Many talk about the interesting trends in economies driven by consumerism – with the rise of consumer spending on domestic products and services, fueled by growing population and higher wage earners across many of world’s growth markets.
Couple this with the rise of Connected Consumers – those living a digital lifestyle who expect to be able to run their lives through a smart phone and will quickly (and publicly) comment on the value of your brand when you fail to support them in doing so. Suddenly we find ourselves in an age where the Connected Consumer is King.
Historically, small to mid-sized businesses (SMB) have struggled to access the significant return on investment offered by predictive analytics, simply because they don’t have the capital expenditure, time and skills required to implement the technology. That is, until now.
You asked for a way to derive predictive insight without the need to acquire statistical expertise and invest capital. IBM Analytic Answers with predictive analytics offered as a service, hosted via a cloud subscription to provide predictive insight on your data.
In 1997, Garry Kasparov, a human, famously lost a chess game to IBM Deep Blue, a machine. There-in started the age of “Man vs Machine” – a hot topic for many boardroom debates and box office movies. What many may not know, is the events that transpired in a freestyle chess tournament held in 2005. Neither Man nor Machine took home the title, it was in fact two men and a machine working in cooperation that reigned supreme and took home the title.
In Shyam Sankar‘s TED presentation “The rise of human-computer cooperation“, he so rightly points out that “brute computing force alone can’t solve the world’s problems“. Least of all, the world’s analytical problems. Which is why Man and Machine must team to drive greater insight.
To celebrate my mother’s birthday, this post is dedicated to fixing one of her frustrations – being overwhelmed with information that delivers very little insight.
Have you ever found yourself in the situation where you’ve had to make an important business decision, IT have given you a 100-page report (that took months to develop) and yet you can’t find the one answer you need to make the right decision?
Normally I write about what I know. Today I’m writing about what I wonder.
In case you haven’t already noticed from previous posts, I’m really passionate about sport. Born and raised in Melbourne, the home of Australian Sport, it really isn’t a surprise. Which is why I’m so interested in how analytics is being used to transform the world of sport.
In previous posts I’ve talked about how analytics is helping the Leicester Tigers better predict and prevent injury in players, and how social media is determining a whole new dimension of “winner” in the Grand Slam Tennis tournaments.
But I wonder, can analytics help us to identify junior and amateur players that have the greatest potential to turn pro?
The IBM Information on Demand event kicked off this morning with inspiring stories in to what customers are achieving today and a taste of the technological innovations of tomorrow. We were encouraged to “Think BIG”, inspired by Conoco Philips’ use of satellite analytics to track and predict movement of icebergs, to Premier Inc. using healthcare analytics to better understand the cause of infections contracted in hospital in order to predict, prevent and save lives.
But there were three key notes that stood out from the keynote that I just had to share.
You may have seen me tweet this week about how unlikely it was for me to find inspiration for my blog at the supermarket. I was wrong!
With two sick kids and a husband away for the weekend, I was looking for a smarter way to do my grocery shopping. I decided to try out the new “Click & Collect” approach – that is to order my groceries online and pick them up in store the following day. Everything was going according to plan – the website knew who I was, and knew from their loyalty program the items that I purchase regularly and suggested I include them in my basket. It also made recommendations on products I might like based on items I had in my shopping basket. Feeling like the supermarket chain knew me and my shopping needs, I happily paid for my groceries and went to collect them the following day.
The problem was, even with all that analytics and insight, they forgot to act.
Spending a summer break working the International Motor Show, I was privy to getting up close and personal with the many concept cars on display. Sleek lines, spectacular colors, racing stripes…everything you could want in a car. Until you popped the hood that is, and saw the cheap, far-from-powerful engine that can barely reach 15kmph underneath.
As the daughter of a car racing driver, I am proud to say I have never purchased a car without popping the hood and evaluating the engine that is responsible for getting me where I want to go. Unfortunately, I can’t say the same about technology. When it comes to analytics, how many of us have been guilty of buying the concept, and dismissing the need for the car?