Tuesday, August 19, 2014

The Bracken Bower Prize

The Bracken Bower Prize is a new initiative that's intended to motivate younger authors to identify and analyse future business trends. It's an important award that could well be of interest to applied econometricians, so here are the details that were sent to me:



Introducing the Bracken Bower Prize

The Financial Times and McKinsey & Company, organisers of the Business Book of the Year Award, want to encourage young authors to tackle emerging business themes. They hope to unearth new talent and encourage writers to research ideas that could fill future business books of the year. A prize of £15,000 will be given for the best book proposal.

The Bracken Bower Prize is named after Brendan Bracken who was chairman of the FT from 1945 to 1958 and Marvin Bower, managing director of McKinsey from 1950 to 1967, who were instrumental in laying the foundations for the present day success of the two institutions. This prize honours their legacy but also opens a new chapter by encouraging young writers and researchers to identify and analyse the business trends of the future.

The inaugural prize will be awarded to the best proposal for a book about the challenges and opportunities of growth. The main theme of the proposed work should be forward-looking. In the spirit of the Business Book of the Year, the proposed book should aim to provide a compelling and enjoyable insight into future trends in business, economics, finance or management. The judges will favour authors who write with knowledge, creativity, originality and style and whose proposed books promise to break new ground, or examine pressing business challenges in original ways.
              
Only writers who are under 35 on November 11 2014 (the day the prize will be awarded) are eligible. They can be a published author, but the proposal itself must be original and must not have been previously submitted to a publisher.

The judging panel for 2014 comprises: 
Vindi Banga, partner, Clayton Dubilier & Rice
Lynda Gratton, professor, London Business School
Jorma Ollila, chairman, Royal Dutch Shell and Outokumpu
Dame Gail Rebuck, chair, Penguin Random House, UK

The proposal should be no longer than 5,000 words – an essay or an article that conveys the argument, scope and style of the proposed book – and must include a description of how the finished work would be structured, for example, a list of chapter headings and a short bullet-point description of each chapter. In addition entrants should submit a biography, emphasising why they are qualified to write a book on this topic. The best proposals will be published on FT.com.

The organisers cannot guarantee publication of any book by the winners or runners-up. The finalists will be invited to the November 11 dinner where the Bracken Bower Prize will be awarded alongside the Business Book of the Year Award, in front of an audience of publishers, agents, authors and business figures. Once the finalists’ entries appear on FT.com, authors will be free to solicit or accept offers from publishers. The closing date for entries is 5pm (BST) on September 30th 2014.




© 2014, David E. Giles

David Mimno on "Data Carpentry"

There's a post on David Mimno's blog  today titled, "Data Carpentry".

I like it a lot, because it emphasises just how much effort, time and creativity can be required in order to get one's data in order before we can get on with the fun stuff - estimating models, testing hypotheses, making forecasts, and so on. I know that this was something that I didn't fully appreciate when I was starting my career. And when I did get the message, I found it rather irksome!

However, the message isn't going to change, so we just have to live with it, and accept the realities of working with "real" data.

In his post, David explains why he doesn't like the oft-used term"data cleaning" (which makes us sound like "data janitors"), and why he prefers the term "data carpentry". Certainly, the latter has more constructive overtones.

As he says:
"To me these imply that there is some kind of pure or clean data buried in a thin layer of non-clean data, and that one need only hose the dataset off to reveal the hard porcelain underneath the muck. In reality, the process is more like deciding how to cut into a piece of material, or how much to plane down a surface. It’s not that there’s any real distinction between good and bad, it’s more that some parts are softer or knottier than others. Judgement is critical.
The scale of data work is more like woodworking, as well. Sometimes you may have a whole tree in front of you, and only need a single board. There’s nothing wrong with the rest of it, you just don’t need it right now."
A nice post, and a very nice "take" on a crucial part of the work that we do.


© 2014, David E. Giles