When are SMART goals not so smart?

Like many of you, I know about and use SMART goals in my work with individuals, teams, and organizations (see more here: SMART).  The research shows that people, when they set SMART goals, are more likely to achieve them.  By analogy, I often reason that when teams or organizations set SMART goals, they too will be more likely to achieve them. But does this always hold?  Is this true for individuals, teams, and entire organizations under all circumstances?

I would suggest that there is a constraint or assumption embedded in this approach: control. Are factors which enable achievement of the goal within our control?  Which factors are in our control and to what extent are they? One can see this embedded assumption in the "Realistic" and "Attainable" characteristics of SMART goals.  For surely our assessment of how "realistic" and "attainable" the goal may be is grounded in our sense of our control over factors influencing achievement of the the goal, regardless of whether or not that sense is explicit in our thinking.

It is this sense of control that leads me to question under what conditions or circumstances might SMART goals NOT be so smart?

Control is a word I associate with a very simple and mechanistic view of circumstances or environments.  It is a view that says the world in predictable, a view where I feel I understand cause and effect.

For example if my widgets are manufactured by machinery and processes I understand well and I, my team, or my organization set a goal to produce a specific increase in the number of widgets by a specific date then I can easily form a plan to scale to increase production.  I have control of the factors that will lead to the achievement of the goal.  I understand cause and effect and can predict the results of my efforts.  I can safely create a SMART goal focused on the outcome of increased production.  The materials, machines, and processes have no will of their own, do not need to participate in the development of the goal, nor agree to it.  There is no emergence present in the environment.  The more mechanistic or deterministic are the factors and processes, the more I understand cause and effect, can predict outcomes, and the greater the control that will at least be possible.

If, on the other hand, the circumstances or environment are less simple and more complex where the relationship of cause to effect is less well understood and the outcomes of my efforts are less predictable, then less control seems possible.

David Snowden, currently with IBM, created a useful topology for describing circumstances or environments called the Cynefin framework described below (See Cynefin on Wikipedia).

"The Cynefin framework has five domains.^[12] The first four domains are:

• Simple, in which the relationship between cause and effect is obvious to all, the approach is to Sense - Categorise - Respond and we can apply best practice.

• Complicated, in which the relationship between cause and effect requires analysis or some other form of investigation and/or the application of expert knowledge, the approach is to Sense - Analyze - Respond and we can apply good practice.

• Complex, in which the relationship between cause and effect can only be perceived in retrospect, but not in advance, the approach is to Probe - Sense - Respond and we can sense emergent practice.

• Chaotic, in which there is no relationship between cause and effect at systems level, the approach is to Act - Sense - Respond and we can discover novel practice.

The fifth domain is Disorder, which is the state of not knowing what type of causality exists, in which state people will revert to their own comfort zone in making a decision. In full use, the Cynefin framework has sub-domains, and the boundary between simple and chaotic is seen as a catastrophic one: complacency leads to failure."

Using this framework, it would seem that SMART goals only make sense in either "Simple" or "Complicated" circumstances not in "Complex" or "Chaotic" circumstances nor those in "Disorder". 

I would suggest, given that emergence is a key characteristic of complex environments, and in those circumstances one cannot control or predict the results of one's efforts, the appropriate use of SMART goals would not be to set specific outcomes as goals.  

In the case of complex environments, one can only influence the outcome by creating conditions under which the desired outcome is more or less likely to occur.  For example, a farmer cannot control the growth of the crop but only prepare the soil, select the seed, fertilize, and water it - in short, create the conditions that are most likely to help the crop grow.

In complex circumstances or environments, it would be best to set SMART goals on the creation of the conditions more likely to produce the desired outcome rather than the outcome itself.

Leaders, their teams, or their organizations should seek first to understand what manner of circumstance or environment they wish to affect, complex, complicated, or simple and only then set SMART goals that are appropriate: goals focused on outcomes under simple or complicated circumstances and goals focused on conditions that influence outcomes under complex circumstances.  

I have helped many people and organizations set SMART goals for outcomes under complex circumstances or for complex environments and have set them up for failure. Understanding what is possible and under their control will help me advise them better in the future.  I hope it will help you as well.