Before you read any more of this blog post, please watch the video below (even if you think you have seen it before).

(Video courtesy of http://www.dansimons.com/videos.html)

As the developers of this experiment, Christopher Chabris and Daniel Simons, emphasize in their book, The Invisible Gorilla: How our intuitions deceive us, the key message is that we are strongly biased to only see what we pay attention to and what we expect to see.  They call this inattentional blindness (blindness to what we do not pay attention to).

A related experiment demonstrated that the percentage of people who fail to see a prominent, but unexpected, object directly in their field of view increases to 90% when the complexity of the ‘attention’ task increases.  In other words, the likelihood of inattentional blindness increases if we need to concentrate hard to pay attention.

Now let us translate these findings to the Observe phase of Adaptive Iteration.  Adaptive Iteration applies primarily to situations that are unpredictable, uncertain and emergent – precisely the situations in which the unexpected may occur.  Add to this the characteristic that these situations are usually complex – unclear cause and effect relationships, many elements, interactions and decision points, dynamic context, etc – and require much effort (attention) to attempt to determine what is happening.  So, in these situations, we have a relatively high likelihood of something unexpected occurring at the same time as we need to concentrate hard to attempt to understand what is happening.  We have the perfect conditions for inattentional blindness.

What can we do to reduce the potential for inattentional blindness?  I think there are several things:

• Deliberately observe the situation from multiple perspectives. I have summarized this approach, including a range of observational perspectives, in a previous blog post.
• Separate, as much as possible, understanding the situation from observing the situation.  We can reduce the distraction of attempting to analyze and understand the situation by separating it from the effort to observe the situation.  We focus on observing what is happening rather than attempting to explain what is happening.  In particular, we suspend our theories and preconceptions so that we do not focus on those observations that confirm them.  (This point summarizes one of the key reasons why we have explicitly separated Observe and Interpret in the Adaptive Iteration framework.)
• Capture a data rich record of the situation.  As with the basketball situation, if we capture a data rich record we can replay it multiple times so that we can observe things that we may have missed.  Replaying the basketball video provides very strong proof that a gorilla did walk through the players even we are convinced from our initial observations that it did not.   One word of caution with this approach – we need to ensure that we do not focus our data capture only on those things that we think beforehand are relevant and important.  This will formalize our observational bias.  The record capture needs to be as broad, detailed and unbiased as possible.
• Don’t attempt to understand the situation – just focus on what is and what is not working.  Many unpredictable, uncertain and emergent situations are so complex that it is impossible to understand and analyze them in detail.  Often, we should just accept this and rather than attempting to understand and explain the dynamics of the situation, focus on what is obviously working and and what is obviously not.  During the subsequent Interpret phase of Adaptive Iteration, we can then identify what sort of things we can do (design changes) to promote that things that are working and to suppress those that are not.
• Use multiple observers, some of whom are not specific experts.  The researchers experience with the basketball video is that approximately 50% of observers see the gorilla walk through the players.  Increasing the number of observers will increases the likelihood that at least one observer will see the unusual and unexpected.  However, it is important that there is diversity among the observer.  Especially, it should contain some people who are not experts in the situation (see earlier blog post) and there should little or no opportunity for the group to develop ‘group think’ beforehand.
• Practice mindfulness. Sam McNerney in an article in TheCreativityPost highlights research that suggests that  mindfulness, defined as “paying attention to one’s current experience in a nonevaluative way,” may provide an effective means of observing a situation or circumstance without seeking to confirm our intuition and expectations.  In other words, by being consciously aware of our own perceptions and thoughts we can learn to recognize and compensate for the filters they place over our observation and attention.
• Iterate rapidly.  The iterative nature of Adaptive Iteration means that we do not have to be ‘right first time’.   If the unusual or unexpected event is not just a result of natural variation in the situation (i.e., ‘noise’), it is likely to occur again in a future iteration, especially if the iterations are rapid and involve relatively small design changes.  Although this is not the main benefit of rapid iteration, it is a significant one.

We are conditioned to see what we expect or are primed to see, not what is really there.  This is fast and efficient if our world is stable and predictable where the past is a good predictor of the future.  But what if it is unstable and unpredictable?  What if our expectations and experience are only partially useful?  The problem is that our expectations and experience are often deep within our subconscious mind.  It is difficult to switch them off even if we consciously realize they may be inadequate in a given situation.

How then do we see things as they really are, not as our subconscious would like or expects them to be?  One of the most effective things we can do is to develop the ability to step through a variety of perspectives when examining a situation.  In doing so we use our conscious brain to counter or supplement our subconscious brain.

In general, we need to adopt perspectives that allow us to be more empirical.  That is, we need to focus on more extensive observation and data gathering before drawing conclusions.  In most cases, we also need to recognise that the conclusions are only hypotheses that require further testing and validation.  We need to be open to revising, or even discarding, a hypothesis as we make more observations or collect further data.

I have categorised the various perspectives we can take under four broad categories – spatial, structural, psychological and effectual.

Spatial perspectives

Get close to the action to see actual behaviour and events rather than make assumptions based on past, prescribed or ‘normal’ behaviour.  This approach underpins the Genchi Genbutsu (“go and see”) principle of the Toyota Production System.

Move further away from the action so that you can see behaviour and events in a wider context (draw wider system boundaries) and therefore consider more structural influences and factors.  Moving further away is also likely to increase detachment and objectivity and therefore reduce any biases introduced by an emotional engagement to the situation.  The movement need only be psychological (for example, by imagining you are in another city), not necessarily physical.

Divide the situation into a comprehensive set of segments and examine each of them separately and then the relationships between them.  This approach reduces the risk that your focus quickly narrows on those aspects that you expect or assume to be the most salient.  It ensures that all aspects get at least some focused attention.  The segmentation basis could be physical, organisational or temporal (time based).

Examine the behaviour at the boundaries of the system or within the system.  New or changing influences and behaviours will often be first evident at the boundaries.  This is either because new external influences first interact with system at the boundaries, or because the more diverse interactions that occur at the boundaries generate new ideas and options.

Structural perspective

Consider the network aspects of the system or situation.  Are there any groupings or networks emerging?  If so, what are the ‘attractors’ for the groupings, or what is driving the linkages for the network?  Is there potential for these to be self-reinforcing, or are there likely to be fundamental constraints to their ongoing development?  On the other hand, what are the established networks and groupings?  Are they structured to facilitate or inhibit positive change?

Identify the constraints in the situation.  The constraints may relate to physical boundaries, information, expertise, resources, awareness and expectations.  If behaviour consistently occurs at or near a constraint, the behaviour is unlikely to change without first relaxing or modifying the constraint.

Look for any potentially significant decision points.   Major decisions create ‘forks in the road’ that influence the future development of the system or situation.  At the personal level, they include choice of a partner, a profession/career, a place to live, etc.  At the organisational level, these decision points are numerous and diverse and may not seem particularly significant initially.  However, they may stimulate or facilitate a self-reinforcing chain of events that eventually have game-changing impact.

Identify any emerging patterns of cause and effect.  Even though the situation appears essentially unpredictable, repeatable cause and effect patterns may be emerging.  Customers in a given segment may have begun to respond more predictably to on-line promotions.  Middle managers from one segment of the organisation may be exhibit similar resistance to a change initiative and offering suggestions for improvement that have a common underlying theme.  These emerging patterns provide early indications of what is working and what is not.  They provide potential guideposts for future action.

Behavioural/psychological perspectives

Look at the situation through the eyes of the key participants.  In other words, take a perspective of empathy.  Aspects of the situation that may be clear and positive to you may be unclear, uncertain and therefore threatening to some of the participants.  Benefits of a change initiative that you think are valuable may appear to be of marginal value when seen through the eyes of a stakeholder group.

Identify the dominant motivations and influences in the situation.  Look for the ‘why’ as well as the ‘what’?  Where do the energy and driving forces for action come from?  Are they derived from proactive aspirations or reactive defensiveness?  Is the source local or broadly based?  Is it likely to be enduring or short term?  In emergent and unpredictable situations, the driving influence is a potential source of consistency and coherence.  Although it will not enable future decisions and outcomes to be predicted with certainty, it will point to how they are likely to be biased.

Is the situation characterised by a few dominant emotions?  Emotions have a fundamental influence on behaviour and decision making.  We may be able to bring some clarity to what appears to unpredictable and illogical behaviour when we understand their emotional underpinning.  Looking at a situation through a lens of emotions may provide insights that we may find it difficult to discover otherwise.

Effectual (effects and results) perspectives

Notice what seems to be working.  Where are successes happening?  What activities and behaviour are being reinforced?  Where are people making progress in spite of their constraints and context?  What have they done to overcome the constraints?  Is this repeatable and scalable? In unpredictable and emergent situations we cannot rely primarily on what has worked in the past or has worked somewhere else.  We need to discover new principles for success.

Be alert to the surprising and the unusual.  Often, much ‘information’ is found in the unexpected events, behaviours, relationships and achievements.  These may be weak signals of the emergent direction of the situation, or they may be just random noise.  If it is random noise, and the surprise is a positive one, can the random conditions be identified and repeated consistently?  The earlier the small surprises can be identified, the more likely it is that they can be purposely enhanced if they are positive or suppressed if they are negative.

Have you ever sat in a meeting and heard two attendees discuss the same topic on entirely parallel tracks?  Or perhaps you have been in meetings where an attendee keeps bringing the conversation back to a clearly inappropriate or irrelevant perspective.  Both situations are confusing and embarrassing for the other attendees.  Why do intelligent and competent people have such conversations?  Why do they miss the point so badly?  Why do they continue, even when the disconnect is obvious to others?

The old saying, “when all you have is a hammer, everything looks like a nail”, gives a clue to one of the key causes of the ‘parallel conversation’ problem.  Our professional training and experience colours the perspective we bring to any related context.  This is particularly so for deep and successful experts.  Their narrowness of perspective is reinforced not only by confidence gained from success but also by the need to defend and preserve their reputation and ego.

Such expertise based narrowness of perspective is a significant problem during the Observe stage of Adaptive Iteration.   Adaptive Iteration is applicable when the situation is unpredictable and emergent, precisely the situations where preconceptions and narrow perspectives are most risky.  During the Observe stage we need to be open-minded, empathetic and sensitive to both detail and trends.

Does this mean that experts should not be involved in the Observe stage of Adaptive Iteration?  Not necessarily.  However, it does mean that we need to think explicitly about how we organise for and go about observing our experiments, not only to reduce the potential for expertise bias, but also to reduce the risk of other forms of unconscious biases (more on these in later blog entries).

The types of things we can do to reduce the potential for observation biases include:

• T-shaped people:  Include people on the team who have not only deep expertise but also broad interests and knowledge and the ability to collaborate with people with other types of expertise.  These are becoming known as ‘T-shaped’ people.

• Multiple perspectives:  Explicitly observe the situation (experiment) from multiple points of view.  The objective here is to quieten our unconscious biases by adopting one or more conscious biases.  I will explore a variety of possible perspectives in a future blog post.

• Diverse team:  Include people on the team with a range of expertise and from a range of backgrounds.  Diversity reduces the potential for observational bias only if the team dynamics enables the diverse observations to be surfaced, discussed and synthesized.  The ability to do this depends on a mixture of structure, process and personality.

• Prepared mind:  Train (prepare) your team to be a better observers.  As Louis Pasteur is reported to have said, “in the field of observation, chance favours the prepared mind”.  Techniques for preparing the mind include learning how to suspend judgement, to implicitly adopt multiple perspectives, to appreciate the impact and role of context, and to see the underlying systems dynamics.  Interestingly, research is starting to suggest that our ability to have empathy (critical when observing many human interactions) can be increased by reading emotionally engaging fiction.

• Focus on data:  Where possible capture rich data to lead, inform or validate human observations.  The complex, unpredictable and emergent nature of situations where Adaptive Iteration is applicable means that is usually not possible to rely solely on data for our observations.  Nevertheless, some situations are amenable to supplementing observations with techniques such as video recordings or with the analysis of (often large) data sets to reveal emerging patterns, trends and relationships.