Imagine the scene at a top 10 business school a day after the application submission deadline has passed. All the admission officers from the admission committee gather around a crystal ball that has magical powers to improve their productivity.
In a matter of a few seconds, it processes thousands of submitted applications, calculates the chances of getting in for each candidate and displays a hologram with the list of folks who rank the highest in terms of admission chances. All that the officers need to do now is call the applicant over the phone to pass on the good news and soak in the pleasure of hearing them squeal with joy.
Chances are, this scenario will not unfold in our lifetime. Adcoms know it and they aren’t holding their breath hoping for such a crystal ball to be delivered to their office. They are relying on their physical and mental powers to get through each of those thousand applications.
However, folks on the other side (i.e. applicants) already have access to many free MBA acceptance calculators to make the difficult process easier. Many GMAT prep and MBA related websites host such match making tools.
Some candidates have asked us why we don’t do what other MBA application consulting teams have already done and create an online application to calculate and predict MBA acceptance chances. It’ll allow applicants to select business schools and move on quickly to the application part.
Here’s a little secret. In the earlier days of launching our site, we thought – “How can a team with a name like MBA Crystal Ball not have a crystal ball!”
So we created an online application by packaging our MBA Application Strategy (i.e. MBA MAP) algorithm within a familiar web-page interface and hosting it on our site. The online MBA chances predictor worked pretty well.
As you might already know, business school selection and MBA chances evaluation are among the things that we cover in our MBA MAP. Instead of relying purely on gut feel to make bschool school selection recommendations, we make the process analytical and data-focussed.
Given the vast number of MBA colleges there are and the amount of relevant data that one needs to consider for such an analysis, it’s impractical for us to hold all that data in our head and do the data-crunching. That’s why we created an algorithm which supplements (important word) the manual part of the MBA MAP process. As with all software applications, it involves data, processing and presentation. Our offline process involves much more than automated data crunching.
In contrast, our online MBA chances predictor was meant to do a subset of that, by stripping off what we do manually (i.e. no essay evaluation, no interviews, no MBA goal validation).
Based on the personal, professional and academic details shared by the candidate, the online predictor would create elaborate & impressive looking reports with the names of the top ranking business universities and the candidate’s chances of getting in.
In those early days, when we were trying hard to gain traction for our website, a free online admissions prediction tool seemed like a great hook to gain the attention of MBA applicants. But after spending all the effort on software development and testing, we discarded the idea. The program never saw the light of day.
Since then, we’ve created other free online applications that have become popular (like our career growth visualisation tool, supply chain game, business strategy game). The efficacy and utility of these tools became apparent to us when not just regular visitors but universities across the world started using some of our software tools in their classrooms.
The MBA MAP went on to become our flagship offering. But even after all these years, we still shy away from hosting our own MBA college admission chances calculator on our website. Here’s why.
We aren’t referring to the profile evaluation and chances prediction algorithm. That would get really complex if you start considering all the relevant parameters. We are looking at it from the candidate’s perspective.
The big advantage of an online tool is its simplicity of use and the simplicity (and often binary nature) of the results. It can create a false sense of clarity. ‘Ah, the program said that, so it must be true.’
For a software program, two Indian candidates with a mechanical engineering degree from IIT / NIT with similar academic grades with a 700 GMAT and 4 years experience as supervisors in an engineering company would appear to be pretty similar.
But we know that this is an over-generalisation. A single subjective factor (communication skills) can turn one into a hero and another one into zero.
Adcoms know how to differentiate between the two, but there’s no way for a software program to even try factoring in such aspects.
However complex the algorithm might be, if the data inputs are incorrect or obsolete, then the results are meaningless. The statistics for Bschools change every single year, as new classes start. When the applicant pool changes, you’ll get a new set of average GMAT scores, work experience.
Most importantly, the interdependency of data also changes. Is a GMAT score of 700 good? In absolute terms, yes. But what if you are an male Indian IT engineer? Well, maybe not. What if your extra-curriculars (outside your day job) were unusual and really impressive? Hmm, not so easy to say now.
Software works well where there’s rule-based standardisation and fixed data elements – like calculating your total Income Tax liability while filing returns. It’s not so optimal for moving targets, as is the case in admissions decisions.
Though we’d love to have James Cameron convince us about the possibilities of artificial intelligence, in most scenarios (other than those where the process can be very clearly defined in unambiguous terms), we aren’t anywhere close to machines and programs replacing humans when it comes to real world decision making.
There’s a reason why bschools haven’t replaced Admission officers with robots yet. And we find that reason convincing enough to follow it in our own profile evaluation and bschool selection process.
For many of the same reasons, we shy away on our MBA forums from making business school selection suggestions, as it goes to the other extreme of depending too much on intuition (rather than data).
Just like Adcoms, we prefer a more balanced approach, of considering data along with experience and intuition to judge whether a candidate will be successful after an MBA.
Of course, not. There’s still value in them if you know the general process behind them, you are aware of the limitations of software driven recommendations and you use it as a supplemental input to your independent research.
Shaadi.com (or any other matrimonial site) might propose 5 profiles for you to consider based on their match making programs. You wouldn’t blindly pick one to marry, right?
You’d probably start off with those suggested profiles, as it’d be better than a completely clean (and confusing) slate. Then you’d do your own research to find better potential partners that the match-maker software wouldn’t have managed to get in front of you.
Not to mention the fact that we have no clue about how exciting or boring the brilliant program designer’s love life has been, how qualified s/he is to recommend your life mate, etc.
Other sites use free match making programs too. Think about LinkedIn that suggests jobs for you to apply to. Amazon does it based on your browsing history. Think about those car and home buying sites that suggest options based on your preferences.
When you are searching for a needle in a haystack (as is the case in the earlier examples), such features can help you with a launch pad.
Stick to the same logic when you are using online tools to find out your admission chances to MBA colleges.
The 5-10 college names that pop up on the screen could be a good starting point for your research.
Go behind the numbers and find out more about the bschool culture, what current students like (and don’t) about the program, how the economy is doing and where’s it heading in the next 2-3 years (when you’d be ready to graduate and start looking for jobs).
If you have started preparing early, you may have some time to build your MBA profile as well. That could positively influence your chances and what you see in the online results of the free tool today may no longer be relevant in a year or two.
The data-oriented algorithm we use in the MBA MAP takes a few milliseconds to run, but it only helps with the number crunching.
It still takes a whole day for us after that to send the MAP report to the candidate, after an old-fashioned human brain (subjected to Darwinian evolution laws rather than Moore’s law of obsolescence) has had a chance to process the inputs from the MBA essays, interview and other elements of the MBA application.
Have fun calculating your admission cances and predicting your future. But don’t get swayed away by the results. Keep your feet firmly on the ground and take solid steps to decide which bschools you should apply to.
Read this related post:
– Average GMAT scores for the top MBA programs in the world
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