Suki Fuller describes what she does as "the language of data" and her role as an "analytical storyteller". She said: “The analytical part refers to the ability to recognise data, recognise disparate pieces of information and pull it all together. The storyteller part is when I explain that to people who don’t have the technical knowledge or background or skill set to understand what it means.”
Fuller said that she sees herself as a translator because she has to understand two different languages, “the qualitative language and the quantitative language.”
She went further and said that ‘quant people’ such as coders and engineers can build things that look really beautiful but often are unable to explain to a layperson how they built them or the tools they used to do so. “They can do it within the technical constructs and that is really good if you are talking to somebody a peer.”
Fuller said that unfortunately potential investors or executives might not have technical knowledge and so it is hard for the coders and engineers to communicate with them. She said that sometimes organisations need an external person to come in and tell them what they see from the outside looking in.
She would say to them: “I’ve spoken to these key people in your company and this is what they are telling me. Based on that and what I understand, this is where you might need to go, this is what you need to look at, this is what you need to throw away and this is what you need to keep.”
To reach this position of analytical storyteller and founder of her own company, Fuller followed a non-traditional path into analytics. Maths was never a strong point as she had always been told she was bad at it. She initially studied chemical engineering and pre-law at university in the United States, having moved there as a teenager. She dropped out and got a job at a chemical engineering lab and later went back to university do intelligence studies at Mercyhurst University.
It was a demanding course; Fuller had to pass an institutional then a departmental interview to be admitted. “The course was founded by a former deputy director of counter terrorism for the FBI. You got classes on the theory and psychology of intelligence analysis, and methodologies. So you are learning about the intelligence cycle. Gather information, organise it, correlate it, analyse it, disseminate it and feedback,” she said.
The university also had a thinktank where the students were able to work on real-world projects. Fuller worked on Department of Treasury projects as well as for a pharmaceutical consulting company and so was able to develop a comprehensive understanding of the financial technology and medical technology sectors. An important lesson she learnt about information gathering on a new topic was to speak to experts, as well as those around them, to find out who the key figures are. “Then take all that information together,” she said. Fuller returned to the UK in 2011.
As one might expect of someone for whom language and communication is a huge part of their role, Fuller can be a stickler for words being used in the correct context. The misuse of one particular phrase is a bugbear for her: artificial intelligence. “A chatbot is not AI. A chatbot is just a basic algorithm. Algorithms does not mean it is AI,” she said.
“It is very frustrating because people think they can just use the buzzwords and get away with it. Using buzzwords and not understanding what the terminology means is the biggest issue I see. They throw around ’artificial intelligence’ and ’machine learning’ and think that it is the same thing.”
Fuller believes that this happens because of the hype around machine learning and artificial intelligence. “Executives want to be seen as cool, hip, trendy. And you see it from entrepreneurs in general. Everybody wants to act like they are a tech start-up when they are a business,” she said.
Aside from her background in intelligence and precision when it comes to language, I wondered what other attributes made for an analytical storyteller. Fuller said insatiable curiosity is always helpful for someone to do what she does. She said: “I am always asking why. Which is why I like my position. I like what I do because it is always about questioning.”