. CoRT-tools like the PMI, CAF or C&S are excellent tools to stretch our perception space around a situation in the mind map upper right hand corner. Especially helpful is to actively look for actors which could be involved or would affected.

Center right of the mind map: It makes a difference if information is needed or is given. Given information tends to be egocentric. Ego-centrism is characterised by preoccupation with one’s own internal world. Egocentrics regard themselves and their own opinions or interests as being the most important or valid. To them, self-relevant information is seen to be more important in shaping one’s judgments than are thoughts about others and other-relevant information. Nevertheless, given information can be very convincing and one can easily be lured in a narrow defined thought path. Also, information could be left out information, deliberately or by accident, Hence, it is very useful to do some perception widening thinking before  looking at the information available, before you get locked in the thinking pattern of the information given.

Right hand corner: Doing some preliminary perception thinking is even important when there is a need for information. Many people, when confronted with a problem, begin a broad search for information. They assume that enlarging the information space inevitable will lead to uncovering the information needed to solve the problem. By doing so, a lot of information waste is generated

At the bottom of the mind map: A far more better approach was suggested in our blog post Cassandra Information. There is a distinction between available information and relevant information.

  • Available information but not relevant could be left out. It is egocentric information from the sender of the information;
  • Unavailable information and also not relevant can be completely ignored;
  • Available information and relevant is Ebne: Excellent but not enough. This is information that belongs to standard thinking, unchallenged;
  • Relevant information but not available is Cassandra information. It is information that is left out by the information provider, but still relevant. The task is to design a strategy to obtain this hidden information.

It is a good habit to assume that any piece of  information that we have is biased. Especially, as we earlier showed in our post Press Patterns, information from the Main Stream Media: those media that disseminate information via the largest distribution channels, which therefore represent what the majority of media consumers are likely to encounter. The term also denotes those media generally reflective of the prevailing currents of thought, influence, or activity.

Business Woman Climbing a Pile of Files

Key Performance (mis) Indicators


Key Performance Indicators are meant to keep an organisation on track. By measuring the performance over time, you are able to look at deviations and to take measures. As Wikipedia defines it: A  key performance indicator (KPI) is a type of performance measurement. An organization may use KPIs to evaluate its success, or to evaluate the success of a particular activity in which it is engaged. Sometimes success is defined in terms of making progress toward strategic goals, but often success is simply the repeated, periodic achievement of some level of operational goal (e.g. zero defects, 10/10 customer satisfaction, etc.).

The concept behind Key Performance Indicators is to build a feedback loop between input and output. Its working principle does not differ from a thermostat, which senses the temperature of a system so that the system’s temperature is maintained near a desired set-point.


In order to get not market driven organisations more efficient the adage “The numbers tell the tale”has become fashion among governments, institutions and not-for-profit companies. There are several metrics or key performance indicators.

However, Key Performance Indicators can also lead to perverse incentives and unintended consequences as a result of employees working to the specific measurements at the expense of the actual quality or value of their work. In the social sciencesunintended consequences (sometimes unanticipated consequences or unforeseen consequences) are outcomes that are not the ones intended by a purposeful action. Perverse incentives are a type of unintended consequence. A perverse incentive is an incentive that has an unintended and undesirable result which is contrary to the interests of the incentive makers.

There are a lot of examples of bad designed Key Performance Indicators. We came across, but not exhaustive:

  • Police officers get a predetermined quota of fines to give out. The unintended effect of this KPI that the police organisation will be focused on easy to obtain files, f.i. traffic fines instead of fighting serious crime;
  • An organisation involved in handling objections has a KPI for the amount of rejected complaints. Imagine how employees will approach complaints. . .
  • It is generally accepted that the progress of students is evaluated by tests. However, student tests assess only a small part of needed knowledge, skills and attitude of students. Also, often the purpose of the test, timely warning of learning difficulties and study delays, dilutes to “a (missed) ticket to the next hurdle”;
  • An agency of child protection is responsible for placing abused or emotional neglected children in foster parents and child care institutions. It is very logic to design a KPI: like the number of placed children. If this performance is coupled to the financing of the agency, it can easily lead  to placing children out of their home, against sound indications that there is no need for or against parents objections;
  • It is complete reasonable to expect higher efficiency and experience of surgeons as a hospital performs at least 30 knee surgery or angioplasty a year. However, such a KPI can lead to more instead of less knee surgery and angioplasty, an example of a perverse effect contrary to what was originally intended (an intended solution makes a problem worse);
  •  The selling of mortgages as an end in itself, even to people who could no pay the interest, led to the bank crisis in 2008. Another example of a negative, unexpected detriment occurring in addition to the desired effect of the policy to motivate sellers to do better their best.
  • To increase the efficiency of university studies universities are judged on the number of successful students per year. It is now tempting to reduce the requirements for passing exams.
  • In order to increase the efficiency of General Practitioners many assurance companies allow for not more than ten minutes consults by patients. This KPI leads to far more referrals to medical specialists because GP’s have not much time to carefully investigate the medical complaints. This is an example of a counterproductive KPI: it is more of an “obstacle” than a help in the achieving of a productive project or an objective;
  • Crews of warships run annual series of nautical and operational exercises. Through a complex multi-factor analysis, a KPI is derived: Operational Employ-ability. Members of Parliaments asked questions when the KPI decreased to 10%, as a warship was actually deployed in a crisis;
  • Notorious are budgets: the setting of expenditure levels for each of an organization’s functions. It expresses strategic plans of business units, organizations, activities or events in measurable terms. However, such budget tends to be exhausted at the end of the year, because organizational units realise that they will be shortened in budget for next year, because last year they needed not the full budget. So, as an example, in many towns you can observe that every five to ten years the same streets and squares are completely overhauled without any need but in order to use the full budget.

Many Key Performance Indicators have unintended effects. They function as rules for behavior. Key performance Indicators are designed to notice need for adjustments of the course of an organisation. However, more often than not, they are invitations to cheat, by employees but equally by companies and institutions,  especially when financial consequences are attached to the KPI.

Whenever designing or encountering a Key Performance Indication, be warned!


unintended consequences

For more examples of perverse incentives, see here. For examples of unintended consequences see here.

To built up your Thinkibility skills, imagine your are the director of a hospice. You have set a thinking task: how to improve the occupancy (KPI) of the hospice. Then check your answers with How Dying Became A Multibillion-Dollar Industry.



Creative Data Collection

Data collection is the process of gathering and  measuring variables of interest, in an established systematic fashion that enables you to answer stated research questions, test hypotheses, and evaluate outcomes. The goal for all data collection is to capture quality evidence that then translates to rich data analysis and allows the building of a convincing and credible answers to questions that have been posed.


However, many research and policy are based on already available information that do  not necessarily fit to the issue or question. For instance, the average income of residents in a district is estimated at the average market value of homes. Suppose there are some big villas in a district. However,  the houses are rented to migrant workers who sleep with twelve persons in a room. Actually, the district has poor inhabitants and impoverishment is lurking. A better measure of prosperity in a district could be the amount of call shops, Travelex foreign exchange bureaus or percentage windows with bed sheets as curtains or without curtains at all. 

Perhaps we could use data of the local supermarkets to assess the risk of impoverish of a district, not only by sales volume, but also the kind of products consumers buy. Income groups differ in the food they buy. Supermarkets may have more or less variety in products they offer, regarding the population.


This could lead to a Reverse Open Data movement, where businesses make their data available for town halls to design social and economic policies. Open Data is a movement that  open data should enable third parties to leverage the potential of government data through the development of applications and services that address public and private demands. This information exchange could be made two-sided.

Perhaps we could measure the level of civilization of a nation by registering the percentage of cars that don’t stop for a pedestrian at a pedestrian crossing (a zebra crossing).

big mac

Another example is the Big Mac Index, a creative alternative to determine exchange rates, the rate at which one currency will be exchanged for another. It is based on the concept that a Big Mac is highly standardized all over the world. The difference in selling price in country A compared with the selling price of a Big Mac in country B gives a better idea of the value of the two currencies relative to each other.


Maybe we can say something about the tendency to conformity by counting people who wear clothes of a specific brand. Or determine the percentage women that is involved in street sweeping.


It’s hard to get solid data on drug usage, because it’s traditionally gathered via questionnaires. Respondents can fudge the answers or forget details. Drug users also sometimes don’t know what they are really taking or whether other drugs are mixed in. However, the laboratory analysis of waste water has the potential to get more accurate results more quickly, as a recent study showed that cities’ sewer water exposes use of cocaine, cannabis, meth and ecstasy.


It is interesting to roam in a town and create some mini theories that explain what is observed, compared with another town. For instance:

  • There are substantially more gulls and open torn garbage bags ;
  • Advertising is everywhere and very blatant;
  • There is a lot of green space and many squares;
  • All doors and window frames are painted in the same color;
  • There are many pizzerias.

What does it mean? Or what does it explain? Can you quantify the phenomena and turn them into meaningful data?


Uncertainty – Thinkibility Nibble


Often when we search for information we want to be certain that the results are true or we assume that the results are true and certain. But scientific uncertainty is part of scientific research. Since we do not know everything, research continues and it is constantly changing. New ideas and pieces of information is added.

  • Researchers have to decide “how much of the picture is known and how confident we can all be that their findings tell us what’s happening or what’s going to happen. This is uncertainty.“ (Making Sense of Uncertainty)

When a scientist describes the uncertain part of the research, we should be pleased rather than discourage an open discussion about the uncertainty. Climate science, disease modelling, and weather forecasting all have a degree of uncertainty. This is not a deficiency and it certainly does not mean that anything can be true. We may expect scientific research to be true and certain and it is this expectation that is the problem. Yet we still need to make decisions based upon the uncertain results and by explaining and estimating the uncertainty, we have a higher degree of confidence regarding what is known and unknown.

Ignoring results simply on the basis that they are uncertain prevents us from making decisions and taking actions. If we expect certain results, we will never make changes to prevent climate changes or develop new drugs. Complex systems, such as ecological systems or the human body, are not easy to understand and we may never have certain knowledge about what will happen. Identifying area of uncertainty should be part of any research map.

Scientists are developing research maps to help them deal with data deluge. Organising discoveries is vital to prevent duplicating experiments and to ensure that key discoveries are noted. A map makes it easy to see what areas that have been covered and the impact of the results to future studies. Neuroscientists have developed maps that show findings in molecular and cellular cognition and an app has been developed to help researchers to expand and interact with the map. The maps work more or less as an online query, where you can see as much of the maps as you like to. The map can be used to explore what information that is missing and it highlights areas that may be interesting to study.

Uncertainty is often used to dismiss results and undermine the evidence. We need to explore in what ways  our actions  is or is not affected by the uncertainty. When we make decisions for checking for fake passports at the airport, we need a higher level of certainty that it will work as compared to when we discuss policies to reduce the number of road accidents.

While uncertainty is not a barrier to taking action, there are  situations where we should not focus on the uncertainty of the research. In some cases, the aim is to test and see how well an observation can explain a certain theory that we have about the world. There is also uncertainty in the data that is collected and this is different from an uncertainty in the conclusions that is drawn. Different scientists can reach different conclusions when they examine the same set of data.

Uncertainty maps:

  • Identify areas of uncertainty
  • Possible factors that influence the uncertainty
  • The scale of the uncertainty
  • Ways to deal with the uncertainty
  • What does the uncertainty mean for a decision? Do we need to  make another decision?
  • Are there some other pieces of information that has different uncertainty?

Above all –  be suspicious when someone says that something is certain!

Photo:”Book Of Knowledge” by digitalart

Crowd Research

There are some fascinating developments which call for some “What If Thinking”.

Four technological developments

Nowadays more or less everyone is connected to someone via the Internet. It is assumed that any person can connect to another person via a friend of a friend, all it takes is six or fewer steps for anyone to be introduced to someone – it is a small world.

Stanley Milgram  explored the relationship in the Small World Experiment in 1967 and although the experiment have several weakness it is still a popular research topic. By the introduction of the Internet only Six Degrees of Separation are between you and  everyone on your mobile phone. Recent studies even suggest that the world has shrinked as a result of Social Networking such as Facebook and there may only be Three Degrees of Separation. We are and feel more connected to each other.


Soon all conceivable devices will also be connected. This means that a thousand physical quantities built-in (like length, or torque, or tensile strength, or clicks per impression), as well as nearly 10,000 units of measure (like inches, or meters per second or katals or micropascals per square root hertz) will be connected to the Internet.Those devices could be linked to a person  (a smart watch for instance), to a product or a process or linked to a GPS-position. If a standard exchange protocol, as proposed by the Wolfgang Connected Devices Project,  will be developed, a seamless integration of as many kinds of devices may be possible.

A third development is that we assume that the production costs of devices will be decreased by the use of nanotechnology and the trend of individuation of products will continue.  As a result of a reduction of production costs, several devices such equipments such as heart rate monitors, fitness equipment and  books,  are becoming more affordable for individual use. These items  were previously only available for organisations and groups, such as a hospital, gym or library,

A fourth development that will function as a kind of multiplier that will dramatically increase the mentioned developments. Manufacturers of devices will no longer offer a device plus its processor plus an infrastructure linked to that device. They will make use of the facilities the buyer already have. That is, a computer or a mobile phone, with all their data processing qualities and connections built-in. We will see that producers will adopt strategies that are derived from the biological concept of  symbiosis.

Crowd Research

Crowd research offers a great opportunity to explore possibilities and opportunities. Already we can see examples how those four developments or trends will interact and reinforce each other, especially what we call, by lack of better, Crowd Research

  •  SETI, a distributed computingproject in which volunteers donate idle computer power to analyze radio signals for signs of extraterrestrial intelligence.
  • In the Open-Source Bee Project a global set of sensors could give scientists new insight into the possible causes of Colony Collapse Disorder (CCD).  A cheap sensor could turn backyard beekeepers into an army of citizen-scientists
  • Zooniverse is a citizen science web portal owned and operated by the Citizen Science Alliance. The organization grew from the original Galaxy Zoo project and now hosts dozens of projects which allow volunteers to participate in scientific research. Zooniverse projects require the active participation of human volunteers to complete research tasks. Projects have been drawn from disciplines including astronomy, ecology, cell biology, humanities, and climate science. The Zooniverse community consisted of more than 1 million registered volunteers. The data collected from the various projects has led to the publication of more than 50 scientific papers.
  • eBird is an online database of bird observations providing scientists, researchers and amateur naturalists with real-time data about bird distribution and abundance.  eBird has been described as an ambitious example of enlisting amateurs to gather data on biodiversity for use in science. eBird is an example of treating citizens as scientists, allowing the public to access and use their own data and the collective data generated by others.
  • Tomnod took images gathered by their satellites and offered them to the public for viewing and identification in the disappearance of Malaysia Airlines Flight 370. 2.3 million people used the site to look for signs of wreckage, oil spills and other objects of interest. During the 2010 Haiti earthquake, OpenStreetMap and Crisis Commons volunteers used available satellite imagery to map the roads, buildings and refugee camps of Port-au-Prince in just two days, building “the most complete digital map of Haiti’s roads”

Emerging Crowd Research

We may speculate that the availability of cheap devices linked to mobile phones will increase crowd research exponentially in nearly every area of human activity.

The Quantified Self is a movement to incorporate technology into data acquisition on aspects of a person’s daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousalblood oxygen levels), and performance (mental and physical). Such self-monitoring and self-sensing, which combines wearable sensors (EEGECG, video, etc.) and wearable computing. Quantified self is self-knowledge through self-tracking with technology. Quantified self advancement have allowed individuals to quantify bio-metrics that they never knew existed, as well as make data collection cheaper and more convenient. One can track insulin and Coriolis levels, sequence DNA, and see what microbial cells inhabit his or her body.

If the collected data are shared, imaging what hidden cause-effect relations will emerge foe example, between life style, geographical area, and food consumption. Architects could use the data to design better buildings, routes and cities. The data can be used to design office layouts that stimulates physical exercise. The data could be used to monitor healthy persons, which could lead to changes in medical science which is per definition based on ill people. It can be used to map the spreading of viruses. People could compare their work pace with others in the branch and in other branches. Scientific disciplines as psychology and sociology would be freed from unreliable research methods like interviews and questionnaires.

 What if dreams are massively recorded on a world scale? Do poor people dream about other things than rich people? Are Japanese dreams different from dreams in Africa? Shadow: Community of Dreamers, crowd financed with $82,500, wakes people up with an alarm, prompts them to anonymously describe their dreams, and beams those reports into a massive online set, where they can be searched and analyzed. Dreams are coded for age, sex, location, and time.  

What if there are cheap devices that measures the quality of tap water or swim water? What if people near Fukushima are no longer dependent on radiation levels from the government or TESCO because there is a cheap device that in combination with a mobile phone share information about radio activity? If many, many people have their own weather station and are plugged in a network, would it not enhance farming at a huge scale? What if anybody with a mobile phone could recognize a sought or missing person?

What if cars have an on-line device that measures the air quality, but also will display that level of air pollution at their rooftops ? Would it lead to “air pollution traffic control”? Wouldn’t it be confronting and provoke to action by citizens?

air quality

All cars have an indicator on their roof that shows the level of pollution: low, medium, too high

Ultimately, we may see an enormous democratising of information that till now has been  monopolised by institutions  and governments and, as history shows,  often a lot of data and information has been denied or hidden from civilians.