Bridging The Skill Gap

Bridging The Skill Gap


Businesses are complex multidimensional entities that require a wide range of resources to function effectively. The core of any business is a set of products or services that the company provides to customers. And to deliver these products and services, it is essential to have the relevant skills and knowhow, or, in other words, an operations team.

Bridging the skill gap

There are a host of other functions that support this technical team in the delivery process. These teams make up the corporate departments and include accounts, human resources, finance, communications, corporate planning/ development, information technology, legal, logistics and administration.


A company in the construction business, for instance, depends alot on a strong track record of several high-quality projects that it has successfully executed to establish itself as a credible player. This is possible only if it has experienced civil engineers and architects with proven skills on its payroll. These technical teams are supported by corporate teams. The legal team would review all contracts that the company enters into, manage litigation cases and provide legal advice on new ventures. The finance team would help in raising finances for new projects, negotiating terms with banks, hedging their commodity risks by entering into forward contracts (for cement, steel), and parking excess funds in appropriate short- or long-term financial instruments.



 MBAs enter the business world in operational as well as corporate roles. Irrespective of that, there are certain generic skills one can expect to pick up during the MBA. The question is: Are these really as important in the current day and age? Try to answer this by reading through some of the important skills listed in the following sections.

Data Analysis/ Information Processing

 In the business world one can get overwhelmed with the amount of data that gets generated. Most of this information overload is actually useless detail in the big picture. This is what necessitates the need to plough through this pile and figure out what is relevant and what can be discarded. Often, there are patterns that can be derived from this data heap, which in turn can be useful in making business decisions.

Consider, for instance, the task of rating existing and potential customers within a business. For the existing ones, there would be historical data on their transactions. What products/ services did we sell them? How much did they pay for it? How many times have we entered into disputes with them for payments or quality of deliverables? How much time/ effort have we spent in fire-fighting for this customer? Do they pay us on time?

For potential customers, there is again a similar set of queries. How big are their operations? How many years have they been in existence? Are there litigations and cases pending against them? What is their overall reputation in the market? Should we do business with them? What should our terms and conditions be? Can we approach contacts within the industry to find out more about them?

Valid questions, we would all agree. And if the business operates in an area that has several thousand customers, the data generated can be humongous. In the life cycle of this data, there are three distinct phases – creating/ updating the data, processing and deletion/ archives. Tools such as Customer Relationship Management (CRM) software are used across nearly all organizations of credible size to manage these phases. Creating new customer profiles involves gathering all relevant data for each customer and feeding it into the CRM package. This is basically a data entry role and staffing an MBA for this is overkill. Old records are archived and moved out of the system for traceability and auditing reasons instead of being erased  completely.

The data processing part can be the most complex in the life cycle. However, the CRM makes this data-crunching task easier by using pre-built and pre-packaged features within the software. For managerial consumption, in most cases, this processed output is more useful than the actual data. Apart from the manual data entry, most other activities are automated. In specific areas where software tools are not available, the business can always approach consultants to create software models for them. So unless you plan to be on the other side and actually design and build such tools, you can be assured that the tedious part of data-crunching can be managed with off -the-shelf tools.


 In B-schools, you will constantly be juggling multiple lectures, assignments, presentations, social/ career/ academic events. And over a period of time, you are expected to be able to manage all this without pulling your hair out in frustration. Often you would be part of multiple study groups and required to commit time for team meetings. Even after a perfect schedule has been drawn on painstakingly, there is always the chance that one of the events gets re-scheduled and you are back to square one. It may not even be possible to get involved in all activities due to overlapping schedules and time constraints. In these situations, you would have to decide which of the mutually exclusive events are higher in priority. And if you have good time management skills, this is not a big challenge.

In the corporate environment, the story is similar. Unless you are part of a highly specialized field where work schedules and processes are extremely well-defined (the assembly line in a manufacturing company, for instance), very rarely will you find that you are working on just one task. And the situation just gets worse as you rise within the organization. But the same rule applies. If you have the knack for time management, you will manage anyway, whether it is in an academic setting or in a corporate environment. Multitasking is something that cannot be taught formally in a classroom.

Theoretical Foundation

 The accounting professional may be keen to understand the operational aspects of the company, the drivers used by the marketing guys to position the company’s products, the strategy that senior management has in mind to help expand the business in Latin America, where the company’s footprint is still small. The accountant knows that he may not actually shift into any of these other areas, but the theoretical grounding will help him gain overall clarity about areas within the company that he earlier treated as blackboxes without bothering to find out what goes on inside. But does this justify two full years in a classroom? Our man could probably have fixed informal lunch sessions with his colleagues from various departments to get an overview about their roles and figured out how it all ties in with his work. In an interactive one-on-one meeting, his queries can also be very specific. As the primary context and business setting are familiar to both parties, the responses in turn would be more meaningful and the data assimilation process more effective.

Communication Skills

 A dreaded part of the MBA class experience is ‘cold calling’. During case study discussions or regular lectures, the professor may randomly call out student names and ask them to explain their views on the topic of the day. Students are expected to come prepared with their pre-readings for the day and are expected to have analysed specific topics, concepts or business problems. For every point that gets expressed, there may be umpteen counterarguments from other classmates, considering the diversity within the class. Getting your points across solidly requires a combination of clarity of thought, confidence, vocabulary and lucid speech delivery.

Similar attributes are required during individual and group presentations in class. Additionally, all group activities require people skills in order to zero in on a common set of objectives and lead the entire group towards that goal.

There’s no denying that these skills are required in the business world as well. But the question is how much progress would someone with weak communication skills make in a classroom setting. Are cold calls, study groups and presentations good enough to help you brush up the entire gamut of your communication skills?

Simulations/ Modelling Situations

 Decision making in real life can be pretty complex. And so academicians have come up with the concept of models and simulations. This involves creating a smaller, and at times oversimplified, ‘model’ of the real-world situation. Software tools such as spreadsheet applications are used to identify levers that impact the model.

If this is sounding too theoretical, let us take a simple example. Say, we make an investment in a mutual fund that has historically provided 15 per cent returns per year on an average. You are considering investing Rs 1,000 in it for five years and would like to know how much you would get back at the end of the investment period in the best- and worst-case scenarios. This is a classic case of scenario modelling. In the spreadsheet, you would identify basic input parameters (for example, investment amount, period, best-case rate of return) and the output parameters (for example, amount after five years for various scenarios). You would then establish a link between the input and output parameters using appropriate formulas. And voila, your model is ready. All you have to do now is enter values for various input parameters and obtain results.

But it’s not as simple as it sounds. Models and simulations can get really complex as the accuracy and the credibility of the results are driven mainly by assumptions and inputs that go into these models. For instance, in our previous example, the designer may have two input values, one for best-case returns and one for worst-case returns. Now the user may enter values for both (say, 50 per cent and 10 per cent, respectively) and the model will provide some results. What’s the guarantee that the input values that go into the model reflect reality? How would you ensure that your estimates and assumptions are not too ambitious or too conservative? Many would actually drill in further details in order to capture underlying assumptions for each input parameter and try to make the model more accurate. This could mean defining complex relationships between the best/ worst case returns to more granular parameters (industry growth, interest rates and global economy factors) that influence them.

We are not trying to say models aren’t useful. They are, to an extent, and firms around the world have spent a lot of effort, time and money in building and maintaining their own repository of models. Some of these are more complex (and less useful) than others. Some are built in-house by corporate personnel for routine activities like budgeting and forecasting. Some are crafted by external consultants for special situations. However, the common attribute that spans across all such models is that they are driven by the Garbage-In-Garbage-Out (GIGO) concept. In other words, if you feed in trash, all you get from the model is trash, irrespective of how sophisticated the model may be.

Most good business managers realize this limitation and use models to whet their own business judgement while making critical decisions. Models and simulations are not an alternative to experience and basic common sense. How many managers and leaders that you read about in the media are applauded for their fantastic financial modelling skills?


 Here we are not referring to technical planning of the kind required in operational research. We are referring to general planning (for lack of a better term). Defining the objective, evaluating various options and initiatives to accomplish it, estimating resources (time, money, people and effort) required for execution, identifying dependencies and finding workarounds are some of the sub-activities that would come under the general purview of planning. In B-school, planning is a continuous process as class schedules, assignment deadlines, group activities, outings, cultural events, all keep on piling non-stop. It does not end here only. The MBAs who will enter the b-school after cracking MAT 2015 or any other competitive exam may have to learn how to cope up with this workload and stay on top of it all or risk getting buried in the avalanche. Prioritization is one of the most important skills in planning. The 80: 20 rule – that a small minority (20 per cent is only an indicative figure) of factors can have a big influence on the overall picture – applies to many situations and can be used as a lethal weapon in the prioritization process. For instance, twenty (of the hundred) suppliers of an electrical product may have an 80 per cent share of the market. Similarly, if you have ten open tasks to take care of, two of them may be the most critical.

But unlike the theoretical subjects, MBAs are expected to pick up this skill ‘on the job’. It is assumed that the MBA student is well-aware of all major milestones over the coming day, week, month, semester or even beyond, and will plan accordingly.

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