When I first started recruiting for consulting jobs, an interviewer at Bain shared a story (arguably a legend at this point) about how Bain (or it might have been McKinsey) was asked to advise Motorola on whether or not they should enter the mobile phone market.

As you might know, Motorola eventually dominated the pre-smartphone mobile phone market with close to $10 billion in annual sales.

As the legend goes, the consulting firm advising Motorola recommended that Motorola not enter the mobile phone market. Obviously, that recommendation was dead wrong and thankfully for Motorola, they ignored the recommendation.

I heard similar stories at McKinsey as well, all revolving around a central theme — McKinsey consultants hate to be wrong, and they hate to have conclusions they can’t support with quantitative data.

This is one of the main reasons McKinsey and the other top consulting firms so rigorously test for logical analysis in the case interview.

However, anytime anyone is over wedded to a particular approach, it leaves them prone to vulnerability. In this case, McKinsey and the other top firms are vulnerable to missing conclusions that are correct but cannot be supported well with hard data.

In the case of the supposed Motorola engagement, which I believe took place in the 1970s, there was so little data available that there was not much to analyze. While there were some clever ways to forecast technology adoption, none of the data or methodologies were 100% accurate or reliable.

(MBB now often uses “real options” analysis to value multiple uncertain scenarios in a more accurate way, but the fact remains that in many of these situations, a high degree of uncertainty exists and that drives MBB consultants absolutely crazy.)

A similar bias exists within corporations as well as most white-collar professionals (especially the well-educated ones). In the Global 500, there’s an enormous bias to create a strategic plan and stick to it — no matter what. Under many circumstances, this degree of focus serves as a sound management principle.

But like anything overdone, it creates vulnerabilities. Anytime one is over wedded to “the plan,” it leaves one exposed to missing emergent opportunities that weren’t obvious at the time the plan was being created.

Harvard Business School professor Clay Christensen, legendary in technology circles, calls this the difference between the “planned strategy” vs. the “emergent strategy.” He argues, and I agree, that when it comes to strategically planning one’s career, many people overlook the emergent strategy approach.

The classic strategic planning approach is to gather all data, analyze, identify your optimal opportunity and focus your plan on it.

For large corporations, this would typically involve segmenting the market and looking at the size of each segment and its growth rate. Then it would involve analyzing the company’s capabilities vs. the competitors vs. what each customer segment wanted.

Ideally, you look for a segment that’s growing fast, overlooked by competitors, and one where your company has a competitive advantage in serving.

This would be a textbook strategy created by McKinsey, Bain or BCG.

This approach works incredibly well in more established industries where there’s ample data available on the market, customer segments and competitors.

But what happens in smaller markets or with smaller clients?

In my consulting practice today, I exclusively serve small businesses — some as small as $500,000 a year in sales up to $15 million typically (sometimes up to $300 million). With these clients, they often operate in very small industries and there’s just no data available (or affordably available) to analyze.

In classic case study analysis, you’d ask them, “What are the market segments?” They’d say, “I don’t know.” “How large is each segment?” “I’m not sure.” “How fast is each growing?” “I don’t know.”

In these situations, the classic strategic planning process doesn’t work very well.

Over the years, I’ve gravitated towards the emergent strategy approach. Here’s how it works.

You take your best guess at what you think is the right strategic approach and then you try it (preferably cheaply and quickly) and see what happens.

If it works, you keep doing it. If it doesn’t, you analyze the data you uncovered in the attempt to find some new insight not previously available and revise the strategic focus.

Seventy percent of my client work these days is emergent strategy oriented.

Let me give you an example.

I was recently asked by a client whether they should introduce a new offer to a particular customer segment. If this were a Fortune 500 client, I would commission a market research project, focus groups or analyze prior research. In my client’s case, none of that was available.

So, my suggestion was to target 100 prospective clients by sending them direct mail and cold calling them and see what happens. It’s market research via taking marketplace action.

In general, one of two things happens. The market test 1) works brilliantly, or 2) it fails spectacularly. I instruct clients that in both situations they need to get direct feedback from prospective clients as to WHY they value or absolutely hate a particular proposed product offering.

The purpose of the test, in these cases, is not to succeed or to fail. It is to learn.

It’s not a particularly elegant approach, but if you have access to very limited information and there’s a high degree of uncertainty, it’s an approach that works.

In this way, emergent strategic planning is a bit of an iterative approach.

Now, let me connect this planned vs. emergent strategy distinction to career plans.

I have found, especially for ivy-caliber, white-collar professionals, that there’s an overwhelming bias to using the “planned strategy” approach.

The plan looks something like this:

I will graduate from college, get a job at MBB, get a Harvard MBA, go back to MBB, make partner, retire.

This plan is often devised when the person is in the middle of college — typically 19 or 20 years of age and is laying out a rough plan for the next 4 decades.

(There are similar career plans for those in pre-med, pre-law, and those pursuing a PhD and career in academia.)

While this approach does work out for some, for many it ends up being problematic.

Here’s my theory as to why.

Let’s take a variant of my business situation framework for analyzing business opportunities and adapt it for analyzing career opportunities.

So instead of:

1) Customer
2) Competitor
3) Company

Let’s replace that with:

1) Employers (those who “buy” my labor)
2) Competitors (other prospective employees vying for the job)
3) Self

When you use this adapted framework for analyzing career opportunities, there are two components of the framework where there is very little data for the 20-year-old college student laying out her long-term career plan.

The first is employers. By and large, most people only research a few employers in a few select fields. For example, out of a global economy with 100,000 industries and 100 million employers, I personally only did research on two industries for future employment (investment banking and management consulting). Within those two fields, I only researched 10 prospective employers.

So out of a universe of 100 million potential employers, I analyzed only 20.

As a result, that which is unknown is infinitely larger than that which is known (or that for which research has been attempted).

In addition, you can research all you want about what it is like to work for a particular company, but you often do not know what the actual experience will be like until you actually show up for work. It’s only then that you discover the clients you will serve, who you will be working alongside in your project teams, and learn the identity of your “boss” (in consulting firms, the partners you work for often are not known in advance or are rotated by project).

Again, things become known with greater accuracy only after the decision to accept an offer has been made.

The second area of vulnerability is in the “self” aspect of the framework.

In my experience, most 20-year-olds do not know themselves very well. Twenty-somethings coming out of the Ivies are incredibly smart but rarely wise.

Wisdom comes from being tested in the real world, falling flat on your face repeatedly and learning who you are in the process. In my opinion, the extremely sheltered environment of a university campus develops intelligence to its greatest potential, but not so much for wisdom. It’s too structured, too protected, too predictable… a massive oversimplification of how the rest of the world lives.

So, what commonly happens is the 20-something college graduate pursues her career “plan” and, once the real world is confronted, she realizes that many assumptions she made in her original plan were not true in reality.

Working at XYZ organization wasn’t exactly as she thought. She thought doing XYZ professionally would be a lot more enjoyable than reality.

This happens when the rising star pre-med student enters medical school only to discover she hates seeing patients and doesn’t like research.

It’s the pre-law student who goes to law school in hopes of being a fearsome courtroom litigator (that’s often glamorized on TV), only to discover that being a young lawyer is spending 100 hours a week reading paper documents and creating new paper documents for other people to read.

This is not at all to pass judgment on these people. It’s just a reflection of the reality that many things are not knowable at the outset of creating a career plan. Some things just aren’t knowable until after you actually try it.

(Though things like informational interviewing do help quite a bit in narrowing down the discrepancy between expectations and reality.)

When assumed expectations don’t match reality, that’s when there’s an opportunity to shift from pursuing planned career opportunities to emergent career opportunities.

In many cases, people find it troubling when they discover the career path they’re on is not the right fit for them but an opportunity with a better fit is not yet obvious.

In these situations, people take one of two paths. They either stay on the current known wrong career path until something better comes along (it rarely does, or the wait is excruciatingly long). Or they exit the known wrong opportunity to deliberately seek out the right opportunity.

It’s my belief that the former is what leads to the “mid-life crisis” — doing what you hate for 10 or 20 years and ending up successful and miserable… or as I like to call it, “successfully miserable.”

The latter has a lot of uncertainty (which again drives MBB consultants and those cut from the same cloth absolutely crazy). The key distinction is that the uncertainty is often temporary.

If you pursue emergent opportunities as a “market test” (such as the ones I advocate my small business clients take), then you discover more information about the market and yourself much more quickly.

Sometimes to find out what is definitely right for you, you have to attempt pursuing things that seem potentially right for you (often repeatedly) until the definitely right opportunity becomes clear.

What makes this journey especially disconcerting, especially for those successful in school, is the final destination is often not known (and not knowable) until AFTER you’ve departed for the trip.

(Just remember that clarity increases and uncertainty decreases once the journey is underway.)

The alternative is to follow a career path that you know is wrong and passively wait for something better to come along. This is the path to being successful (if you force yourself to do what you hate) and miserable, or successfully miserable.

That’s my thought for today.

What are your thoughts?