Reinventing business models with Big Data Analytics

From a business perspective, the purpose of Big Data Analytics is ultimately to improve competitiveness and impact by making better business decisions that can be acted upon. Such decisions are backed by relevant and reliable facts collected from a variety of sources, providing insights based on trends and patterns which the human brain would never have found, in turn enabling a predictive approach to decision-making.

Every single industry is impacted by Big Data Analytics as digital transformation accelerates. Individual companies and public organisations are trying to make sense of all the changes, determining which are opportunities and which are threats to their activities.

As entire industries reinvent themselves, taking advantage of data-driven business models, we decided at BSL to zoom in on a few sectors and invite guest speakers to help us understand the business challenges each faces as well as how Big Data Analytics is helping them find a path to resolution, sometimes by reframing the challenge.

  • As Public Healthcare seeks to improve our quality-adjusted life-years, Big Data Analytics help direct the right care to the right person at the right time. Treating illnesses earlier, sometimes even preventing them, positively impacts society and the economy. Kevin Dean, Managing Director of Smart Health Science Limited and former Director of the Genomics England Project, shared with us how Big Data Analytics is used to accelerate our medical understanding and decisions, thus improving lives and saving costs. One of the main challenges with these often decade-long projects is to balance what is viable with what is affordable – in other words, to prevent costs getting out of hand without steering away from the end goal. Finding immediate applications for the technology is a good way to improve affordability.
  • The Financial Services sector uses Big Data Analytics extensively to inform better investment decisions and to improve their client experience. Who better than the world’s largest asset management company to talk to us about Big Data? David Wright, BlackRock’s EMEA Head of Product Strategy for their Scientific Active Equity (SAE) Group, shared how self-learning algorithms are driving 1,000+ investment decisions daily for parts of BlackRock’s portfolio. To be able to do that, the algorithms analyse over 4,000 brokerage reports a day as well as transcripts of earnings calls, correlated with external data sources ranging from satellite imagery to consumer sentiment based on online search behaviour. Constructing better economic indicators whilst de-risking investments is the main goal.
  • A fascinating talk with Anne Mellano, co-founder of the Swiss startup BestMile, gave us insights into what Public Transportation will look like tomorrow. BestMile offer the world’s first Cloud platform for the operation and optimization of autonomous vehicle fleets. She shared with us today’s main public transportation challenge, which is that users need to adapt to what is offered, no personalisation is possible. Also, no matter how good the historical data, public transportation will always be planned based on past trends (pick-up locations, routes, timetables, capacity, etc.). BestMile are reframing the challenge by imagining an urban public transportation model which adapts to individual user needs through real-time routing and capacity management based on big data analytics feeds from various sources, including user devices such as smartphones. Sharing the mode of transportation will also help solve our urban congestion and pollution challenges.
  • With urban migration leading to >60% of the world’s population living in cities by 2050 (UN report), and with cities representing only about 2% of our available landmass, there are many challenges to be addressed urgently. Health, safety, movement, jobs, construction, education, entertainment and the list goes on. Nicola Villa, Global Leader of Digital Platforms for Government at IBM, shared with us the concept of the Cognitive City. A city where the Internet of Things (IoT) platforms are successfully addressing the various urban challenges and enabling us to shift from smart city to smart citizens. We are all co-responsible for the quality of life we aspire to in our cities around the world.

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  • Whatever the industry, tomorrow’s talent needs to be more agile, curious and collaborative than has been required in the past where the focus was more on hard skills. So, to wrap up our Big Data Analytics course, we invited an expert in Human Resources to share with us the role that technology is playing in redefining that industry. Paul Jacquin, Managing Partner of Randstad’s Innovation Fund, explained how recruiters are changing their approach to sourcing, screening and selecting the right talent. Increasingly, online tools based on self-learning algorithms are testing candidates, managing the hiring process and finding the best match with employers. Sometimes, it’s even the other way around with several employers bidding for the right candidate. Often we are victims of unconscious bias which leads to people hiring people like themselves. Also, the traditional application process of sending unsolicited CVs can be highly frustrating for candidates. And for employees, the cost of hiring the wrong person is very high. Big Data Analytics addresses all these issues, helping reduce the hiring timeline and the associated costs whilst finding the best candidate match.

Getting our BSL students ready for this changing digital world is paramount for their success and their ability to contribute to our collective future. This requires a sound understanding of the use and implications of Big Data Analytics. As one of the leaders at BlackRock says: “All employees are responsible for being students of technology”. That responsibility starts even before becoming an employee.

Author: Anja Langer Jacquin,
Professor at BSL