Between 2000 and 2013 I had the same family doctor as Mama Cass, Roman Polanski, Prince Ernst of Hanover, and Margaret Thatcher.
My doctor was amazing – he had no computer, a nice carpet, and at my young age I would be offered a scotch and a cigarette on arrival.He would deal with problems un-embarrassingly. If I needed a prescription he would go into a 1984 version of “Pharmaceutical Yearbook” and dig out a medieval chemical and assure me that “Michael around the corner” at the local pharmacy had exactly 3 bottles. And he was always right. And it always worked.
Yet he had no computer.
My Family Doctor | Source: eatonsq.blogspot.com
Cast forward 6 years later to 2019 to another family doctor - my friend Dr. Wu.
As a student, the free-time (and lack of money to go out) in the evening allowed him to self-learn Python and R and experiment with Healthcare Analytics. So much so, that in this spare time he developed a programme to look at Diabetic Retinopathy – a way diabetic people’s eyes can degenerate.
Diagnosis of Diabetic Retinopathy |Source: Anjui Wu 2018
His experimental programme takes away the clinician’s task of diagnosing the condition – which typically takes around 30 minutes – to HALF A SECOND with 96% accuracy through analytics, leaving the clinicians to concentrate on treatment.
Across various interests, Dr. Wu has already won five international awards from MIT (iGEM Gold Medal), GlaxoSmithKline (1st Prize, Elite Program), National Taiwan University, and the International Chemistry Olympiad, received nine academic grants, and interned at John Hopkins, USC, and Cambridge.
To put things in perspective, once when he was late for lunch, he told me it was because he had to drop by a laboratory and reconfigure some DNA.
I usually blame the subway.
Interviewing Dr. Wu for this Blog | Source: D Warne 2019
So, we now have family doctors who not only use analytics to aid them in their role, but embrace experimentation of analytics in their spare time. The new Explorers.
Observationally, the last years’ thinking was that using Analytics in a self-served, day-to-day way was the preserve of a.) young people who are tech-savvy and b.) data scientists. But today we should add a third category to this – c.) the Productive.
Dr. Wu is arguably young, and a data scientist, but moreover he is Productive – he wants to work in a way that gets to the right answer quicker. What I mean is, anybody that needs and wants to be more valuable through being more productive, accurate, and fast, needs and wants data and analytics.
And that’s at every generation and experience level.
Many things work well and look good over the age of 40 | Source: D Warne, 2019, Beverly Hills CA
So, what is the significance of this for you, and for Qlik? Firstly, the philosophy behind Qlik’s products has always been simplicity, speed and many other functional advantages.When married with business users from your organisations, our customers are quickly realising the power of analytics in terms of the value and productivity this brings to their roles – pace, process elimination, more collaborative, accessible anywhere, accurate, and fun, to name a few.
What this means when you are planning investment, implementation and adoption, is that communicating this value early and often, is paramount.
So, when you are thinking about your organisations – why and how you are using modern technology, Analytics, and Lots of Qlik, in other words your strategy, think about a few things:
- Find the Value and Sell the Value – put in place measures early on to understand how analytics is making productive impact – it might be cash generation or savings, it might be metrics (such as “I halved this or doubled that”), it might just be people’s stories “I’m SO much less frustrated! I couldn’t do this before”. Data and Insight driven organisations are more financially successful than those who are not (Sources: McKinsey, Strategy&, University of Pennsylvania - The Wharton School et.al.)
- Like Dr. Wu, have Fun. A data-insight driven culture breaks moulds. Use it to your advantage, and make it a cornerstone of any wider organisational transformation
- Lastly, Analytics for All – think about which groups or personalities are your Explorers who have a hidden craving for insight and faster better decision making.Is it just the Finance Analysts, or could it be a practice nurse, a cleaner, a teacher, older employees, or people we perceive to be “happy” doing things the same old way
You CAN teach an old dog new tricks and take them to a happier place | Source: D Warne, 2019, St Johns Wood, London
From the Nerdy to the Needy, we are in an era where increasing individual and corporate productivity is essential. Historically, there were generational gaps in technology usage, but today anything goes – for anyone. Identifying and nurturing our technology Explorers drives forward our organisations, our individuals, and society as a whole.
How are YOU identifying your new Explorers of Analytics?
This article is written with thanks to the awesome Dr. Anjui Wu M.D. PhD, University College Hospital London