There is a new generational gap emerging in the world of business, driven by a group of organisations we fondly refer to as “Generation D” — for data, which sits at the very heart of how these organisations think and act.
The bad news is, according to the statistics, chances are you’re not working for one of them. The good news is, unlike many generational trends this is not related to age, so there is hope yet.
We know that data and analytics has the potential to impact how we work each and every day, and is already being used to transform entire industries for the better. Generation D organisations are data-rich, analytically driven, and setting new benchmarks in business performance.
How often have you found yourself needing to make a key business decision, but don’t have the insight to back it up? You have the data, but it’s sitting in a spreadsheet in a format that doesn’t highlight key trends or statistical insight. You simply don’t have the time, or the long-term business need, to work through a structured analytical process to load and analyze it through formal Enterprise systems.
What you need is a fast and easy way to investigate key trends, identify insight of statistical relevance, predict likely future events, and package it up with compelling visualizations that help you communicate insight to others in the team. And you need to be able to do it on your own without the need of a statistical genius or farm of servers.
What you need is Watson – and he’s bringing the power of analytics to the people!
With many clients achieving phenomenal business results from Big Data & Analytics — 150% growth in revenue, 95% accuracy in sales forecasts, 98.5% on-time delivery to name just a few — companies around the world are trying to replicate the same super productive analytical state in order to achieve their own business goals.
To be successful, you need to understand- and get in- the analytical zone.
If, like me, you were raised to always finish the food on your plate because there were less fortunate children starving around the world, you would be horrified to know that in developed nations, 40% of all food produced is thrown away before it even makes it to your plate!
Add to that the knowledge that more than 70% of fresh-water usage is consumed trying to get food from farms on to your fork. With a typical carrot in Iowa traveling 16,000 miles from farm-to-fork, do you really want to be eating that carbon footprint?
Fortunately, there are smarter ways to feed our families thanks to analytical insight.
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?