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The Annual Analytics Summit 2016

From Data to Decisions

2016 Analytics

21 June 2016 9:15am to 5pm

BMA House,
Tavistock Square London WC1H 9JP

Bought to you by the OR Society, in association with the Royal Statistical Society, the Annual Analytics Summit brings together speakers and exhibitors from the very cutting edge of analytics to deliver a one-day event that is a one-stop shop for learning about how big data & analytics are shaping the future of organisational decision making. Filled with case studies, new innovations, and strategies on how to turn data to effective decisions the Annual Analytics Summit is an event not to be missed. So join us on the 21 June 2016 and keep up to date by visiting us here or on Twitter (#TAAS16).

NEW FOR 2016 – to aid delegates’ learning the format for this year’s event will take the case studies presented in the morning and explore some of the techniques and technologies used in the projects in the afternoon sessions.

Download a summary of the talks and afternoon sessions.

The aim of this event is to demonstrate, by way of case examples, how developments in analytics are leading to increased competitive advantage. The programme will present case studies in the morning that will be business-relevant and highlight the value creation opportunities of analytics. Delegates will benefit from tutorial sessions in the afternoon that will relate to the morning talks by exploring in more detail particular techniques or methodologies mentioned.

The theme for this year’s event is Big Data Technology and Data Visualisation. Speakers will represent a broad spectrum of sectors that can benefit from advanced analytics. The programme is intended to raise awareness of applications and techniques that will inspire delegates to think about decision making in their organisation.

The Annual Analytics Summit 2016 takes place at BMA House, Tavistock Square, London WC1H 9JP 
on Tuesday 21 June 2016, from 09:15 to 17:00. Registration opens at 08:30 with tea and coffee available.

Download the programme for the event.

Places cost  £150 + VAT  to include refreshments and buffet lunch.

Megan Lucero2Plenary Speaker:
Megan Lucero, The Times
Data Journalism Editor

Megan Lucero led the development of The Times’ and Sunday Times’ first data journalism team from a small supporting unit into a key component of Times investigation.

Her team’s data analysis brought many issues into the public discourse, including blood doping in athletics, the six-figure pay of charity executives and continuing income gender inequality.

Megan also headed The Times’ political data unit that rejected polling data ahead of the UK’s last general election and is at work on a project looking at data relating to the upcoming ‘Brexit’ referendum on EU Membership.


Main Speakers Hamflett and Giles Hindle, AAM Associates and Hull Business School
The Analytics of Hunger
Andy and Giles will present an impact case study of the emerging power of data visualisation within one of the UK’s most dynamic and talked-about charities. The RCUK funded NEMODE project – delivered by Hull University Business School, AAM Associates and London-based data science and machine learning company Coppelia - aligned the Trussell Trust business model with food bank data and a variety of open data sets.  The team created the UK’s first dynamic visualisation tool for crises related to food poverty. The prototype uses foodbank data to map geographical demand and also aligns findings to 2011 Census data to predict where additional foodbanks may be needed. This led not only to immediate insights on usage patterns, and the development of a predictive tool, but also points to much greater strategic potential both for the Trust and for a wider community of charities working to counter UK poverty. Digges La Touche and Alina Marin, Movement Strategies
Insights into People Movement from Location Data
Movement Strategies provided crowd movement advice for the design of the London 2012 Olympic Park, which ultimately led to a Games-time role within the Main Control Room to capture and monitor how actual spectator movement patterns compared to expected behaviour – and to feed this into operational decision making. To achieve this, innovative automated data collection methods were deployed – and the ability to analyse and interpret that data was also a key area for consideration. Following the success of this high-profile application, Movement Strategies has spent the last four years expanding our ability to capture and analyse different sources of people movement data and use this to provide design and operational advice to our clients in the Transport, Sports and Entertainment, Retail and Cultural sectors. In this talk, Emily and Alina will introduce a range of analytical challenges we have been faced with through a series of case studies – including projects that have drawn on cellular mobile location data through our partnership with Telefonica as well as insights for long term city planning resulting from our recent Sheffield Smart Lab experience. Goody, Dept. for Education
Managing risk in the education sector using data science
The Department for Education has direct oversight of over 5000 education providers and responsibility for the regularity and propriety of funds spent within them. To do this we work to ensure appropriate arrangements for sound governance, financial management and securing value for money are in place. To aid this process a scalable systematic process of data collection and analysis is applied to help identify and intervene where appropriate in cases of financial concern.

Key OR techniques that are used to support this work are:

  • Clustering and machine learning techniques to allow us to review and analyse a wide range of large and dynamic data sources. These include decision tree learning, lasso regression, k-means clustering and k nearest neighbouring clustering.
  • Advanced visualisations, including using interactive geo-spatial analysis showing areas served by different education providers
  • Combining multiple data sources to create effective MI reports and presenting these in ways that non-analysts can understand

Pete Williams, Marks & Spencer
Embedding Analytics at the heart of Marks & Spencer
Pete Williams is one of the UK’s top data leaders and influencers. Pete is a passionate advocate of data-driven thinking and a thought leader on the use of analytics to disrupt organizations. In his role as head of enterprise analytics at Marks and Spencer, Pete’s remit includes building an analytic community to empower M&S’s data-driven future.

A number of vital decisions are made across large organizations each day. Providing insight to support better decision making is essential in today’s competitive landscape, leading companies to become more data driven. One enabling element of this data-driven movement is the evolution of new technologies, such as the Hadoop stack, that allow greater access to large sources of information from which insight can be derived. However, the implementation of big data technology does not guarantee success within an organization. So how do you drive value from big data? Drawing on first-hand experience at Marks and Spencer, Pete Williams shares practical examples and advice on how to take your data culture and capability from walk to trot to gallop.
Topics include:

  • The skills required to implement analytic approaches
  • The impact of proactive analytics on existing analytic behaviors
  • The structuring of analytic functions within a company
  • Building the links between business and analytic functions

Afternoon sessions Raper, Coppelia Machine Learning & Analytics and Richard Vidgen, University of New South Wales Business School, Sydney
Mapping in Minutes
Produce beautiful interactive maps with only a few lines of javascript. Simon will show you how he created a mapping tool for The Trussell Trust and walk you through how to create your own maps out of your organisation's geospatial data using the open source libraries leaflet.js and d3. Goody, Dept. for Education
How to Make the Leap to Data Science
Data science is an important and expanding field of work. It offers ways to harness the power of big data and transform how we work. The aspiration to engage with data science often runs aground on the challenges of trying to change the working practices of an organisation to embrace these new techniques and technologies. This talk will outline the strategies used to make the transition to data science and will include details on:

  • Open source software – How do you manage the security, stability and training implications of moving to open-source software?
  • Machine learning – How do you transition from tried and trusted analysis techniques to computer driven techniques that may be viewed as a black box?
  • Data visualisation and geo-spatial analysis – How can you create interactive and informative visualisations without big investment in new business intelligence platforms?
  • Finding the time to innovate – New and innovative approaches may not always succeed, how can you justify the time to pursue this when resource is scarce?

The talk will include examples of data science techniques in action from the department’s work and examples that audience members can replicate. Huish & Justin Sebok Marks and Spencer
Spotfire and beyond…
Find out how the analytics teams have utilised one particular technology, TIBCO’s Spotfire. Kate will cover some of the applications and its limitations, highlighting the need to have skilled people using analytical tools. Justin will then discuss how they overcame these limitations using a variety of open source programmes.


DanielMarin.jpgDaniel Marin Movement Strategies
Modelling with SENSE
SENSE is a modelling tool created by Movement Strategies, it is a GIS based simulation tool that is used to predict movement during evacuations. It assigns individuals to routes based on capacity constraints and can be used for multiscale projects. It uses fluid dynamic equations to understand how the flow of a crowd might behave. Movement Strategies has used this tool to understand movement from projects looking stadium concourses to a whole neighbourhood in London.