As part of the 'Businesses after COVID-19' webinar series, UCL FinTech Society interviewed Diane Berry (Senior Manager at Bain & Company).
Mo Safayat covers key discussion points about data analytics at Bain, the talent gap and regulations on data privacy in this interview transcript.
1. How would you describe your role and how does the data analytics division fit in the whole organisation?
Data analytics team is an integrated, multidisciplinary team formed by data scientists, data engineers and engineers in operation research. We are part of Vector which is Bain’s short integrated platform for all digital capabilities. One of the things we do is give recommendations to insurance companies to optimise discounts for clients. In short, we are experts in data analytics and solve business problems.
2. Can you think of any industries that can benefit from data analytics?
One industry that can benefit is the financial services sector as companies have to deal with new regulations. The retail industry can also benefit, especially with Covid-19 resulting in an online buying boom. But even in the physical space, Amazon GO is using data to get rid of cashiers. They use sensors and monitors to see how customers spend their money. The Transport and logistics industries can also benefit as AI technology gets implemented in a lot of railways to allow for trains without drivers.
3. Do you think the government is doing enough to create more talent and train people with the necessary skills? Is there a skills gap?
We think that the data science skills gap is being closed as universities are increasingly focusing on producing a lot of students who have such skills. Companies also have training programmes that address this and sometimes they outsource their training. I believe the gap will be closed. According to a recent survey we did, the areas with unmet demand are data architects and engineers.
4. Is regulation detrimental to innovation?
Regulations on data privacy are closely related to consumer rights and competition. This is more of my own opinion. Bain does not have an opinion. Everyone needs to comply with GDPR whether you're a small or big business. I think it is important for the general population to know that their data is safe. GDPR made it punitive enough for companies to care but we can still do a lot with data despite GDPR. An organisation wants for its data scientists to be able to use data to make decisions.
5. People are fearful of data, is there something we can do to change that narrative? Is there anything that companies can do?
Companies need to face up to scandals. We are living in a world where advertisers are threatening to boycott Facebook for the way it uses data to market products to us. Companies need to be transparent on how they are using our data. However, we as customers need to educate ourselves and realise that marketing works. Despite being free, we need to make sure organisations are ensuring the safety of our data and are being ethical on how they are doing that. People fear that their data is being misused but at the same time we are increasingly using online services.
I think we need to show a level of maturity as well as organisations.
6. Are companies struggling with complying to regulations and using data in the right way?
I think companies are more ready than we think. There have been a lot of scandals but a lot of companies have been doing well. But there is room for improvement. Companies still struggle, in 10-20 years companies will take a more data driven approach to really take on board insights and embed that in their process. However, I believe companies will continue to struggle to comply with regulations.
7. Are there any sectors that are lagging behind innovation?
The sectors that are lagging are those without competition. Power industry is one such industry especially with hydroelectric pump stations. However, we are still seeing an increase in use of data analytics, in that industry, to understand the speed insights and maintenance logs and to see what could be improved. The innovation is slow but it is there and might change over time.
8. How to address the issue of bias in AI where the training data used may have some inherent bias?
I have been thinking a lot about this. We have to look at the variables we use and see how biased they can be. Companies need to bring in ethical viewpoints and be honest with themselves. We can also build datasets and test different ways we make decisions thus generating more insights. But this is an increasing issue.
9. Do you think young people should join the corporate sector like Bain Analytics or a startup after finishing university?
I think Bain is an awesome company and what attracted me is the variety of cases. We are really focused on adding value as a management consultancy. However a benefit of working with a startup is that you get to learn a lot of things across different divisions so you can do a bit of data engineering and a bit of data science. It depends on what you are interested in, your passions and what will get you up in the morning.
10. Do you think that graduate studies in stats or in data science will be more valuable than doing it in your bachelors?
A lot of companies are looking for a minimum of Masters degree with applied maths such as stats, data science, computer science or physics. It is nice that in the UK Masters take one year but you need to cover a lot of materials. They do shape the course to get you deeper in something that you like. Masters have a lot of value but a PhD might not be as financially valuable.