Interview with Susan Etlinger, analyst at the Altimeter Group and TED Speaker
When it comes to major trends, people are embracing them in an instant and start boasting about their endless benefits. There are few of us though in the midst of the wildfire-like spread of the trends who have the lucidity and power to take a step back and tell people to curb their enthusiasm. Nowadays, this is the case with the Big Data trend – everyone is excited about gathering it, using it and analyzing it in order to obtain the insights that may trigger the competitive edge, the decisive discovery, etc.
But as the amount of data grows, we, as users and human beings have to also grow and evolve our capacity to process and understand it. And a major role in this endeavor is played by Susan Etlinger, an analyst from the Altimeter Group, who, in November 2014, had a breakthrough TED Talk on humanity’s need to strengthen its critical thinking in order to use Big Data at its full potential. Her talk has now been watched more than 750,000 times.
In a continuation to her talk, our discussion with Susan drove us further into her vision on the way we should do a bigger effort to understand and use Big Data.
‘After I gave the talk at IBM and TED posted it online, it generated an impact across many audiences, some expected and some totally unexpected. From Big Data experts to academics to parents and up to specialists in digital ethics, people started writing to me on Twitter, on my blog, to confirm to me that they felt that critical thinking is key to not missing the right signal in the sea of data we are exposed to every day. Whether it’s healthcare or politics or other issues of our society, it’s critical thinking that will make us come up with the right questions in order to get good answers from the incredible amount of data we now have.’ explains Susan, while adding the example of the recent Ebola outbreak in California that data scientists could not perfectly anticipate due to a lack of adaptation of the analysis tools they were using.
But who is responsible for these discoveries? Are the data analysts or the data scientists assigned to improve our thinking and our algorithms of discovery? ‘You know, people are still using these terms interchangeably. A Berkeley professor I know refers to data science as a kind of applied statistics, while some would call a data scientist “an analyst who lives in Silicon Valley.” Susan stops for a bit, thinking about the many companies she worked with as an analyst at Altimeter.
Our discussion leads to the inevitable debate of the business vs IT modern battle for the data power. ‘This is the biggest disruption happening within organizations nowadays and it can either decisively drive or totally hinder the adoption of data strategies. But the most important principle is that the business and IT have to collaborate in order for a data strategy to emerge and be effective. The IT organization needs to understand the context in which data is enhancing the business while the business side needs the tools and the methods to generate this enhancement on a constant basis.’
The collaboration on which Susan is putting an emphasis is crucial for the years to come. She talks about the rise of unstructured data and the need for new analysis methodologies that can be devised only through collaboration between IT and business. ‘Have a look at the stock market – just at the NY Stock Exchange, for example – it is generating billions of stock transactions per day but in terms of taxonomy, a trade is a trade while a few million tweets are far more complex from an analytical point of view.’
And the puzzle of making sense of social media data is one that PR, marketing and advertising combined are trying to solve. ‘In the past, decisions were based on grey hair – expertise and experience were the ultimate decision makers. But now, through data and with the right questions, companies can truly explore people’s opinions about relevant issues – food companies can understand how people feel about GMOs, financial institutions can dig deeper into people’s views on legislation, etc.’
But, she says, it’s important not to let siloed organizational structures drive analytics. Business strategies must be created based on data, data that is pervasive across the whole company and coming from data-driven collaboration between departments.’
If asked the right questions, Big Data can do more than just create an overview of any industry or part of society – it can enhance its performance. And – for long-term thinking – it can impact education in such a manner that Big Data technologies will get enhanced themselves by teaching children to have data-driven critical thinking. Used correctly, Big Data analysis can influence education at a macro and micro level as well; from better understanding of learning styles to tailoring teaching methods to improving education at an individual level depending on human variation – from children who are linear thinkers to the ones who understand the world through concepts or the ones with learning problems.
‘It’s just the beginning of our understanding. We can understand a lot through data but we have to prioritize what’s most important to understand.’ concludes Susan.