Sometimes you have to learn and adapt. In undergrad, usually statistics is not the favourite subject for anyone. So to make it more interesting and interactive I used to cold-call people. In some cases you have fun because they are not able to answer, in some cases they give brilliant answers. In one case I was taking a class and I cold-called this girl from South Korea and she started crying, immediately. I was feeling so embarrassed. In the end she came to me saying that she was embarrassed because this was the first time she was the centre of attention of more than a hundred students. There I understood the differences in culture. For a European and an American and an Indian, when you ask a class of international MBA students, you will get an answer from US and Indian students. There are some cultures that don’t like to show themselves. Cold call in that case is very dangerous.
What are the traits you would like to see in a good student? What skills would you like to impart (and like the student to imbibe) from your courses?
Willingness to learn and curiosity – these two traits can summarize everything required in a good student. All the other traits are secondary and linked to this. If you are curious and willing to learn, you can pass any difficulty you have. You are poor in communication? If you want to learn, you will have a course in communication, and the same holds for your technical skills. If you want to learn and you are curious, as a professor I will definitely see the difference.
I would like to my students to imbibe the idea that numbers are important, and analysing numbers is important for your business. In 2014, a manager cannot be effective without a good comfort level with numbers. I am not expecting that they become a Ph.D in statistics. I am expecting enough knowledge to interpret results. You cannot always put yourself in the hands of others, in the hands of a consultant – you need critical thinking skills.
How do you think the higher education industry will evolve in response to technological advances like MOOCs from Coursera?
MOOCs are a reality – we started 2 courses as a partner with Coursera. I recently read an article titled ‘Why Most Business Schools Will be Dead in 2020’. I also do not agree to this view. I believe that both MOOCs and business schools must evolve - and I'll tell you the reason why -
I was talking with participants in Los Angeles for our executive program. We meet once every two months, and they were of the opinion that this experience of meeting face-to-face cannot be replaced by a MOOC. Of course, what the MOOC can do is it can give you the basic knowledge you need before you come to class. That’s why I say the B Schools must change – they must change the way they deliver content. The basics should be delivered by a cheaper online course.
Do you think data mining, machine learning and statistical artificial intelligence techniques will eliminate jobs?
Definitely not. I don’t think that machine learning and AI techniques are going to eliminate jobs. Of course, technological support and technologists are very important in analysing data, especially because now you have to be very fast in analysing data, but I strongly believe that the contribution of know-how from the people will absolutely make the difference, so I believe in the exact opposite – technology will suggest the right people to hire, the right know how to buy, but in itself it is not going to eliminate jobs. Companies like IBM and Infosys may have said that they are going to hire fewer people because they have built some software, but on the other hand, more and more people are going to be doing the work of analysing data – so if you can’t work for IBM, you can work for some other company in data analysis, you could be working for a company that 2 years ago was not thinking about having a person doing data analysis.
In which industries do you think statistical techniques and Big Data will be most useful (i.e. which industries can students look forward to gain employment)?
Big Data – the immediate association is web-based B2C companies. But even in B2B, there is a huge need for data analysis, probably not necessarily Big Data, but a large amount of data. Every company has a lot of data to analyse, but I don’t think all of them are analyse them effectively. The most likely companies for using statistical techniques are web-based like Google and Amazon, but even small start ups in Italy are ramping up – I just received many emails from my ex-students in the last year – they are working in these startups – asking if you have any students who are good with analytical skills. The B2C companies probably feel the need immediately, B2B do not see the need immediately, but the data is there and it needs to be analysed.
Please don’t think that the only way out and the only way to have a fantastic career is starting with finance. Let’s stop with the myth that Finance as the end of every MBA. There are many careers you can start without starting with finance. The feeling in our B school – the full time MBA at SDA Bocconi is that everybody wants to end up in London and work in finance. Do you think this is a long term decision by students? Do you think private equity and investment banking can pay high level of salaries to everyone for a very long period? Is this a good choice in the long run?
What are the benefits and pitfalls of using the statistical and modelling techniques to solve problems in marketing, finance (valuation etc)? How can the pitfalls be avoided?
You cannot avoid the problems completely. The real goal of a model is not to give you one number. It is to give you more understanding of the problem. E.g. for a capital budgeting model, the objective is not to get the NPV. The goal is to find out which is the most important variable influencing the NPV. What is the level of uncertainty regarding the NPV. If you interpret statistics and modelling this way, modelling is useful. Otherwise you will go with the saying “Lies, Damned Lies and Statistics”.
What does a company need to do to ensure that its Big Data or Analytics Initiative turns into a success and does not turn out to be an expensive waste?
I think the decision they have to make is to include this initiative as part of their strategic plan. In many cases companies think that analysing data is an activity that comes on the side. There is the business, and there is the analysis of data. And so they invest, in technology and in people, - they have nice tools, but they don’t achieve great success. But if you start your data analysis division and let it be a part of your company rather than being an offshoot, and let it be part of your strategy. You can use your iPhone for having fun, or you can do your iPhone for doing work – this is also the same.
What is your advice to an MBA grad wanting to make a career in analytics? Do you think an MBA is necessary to make a career in analytics?
It’s a complicated answer. The first step to starting a career in analytics is to strengthen your fundamentals – choose a good Masters in Business Analytics. I strongly believe in having a strong background in both technical and the business side. I have been a data analyst, but I have a degree in Economics. I have always invested in this side of my education - the business side, and not just data analysis. Even if you want to start a career in business analytics, you need to have a way to get a 360-degree view of the business. Otherwise you will just be a geek crunching numbers. If you don’t understand the problem, the real reason why a company is doing something, then you will find things difficult.
A huge part of my career has been based around the fact that I was a software programmer, I was writing code, but I had a degree in economy. I was able to talk to those who had a problem, and I was able to talk with the ones who were going to solve the technical problem – that was my career. If you are a business analyst and you have a Ph.D in statistics, but you don’t understand why people are doing this analysis – financial analysis or marketing analysis, then the final result will be poorer than if you do. You remain a number cruncher, I don’t think you are going to do a brilliant career in business analytics, because it is no longer data analysis, its business analysis.
Companies are hiring experts who can analyse data, but what they want to build is businesses. In my opinion, you need both. You can start with an MBA – a general management course, and then make an investment in data analysis skills. You can do the reverse as well. That’s why we have good success with our executive MBA (specially in Italy) as well as the global executive MBA. They are attended by a lot of engineers, technical experts – who after 5,6,7 years realize that they need a broader perspective.
What are the main objectives of the statistics course in India by MISB Bocconi?
The graduates are going to be managers. And in 2014, you cannot be an effective manager if you don’t understand a bit of data. None of them will become a Ph.D in statistics with this course. But you can’t be fully dependent on others for analysing data. The young manager of 2014 should be able to (when I started to work, all managers had a secretary – to write letters for them etc). Now – people are using word processors and powerpoint to make their own letters. You cannot be a manager without being comfortable with numbers.
(This is a Promoted Feature Story)
Follow MISB Bocconi at InsideIIM at misbbocconi.insideiim.com
Interview with Siddhant Kedia, student – MISB Bocconi
Soft Skills are Key for Success: Interview with Prof. Caselli and Mr. Giuliani from MISB Bocconi
Chat
Comments