May you live in interesting times – or so the old Chinese curse goes. Well, we’re certainly doing that. In 2017, the global economy was firing on all cylinders, and things weren’t looking too bad. Since then, a mixture of protectionism, the Sino-US trade war and economic uncertainty has changed
The Economist magazine takes pride in its ability to provoke deeper thinking. One of its campaigns was to ask people to taste weird-looking foods, such as smoothies made from “ugly” produce that had been rejected by supermarkets. The idea was to stimulate participants to reassess what was important to them.
As Malcolm Gladwell reminded us at the World Business Forum There is a time to innovate and a time to reap success. History, both recent and less recent, is full of examples of great innovations that had to wait years, if not centuries, to become successful. Why was this, though?
So, you want to compete and become a data-driven organisation, like everyone else in your market? Increasingly, organisational use of analytics has moved beyond process improvement, as analytics maturity increases. The most advanced organisations are now using data and analytics to generate new business models, products and services. In practice,
It suddenly seems as if artificial intelligence (AI) is all around us. It is already having a huge impact in a wide range of sectors, including health care. We are now starting to see it move into the manufacturing sector as an important part of Industry 4.0, the digitisation of
In my previous post, I suggested that it was possible to provide a road map that would help with the introduction of artificial intelligence, advanced analytics and machine learning into insurance companies. This post outlines the process. Start at the beginning The first area to address is applications where the
Recently, as a result of the EU’s General Data Protection Regulation (GDPR) and other regulations, new governance requirements for data management have emerged. These have had some interesting effects on the data preparation process. This post is the third in a series on data preparation (Data preparation in the Analytics
This post is the second in a series on data preparation based on a webinar about its role in the analytical life cycle. The first discussed how data preparation fit into the analytical life cycle. This post considers some trends in data preparation and some of the structures and processes
The increased availability of data is opening up a new world of analytics to insurance companies. There are both new sources of data and also increased volumes of information, and together, these are being used to generate insights and influence decision making. This post, the second in a series on
Data preparation is often seen by companies as a difficult and dangerous job, one best left to IT. However, business departments often do not want to wait for their data, so thick SQL books and spreadsheet applications are booming in most offices. This does not really make sense, however you
