Digital technologies are changing business, government and society worldwide. Clearly, they’re opening up new risks and opportunities for every sector of the world economy. Such “futurology” may offer you the big picture, but what does a digital world mean for you, personally? Will you be ready for an automated, AI-assisted, big-data-driven employment future? This course provides you an answer to these questions, and it does so from a unique perspective: by introducing you to the world of intelligence analysis. First, this course explains some of the skills that will command a premium in the digital age, and why. Then, it offers you mental models and practical frameworks developed by the US intelligence community to give you a cognitive edge understanding the digital world. This edge is not about spying or secrets. It’s about better thinking. This analytic toolkit has nothing to do with tired, static MBA-style strategy frameworks. Instead, these tools to help you come to grips with the volatility, uncertainty, ambiguity and deception of the digital age. Ultimately, this course makes the case that as the world becomes more digital, your future success depends most of all on asking better questions of both yourself and others. Therefore, it teaches you how to adopt an intelligence analyst’s question-asking mindset. In short, take this course to acquire a sustainable business advantage through clearer, more structured thinking.
Question Clustering
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From the course by IE Business School
Intelligence Tools for the Digital Age
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From the lesson
The Intelligence Analyst’s Mindset
Meet the Instructors
Milo JonesProfessor at IE Business School
Geopolitics in the Digital Age
Okay. Let's get started,
and let's get started with theory.
Now, you're going to say, "Wait, I thought this was supposed to
be practical," but theory,
I always tell my students and I genuinely agree,
theory done well is intensely practical.
In some ways you can think of theory as sort of like iron filings,
when trying to figure out the fields of a magnet.
That theory will help you see things that you otherwise might miss,
and help you notice forces at work that you otherwise might not see.
We're starting with something called tasking.
If you'll remember back in module one,
I talked about the importance of asking good questions,
and tasking, is really this idea in intelligence,
that you need to sit down and not just collect everything.
You need to figure out,
what do I need to know?
Which is in itself obviously a question,
but ideally what you're looking for is clusters of questions that
shed light on the sorts of problems you're trying to analyze,
and here we immediately bump up against a problem
because we talk a lot about intelligence analysts,
but the fact is,
good question clusters are usually put together not just by analysis,
which as you know from your reading,
actually it's from the Greek word analine,
which means to break up.
Analysis is breaking things up.
To ask good questions,
you've also got to synthesize,
which means to bring things together.
So, we're talking about question clustering.
In other words, creating small question,
subsets of a larger question that you're trying to
answer to solve a particular problem, and you're asking,
"How might I create a good question cluster,
a group of small answerable problems that bear on some larger question?"
There are two techniques I know of,
but before we go into those,
take a minute and tell me how you might think about asking better questions.
The first technique I want to talk about for asking better questions,
creating better question clusters, is synthesis.
Now, the root of our word to analyze actually means to break up,
but good intelligence analysis, ironically,
actually involves a lot of synthesis,
which is putting things together.
You want to think about when you're synthesizing something,
bringing in ideas from diverse sources and
bringing intelligence from diverse sources and putting it all together,
not breaking it up.
So don't just think about breaking things up, think about synthesizing.
Another tool for good question clustering is using analogies.
An analogy is sort of like saying,
"This question reminds me of x,
or this situation reminds me of y."
When you're doing that, you want to think about both the similarities
and the differences of the analogous situation.
But finally, you are going to be working towards what we call question triage.
You're going to have a bunch of little questions,
and you want to break them up,
by triage is frankly
a rather unpleasant and sad process
when sorting wounded people from who's definitely going to die,
to who's definitely going to survive,
and who can we productively work on.
Similarly, when thinking about questions in intelligence analysis,
a good intelligence analyst will say,
"We've got a bunch of questions
clustering around the big question we're trying to answer,
but some of them frankly are impossible to answer,
so let's lay those aside."
That's part of question triage.
But you've also got a bunch of questions that are pretty easy,
so let's take those.
Then let's focus our main efforts on answering
the challenging questions that are both hard but also answerable.
To sum up this whole part,
good tasking is somewhat like making a good hamburger frankly,
you need butchers who cuts stuff up, who analyze things,
create a lot of little questions from obvious things,
but you also need bakers to make the bread,
to synthesize things, to put things together.
You really do need both a butcher and a baker to make a good burger,
but you also need,
frankly, different types of intelligence that are you
can think of is maybe the lattice and the tomato and other things on a good burger.
But ultimately, in tasking you're trying to say,
what do we want to know,
and what are the subsets of what we want to know,
that cluster around that big question?
A good intelligence analyst is quite
skilled at making those judgments and performing sort
of some triage on the sorts of questions that they need their team to answer.
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