Kamila Jasinska from the Class of 2021, shares her experience from a project with Sense Worldwide, an organisation that harnesses cognitive diversity at scale to help leaders, innovators and teams see things differently and think differently.

Kamila shares what she learnt from the project and how the skills she developed studying MSc Business Analytics at UCL SoM have prepared her for her future consultancy role.

Why did you want to study Business Analytics at UCL School of Management?

I discovered a passion for analytics during my undergraduate studies in International Business Management – I fell in love with data during the Statistics module, inspired by my module leader, and decided that it is the direction I want to develop in. I very much liked the UCL School of Management’s MSc Business Analytics programme specifically, as it included both the technical and the business aspects of analytics – and it turned out to be exactly what I was looking for.  

When did you graduate and what have you been doing since you graduated?  

I submitted my dissertation (so finished my programme) in August. For the past three months I have been a part of a University Programme in the world’s leading fin-tech company, and now will be switching to a Junior Analyst role in one of the ‘Big Three’ consultancy firms - so was very lucky to get some amazing experiences straight after graduation. 

What need was investigated through the consulting project? 

The project’s overall aim was to find a universal way to score and scale cognitive diversity, measure its influence on innovative project success and test whether cognitive diversity drives incremental, early-stage innovation. It also meant empirically proving, or disproving, whether the company’s core belief that cognitive diversity drives innovation is true.

do you think the skills that you learned on the programme helped you support Sense Worldwide? 

Yes, the experience definitely helped right from the outset of the project, I understood that first and foremost it’s key to understand how to look at the company’s questions or needs and translate them into analytical problems that can be solved with the available data. Then I also definitely used a lot of technical skills I had learned (especially Programming and Predictive Analytics modules) – before taking the MSc programme I had no prior coding experience, and then, for the final project, I was able to build a machine learning model to predict personality types from text – which would not be possible without the skills I acquired during the time on the programme. The Statistics module, helped me understand hypothesis testing and regression – both of which I applied to the project. Data visualisation has also been hugely important, not only in the technical aspect but also in deciding what and how I want to show, considering who my audience is and what the overall aim of any visualisation is. Lastly, the Business Strategy and Analytics module taught me to always keep in mind what the actual aim is and what practical value will this provide to the company.  

What did you learn from the project?  

I surely have learned a lot from this project, and working on it has been an immense inspiration for me. I definitely got more and very practical coding experience, a chance to further develop my presentation skills, and developed the ability to convey very technical information to a non-technical audience. I’ve also learned a lot about cognitive styles, which turned into a passion for the area of cognitive science, which I am actually planning to take further. Lastly, the project has once again shown me that analytics is indeed a mix of art and science, and if we use both, virtually anything can be translated into an analytical problem – even peoples’ personalities and thinking styles - and the solution can provide so much value, and lead to insights we wouldn’t even think about when planning the project.

What was the most challenging part of the project? 

The most challenging part was definitely translating the main problem statement given by the company ‘How might we measure cognitive diversity to drive innovation?’ into analytical research questions that could be answered with the available data and analytical skills I was able to offer. However, since both the question and the area of research were of great interest to me, and the company was fantastic to collaborate with, I believe that together we managed to make most of the project and came to some really interesting conclusions. 

What was the most rewarding part?  

Simply making it all work. From the initial data, including peoples’ answers to very different questions (from cheese to sports, to perfumes) I managed to get to the point where those peoples’ personality types were obtained, cognitive diversity was calculated and unique projects could be compared against each other. The fact that the ideas I had to make it all work were actually possible to implement, and the results were useful for a real business, making it all really rewarding and inspiring.   

How do you think the project helped prepare you for your current role? 

The technical skills I acquired are definitely very helpful - even though I currently do not code in any of the languages I was being taught, learning those gave me a general understanding of how machines ‘think’ or ‘talk’, which is very useful to me now. For my future consultancy/analyst role, I will surely use this experience to remember that in analytics it is good to stay open-minded, look for different solutions, and try to see where the data might lead me – which in the case of this project turned out to be a really inspiring journey.