zaid hassan has been working on 'complex' challenges like public healthcare, climate change, and state collapse.
he wrote a book on his learnings called the social labs revolution: a new approach to solving our most complex challenges
our societies are getting more complex
- things are emergent, the trajectory of society is unpredictable
- as a result of emergence, we tend to generate massive amounts of information on our society
- chief scientist @ IBM: "the amount information in the world is doubling every 2 years"
- when trying to address a complex situation, it's impossibl to know everything.
- we feel that we don't know enough, so we do more analysis, math, etc., before we feel we can proceed
- as a result of emergence, people tend to change their behavior autonomously
everything is invariable, fast-changing, accelerating. we must design for this.
our dominant response is planning, and planning doesn't work.
planning has a 90 - 100% failure rate in all situations
what determines failure?
- is it on time?
- is it on budget?
- is it in scope?
planning fails because its predictive and we're operating in an environment where prediction doesn't work very well.
bad news because, most of our resources go towards planning.
we have a different response: experimentation
in cancer research ..
no donor would go to a cancer researcher, and say, i'd like you to come up with a five-year plan. tell me what inputs you're going to use, and what outputs you're going to produce, and you've got five years to come up with a cure for cancer. and if you don't do that, your funding is going to be at risk.
in a lab-based / experiment-based space ..
- not investing in a plan, investing in a team
- if you can bring together people with talent, than you have hope.
- methodology used in startups, entrepenuership, medicine, science, engineering
we must invest in teams that will eventually produce value, but its very difficult to predict what that value is.
in NGOs, team is a sidenote. somewhere in the appendix of the plan.
how do we increase success rates of response to complexity?
- the response has to be social
- the people that are impacted by the situation have to be involved in designing a response
- planning response: assemble a small group of technocrats to create a solution, and trickle it downwards. neo-soviet response
- the approach has to be experimental
- trial/error, try things, see what works, ramp up investment based on the evidence you get back
- must have a portfolio of responses you can try
- planning response: all eggs in one basket
- the response has to be systemic in its attitude
- address situations at the level of cause
- what's causing ____?
- no formula for this, its just a way of thinking
given these characteristics, probability of success should go up
lean and agile have it right -- operate on short feedback loops.
feedback is critical, where does it come from? in a market context, this is clear. look at your users.
in a social context, this is a bit harder. how do you know something is working?
- observation: a push for metrics. we're funding things that largely fail, so rationally, we shoulnd't be funding them. decisions to fund strategic planning are not made on a rational basis.
so on what basis are they made? dominance of funding culture. donors need to be pushed / challenged to shift this culture. donors must realize the futility of strategic planning in complex social situations.
an analogy:
- you are hired by someone to win the lottery (odds are 14mil to 1), who wants the odds to be 50%
- response 1: "what? you're crazy. things dont work this way"
- response 2: you make it up. come up with a series of activities and interpret them in a way to appear as if the odds are 50%.
in a neo-soviet system, you have to game the system. donors are asking for something that makes no sense.
hassan likes to ask donors, "what's an acceptable failure rate?". donors typically say "50%".
henry mitzberg, professor at McGill: 20 years ago, wrote a book called: 'the rise and fall of strategic planning'
planning works in situations that are technical in nature
- clear problem definition
- clear solution definition
putting someone on the moon
- problem and solution are clear
- variables don't change. laws of physics, etc. are a constant
mental health
- problem and solution are not clear
- our knowledge of mental health is always changing
when things get really bad, people think, "well, clearly we've got to do something different now, because things are devolving so rapidly, people are dying, it's just terrible, we must do something innovative and different."
that hasn't proved to be the case. what tends to happen in this situation of crisis is actually the opposite. when you join the army, the way you're trained in bootcamp is through repetition. you're basically asked to do the same task again and again and again, to build muscle memory. the idea there is that, when you're in a conflict or you're in a crisis, your head will disassociate, and your muscles need to remember what to do in that situation ... planning is muscle memory. it's what we're trained how to do.
what i've found is that when situations become worse and worse we tend to fall back on muscle memory. so instead of going "wow, this situation requires innovation, because what we're trying isn't working", we tend to fall back on what we know how to do ... in an institutional context, that's typically planning ... what you're trying to do, is to break muscle memory
so what breaks muscle memory? events. events that force institutions to realize that their behavior must change.
we must create events that rupture muscle memory. events that create a situation that people are forced to respond to. we must create events that can't be ignored.
no idea.