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Stenberg’s intelligence theory
Before I explain my point of view, let me introduce you shortly to Stenberg’s theory of intelligence, nicely summarized in this picture below
The three types explained above are pretty much explanatory in the picture above (source: lumenlearning). But what is the relation ?
The reason I bring this up is because the picture above can help us explain why despite a massive demand of analytics professionals, there is a massive pool of graduates, coming out of (now thousands of) Data Science and Business analytics programs, are either unable to find desired roles or end up disappointing their managers in their new jobs.
Its “Groundhog Day” in the world of Analytics
” Groundhog Day is a Hollywood movie in which the central character, Phil Connors, becomes trapped in a timeloop, that forces him to relive Feb 2nd repeatedly. Something similar is happening in the way we are trying to leverage analytics.
To understand it, you need to start with looking at the programs in Data Science and Business Analytics. And remember, I am not blaming the programs. These programs are expected to provide the “foundational skills” and they do so. So here is a challenge -pick any ten graduate programs in Data Science (Top ten or randomly). Now compile a list of all the case studies and applied examples leveraged in the curriculum across these ten programs, in a single list. You will be amazed to see how amazingly similar they are. Different programs, different universities, different “branding” of programs- yet, the example case studies are all around similar themes. Data or narrative may be different.
Here also, you can’t blame universities. They pick case studies or business problems that are most widely used, like churn detection, price predictions, customer segmentations etc. Afterall, their job is to provide foundation for solving the “frequently encountered” problems companies solve leveraging Advanced analytics.
It is just that companies have been solving the same problems, repeatedly, for decades- they are reliving Feb 2nd year after year. The methods, tools, algorithms keep on getting more advanced, I must admit.
And there are already plenty of experienced people solving these problems
And there are already plenty of people solving these problems that have been solved 1000 times, and have been doing it for decades. That does not mean fresh talent is not needed. Afterall, no one wants to manage and run churn detection models for decades. They want to move to senior, leadership roles. Fresh supply of talent is necessary. But if you are looking for this fresh supply only for the problems for which models and algorithms have existed for years (yes, no matter what “modern AI” hype you throw at it), then the opportunities for new grads become limited (and so do opportunities for companies as well).
And that is why we see disappointments among the newly minted graduates who are not able to land the jobs they dreamed of. They are already taken and have been taken for years now.
The Analytical Intelligence fallacy
And now we will slowly start getting into Stenberg’s Intelligence theory !
The issue at heart of the problem mentioned in the previous section is the focus on Analytical intelligence for decades in the corporate world. Analytical intelligence, as indicated above in the illustration, is the intelligence that allows us to do analytical problem solving and computation.
The challenge with this, is that if you focus primarily on this aspect, this type of intelligence works best when you have a defined problem. This is how all the “typical” case studies like predicting prices, churn detection, assortment optimization etc. etc. originated. The problem type got defined decades ago. We know exactly what type of algorithms need to be leveraged. Technological and computing power advanced allow us to solve more complex problems in these areas, but these are well known.
Yes, you still need folks with high Analytical intelligence to work on them. But as mentioned, these problems, and hence the job market for these, have existed for decades and is not the area where there is scarcity or in my mind. A huge huge untapped goldmine exists elsewhere !
The real void is where the three types of intelligence meet
The real void is where all the three types of intelligence meet, from an Advanced analytics perspective. And this is important not only from the perspective of job seekers but organizations as well.
What you need is a talent pool that can identify new opportunities (creative intelligence), which requires a great deal of understanding business and ability to visualize complex operational aspects in simple forms (Practical intelligence), AND THEN leverage Analytical Intelligence to solve the newly formulated problem.
All the key think tanks in our world are on to something- AI & ML does have the capability to change the way we work drastically. But that is not going to happen with the extreme focus on Analytical thinking approach.
Universities will not be able to fill that void soon
Universities that collaborate extremely closely with corporations so thhat they can train their students to leverage all three types of intelligence, something that the world of analytics desperately needs- in my world, I can count such universities on the fingers on both my hands. For rest of them, if they start now,it will take them years to transform their curriculum. The gap between skill desired and skill produced would have widened exponentially by then.
Corporations need to step up
And this is where large corporations need to step in. The opportunities around are limitless. I am myopic in my thinking because I think primarily about Operations but even from that perspective, I believe there are so many new problems that can be formulated, solved and those solutions then subsequently automated. Corporations need a talent pool that is a combination of the three types of intelligence listed above (along with few other traits) but Universities will not be able to meet all that gigantic demand. What is the solution?
Acme Inc. needs to become Acme University as well
Essentially, corporations will have to become their own source of supply of talent. And here is an example scenario:
1: Acme Inc. understands what type of talent it needs for this decade in terms of Advanced Analytics, which will be aligned with many other factors like its corporate strategy, operations strategy etc.
2: Acme Inc. designs a x months program that will help participants, with specific skills, come out from this program ready to usher the company into the digital renaissance of this decade and nurture subsequent batch of “graduates” from the program. Unlike conventional LDP programs, this program will be primarily academic, Analytics focussed but with additional elements to further build on “practical intelligence” included throughout the curriculum.
3: Now that the program has been designed, with a specific skillset in mind, Acme Inc. needs to shortlist a set of schools and programs from where it will hire its students.
4: It needs to design the “Admission” process, the most crucial aspect- That can be a combination of:
- A written exam designed to test the combination of different type of intelligence, Emotional Quotient etc.
- Case study (if required)
- Group exercises and games
- In person interviews
Imagine the results is Acme Inc. nails it
While at first this idea may seem “maverick”, companies have been designing their own trainings for decades now. This will be taking it way beyond that but is not something that is unimaginable.
Imagine the results if Acme Inc. nails it. An analytics talent pool tailored to your business. The most potent weapon you can have in this decade ! It opens a whole new floodgate of opportunities not only interms of new opportunities, solutions and resulting $$$$, but it can monetize its curriculum/program as well. If within 5-10 years, Acme Inc. demonstrates to the world that it is breeding a generation of Advanced analytics talent, the likes of which the world has not seen before, there is a significant opportunity to monetize it. How and in what form can be a topic of seperate post in itself.
Views expressed are my own.