Analysts Arise – the Analytics Age is Nigh!?
Posted on November 2nd, 2009 by Paul McArdle – 5 Comments.
Paul Klaptocz pointed me at this interesting blog post from Stephen Few entitled “Malcolm Gladwell, modern problems, and the analytics age”.
With us having read two of his books many months ago (Blink and the Tipping Point – sorry, no book reviews up yet) and having previously discussed the follow-on from his 3rd book (Outliers) in my post about the 10,000-hour rule, I was curious to read further.
What it means for us?
Let me start by noting:
1) Stephen Few’s post itself, and the commentary afterwards, is well worth reading, but
2) I will summarise a few of the key points here – mainly for internal consumption (though, of course, we’d welcome your comments).
I agree with the main point of the article, which is summed up in this excerpt (with my emphasis added):
The problems that we face today, both big ones in society like the current health care debate and smaller ones like strategic business decisions, do not exist because we lack information, but because we don’t understand it.
They can be solved only by developing skills and tools to make sense of information that is often complex. In other words, the major obstacle to solving modern problems isn’t the lack of information, solved by acquiring it, but the lack of understanding, solved by analytics.
After all, I’d have to agree (you might say) - I have built this company around just this principle! It’s in our tagline:
we make the electricity market understandable
(and to a wide range of people, not just the usual suspects!)
What does that mean to our business - it means that, for us to succeed, we all need to develop (as best we can - keeping mind mind what I’ve noted before about personal preferences) our own analytical mind.
1) This does not mean we need to all think like NEM-Review (our more traditional statistical analysis package),
2) I believe it is quite often easier to see things ala NEM-Watch (i.e. by graphical presentation). What’s the key to NEM-Watch? It is the fact that the human brain is still loads smarter than any algorithm, and hence can more easily see patterns in separate data sets - so much easier if the data is presented intelligibly.
This ties in with Stephen’s comment:
They must switch from an engineering-centric worldview, focused primarily on technology, to a design-centric perspective, focused primarily on the human beings who actually work with data.
Only then will they be able to build effective analytical tools that take advantage of human visual and cognitive strengths and augment human weaknesses.
Hence, the people who deliver the most value in our company will be the ones who can best adopt this new perspective - which you get by focusing on learning how our clients think, what keeps them awake and night, and how to alleviate these stresses…
You must, however, have the soul of an investigator and a flexible, analytical mind. You must be able to think critically.
Hence the absolute necessity for everyone to be committed to their Guru Plans.
I’m reading this pretty early so perhaps my brain isn’t switched on, but I’m confused about how exactly this relates to our guru plans?
In two ways, Adam:
1) In whatever areas people choose as the focus of their plan, the simple act of establishing and following through on the plan will stimulate a lot of analytical thought that will put us all in better positions to see new opportunities for us in the market (i.e. your “practical PhD” will continue from university in teaching you to think - and hence lead to more insight). This will increase everyone’s ability to be in a position where they:
2) It may be that someone actually chooses to focus their plan on topics such as the analysis of the electricity market (or on the clear display of quantitative/qualitative information), in which case there would be both direct or indirect benefit.
Make sense?
“Make sense?”
Not really.
It’s not that what you’ve said doesn’t make sense, only that what your post was about seems to have no real relevance to the Guru plans. The second point you made ties it back to the guru plans a little bit, but did not really explain why it is “absolute necessity for everyone to be committed to their Guru Plans.”
It seems to me that if anything a guru plan will create a number of specialists who will not have the broad knowledge required to have “a flexible, analytical mind”. Thinking critically is a prerequisite for being a programmer really. It is, for example, impossible to understand when to use a balanced binary tree and a linked list without being able to think critically.
Apologies guys,
I realise (after speaking with a few in the office today) that my explanation was not clear.
What I mean to say is that, at each stage of someone’s “learning journey” (institutional and/or experiential) they progressively improve their capability for analysis:
1) Perhaps, at the end of high school you are 3/10
2) Perhaps, at the end of undergrad, you are 5/10
3) Then, with the Guru Plan, you should be focused on improving this capability to 8/10
The value for us, as a company, in having everyone at 8/10 is that everyone will more easily/quickly/consistently see connections in separate data sets - for instance:
1) in terms of NEM data from different providers; and/or
2) to “read between the lines” when listening to clients talk about their business (to identify new product opportunities).
In simple terms, following through with a Guru Plan should drive your thinking deeper.
In this sense, what you focus on is almost secondary to the fact that you focus on your Guru Plan in the first place.
Just like a trading company will value a trader much more highly if they can more easily/quickly/consistently make these kinds of connections, so will we (as it will lead to business growth opportunities that we otherwise would have missed).
In terms of “making things understandable”, I obviously I come out with an “F” in this instance!
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