Bloc Hotels: Using AI to Power Hotel Revenue Management

Image result for bloc hotel logoAt Bloc Hotels we have spent the past 5 years developing our own proprietary revenue management system to help manage our room inventory and optimise room pricing. The system incorporates data from a wide array of data sources such as the Property Management System, Online Travel Agents, hotel reviews, Google Analytics, flight information, and local events. It allows us to breakdown and analyse all of this information using a very intuitive web application, and uses AI for demand forecasting and price optimisation. The solution is hosted and managed on Amazon Web Services (AWS). The system is an integral part of our pricing process and has significantly improved pricing strategy and efficiency.

We partnered with Spectra Analytics to develop and manage the system because of their extensive AI and Data Science expertise and their ability to manage cloud computing solutions. They have provided excellent support and guidance over the years and we would highly recommend them to other companies looking to develop AI solutions and use AWS.

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£1m Funding Award to Improve Primary Care using AI

[Manchester, UK, May 28th] Spectra Analytics is delighted to announce a £1m funding award from InnovateUK to use Artificial Intelligence (AI) to improve shutterstock_284499977NHS Primary Care. The PA
TCHS project, in collaboration with the University of Manchester, Salford Clinical Commissioning Group, and Manchester Health & Care Commissioning, aims to ease access to GP care for urgent cases and reduce GP waiting times. PATCHS is expected to improve patient satisfaction and reduce pressure on staff. Trials are taking place in interested GP practices over the next 2 years.

Primary care is at breaking point nationally as the demand for GP appointments continues to rise whilst under-investment continue
s to squeeze resources. Consequently, waiting times have risen, as have instances of patients being unable to see their GP when required. This is potentially endangering patients and putting immense pressure on GPs.

Effective triage procedures – directing patients to the appropriate care based upon clinical needs – can improve the situation. Research suggests 27% of GP consultations are potentially avoidable with patients better seen by another healthcare professional such as a nurse, pharmacist, or mental health worker.

GP practices do not have standardised triage processes, so the approach can vary significantly between practices. Some have adopted triage technologies but Dr Ben Brown, Wellcome Trust Fellow at the University of Manchester and practising GP, says “Current triage technologies are gnerally not very sophisticated, which means that they either make a large number of incorrect triage decisions, putting patients at risk, or rely heavily on medical staff, increasing workload. Furthermore, the effectiveness of these technologies has not been rigorously evaluated”.

PATCHS uses AI to analyse patient symptoms, medical history, and a range of other factors such as weather and pollution, to determine the type and urgency of a GP appointment request. It then directs patients to the appropriate care professional. CEO of Spectra Analytics, Dr Marcus Ong, says that “This data-driven approach potentially allows the AI to analyse a far broader range of factors that can influence the urgency of a patient’s GP appointment request. It also means that we can tailor triage decisions for individual patients.

Trials are being held in Salford and Manchester over the next two years. Kirstine Farrer, Head of Innovation and Research at Salford CCG, said “Digital innovation is of utmost importance to Salford CCG, and we are keen to support projects that have the potential to improve the efficiency and quality of primary care. We are keen to assess how PATCHS can help manage patient demand and reduce GP workload.” 

If you are interested in finding out more about PATCHS please contact Dr Marcus Ong at Spectra Analytics, email info@spectraanalytics.comor call 0203 968 7800.

Spectra Expands Leadership Team

We are delighted to announce that Spectra are expanding our leadership team. Our Chief Science Officer, Dr Dan Sprague, is extending his role to include Chief Technology Officer, and we have three new team members: Chris Crowther (Chief Information Officer), Steve Williams (Head of Business Development) and Dr Ben Brown (Chief Medical Officer). These appointments will significantly strengthen Spectra’s expertise in Security and Defence, Finance and Healthcare. Their extensive experience will also support Spectra’s ambitious growth plans.

Dr Daniel Sprague

Chief Technology Officer & Chief Science Officer

dan_sprague2In his CTO role, Dan leads Spectra’s technology and software delivery. A full-stack developer, Dan has extensive experience in developing and managing production level systems, database design, system testing architectures, and implementing security protocols. He is also experienced in front-end software development and UX design. As CSO, Dan leads the Data Science / Artificial Intelligence team. He is an expert in statistical modelling and machine learning. He also acts as an external academic supervisor for PhD/MSc students at the University of Warwick.
Dan holds a PhD in Complexity Science from the University of Warwick where he also obtained an MSc in Complexity Science. Previously he read Physics (MPhys) at the University of Oxford. He is also a Certified Prince2 Practitioner with experience of Agile project management.

Chris Crowther

Chief Information Officer

chris_crowther2Chris has over 25 years’ experience in the information assurance and security domain. He is uniquely qualified to understand the evolving threat environment, as well as having an exceptional track record of driving and delivering change in complex organisations. He is a global digital leader with senior experience with the UK military and other Government Departments, US Military and Federal Government, the United Nations, KPMG and Airbus. Amongst a plethora of awards and accolades from the UK and US, Chris’ contribution to the world of Information Risk was recognised in 2016 by his qualification as a CESG Certified Professional Lead Security and Information Risk Advisor. Chris is co-founder and chair for the West of England Cyber Cluster.

Steve Williams

Head of Business Development

steve_williams2Steve is an established leader with over 30 years experience in the capital markets and an extensive background in technology infrastructures. He is the General Manager of DXC Fixnetix. Previously Steve was Global COO for Equities Electronic Markets at Citigroup and General Manager for BNP Securities where he oversaw the firm’s Japanese business and headed all equities trading across the region.

Dr Ben Brown

Chief Medical Officer

ben_brown2Ben is a practising General Practitioner (GP), and expert in developing advanced analytic clinical software. In addition to his medical training, Ben has qualifications in health informatics (PhD), public health (MPH), and leadership (MSc). Ben’s unique career provides him with insights into the challenges of day-to-day clinical practice, combined with the skills to harness data science to address them. This has allowed him to build a strong track record of developing software implemented into NHS clinical practice. His work has been published in over 40 peer reviewed scientific papers, and has won awards from the International Medical Informatics Association, British Computer Society, and Royal College of General Practitioners.

CogX – The festival of all things AI

CogX 2018,cogxlogo the “festival of all things AI”, drew over 6000 attendees and 300 speakers from across technology industries and expertise, ranging from company CEOs to early career research students. Included in this attendees was one of our resident data scientists, as well as many students from the University of Warwick doctoral training centres in Complexity Science and Mathematics of Real World Systems – the very PhD schemes that have given rise to many members of Spectra, as well as being the birthplace of our company itself.

CogX Robot

Companies big and small exhibited content. The expo part of the conference contained a startup village showcasing a variety of new companies in AI and robotics. Larger companies also exhibited content, such as Microsoft Azure and data analysis platforms being used to recommend people their perfect juice (unfortunately including beetroot). Tesla were also showing off their famed car. Google, IBM, and BT each hosted pavilions to demonstrate their latest technologies. Newer dedicated data companies such as Pivigo, Seldon, and were also showing off their various data-focused product platforms.

Seldon was also one of the many companies giving talks throughout the conference. Seldon, Nvidia, and others spoke of the various infrastructures they’ve developed, including data source and optimised software made available to push forward deep learning research in the case of Nvidia. The Financial Times hosted a stage all of their own. Representatives from many companies and academia were involved in many talks and discussions, including AI specific ones such as BenevolentAI and the Open Data Institute, and broader ones such as Deutsche Bank and the Financial Conduct Authority. Government representatives, such as Matt Hancock the Secretary of State for Digital, Culture, Media and Sport, were in attendance. The Turing Institute were also hosting research specific talks, including that of Warwick Complexity alumni Merve Alanyali.

The content of talks were wide ranging, but largely focused on the impact of AI and the broad issues in the future of AI. Ones of particular interest included discussions on the impact AI will have on the economy, mostly on the impact of automation on employment and whether we may be able to achieve a dream future where AI take on the mundane jobs and humans are left with loftier goals. There CogX 2018 Talkwere also discussions on fake news, the many different kinds and motivations that exist, and how organisations such as Full Fact are attempting to combat it. Finally, there was a great deal of talk on the use of AI in seeking a cure for cancer, and in extending life, concluding that complex treatments for complex diseases need machine learning to draw on a wealth of information, as the expertise of a single doctor can only go so far.

If nothing else, this event very effectively showcased the excitement, interest, and range of talent currently in AI. AI, machine learning, and data science are constantly developing tool sets that can give immense utility to any and all businesses. To begin taking advantage yourself, contact Spectra Analytics for a free consultation to see how we can apply our cutting edge data science and business intelligence techniques to help you grow your business.

Modelling fertility in rural South Africa, Rob Eyre

Individuals living within the study area of the Agincourt HDSS. Image by A Khosa, courtesy of
Individuals living within the study area of the Agincourt HDSS. Image by A Khosa, courtesy of

One of our data scientists Rob Eyre recently published a paper in Emerging Themes in Epidemiology on modelling fertility in a poor rural region of South Africa using an innovative non-linear approach (the full paper can be found here).

A common issue throughout much of quantitative Public Health research is the application of a range of standardised statistical methods even when such methods are not appropriate. Such standard methods often assume the relationships being modelled to be linear, despite this assumption often being unjustified. One such area where this is the case is in the modelling of how fertility changes over different socio-economic characteristics such as age, education, and social status.

A core aspect of the work we do here at Spectra Analytics involves using more modern, sophisticated, and well-thought-out methods that provide better results to our clients. In line with this, Rob’s research used an innovative combination of a non-linear parametric model of fertility over age, with the use of the highly flexible semi-parametric machine learning method of Gaussian process regression to bring in further variables such as socio-economic status for which no established fertility pattern model exists.

Rob and his research colleagues – Thomas House of the University of Manchester, F. Xavier Gómez-Olivé of the Agincourt research unit in South Africa, and Frances Griffiths of the University of Warwick – successfully applied this method to data from the Agincourt Health and Socio-Demographic Surveillance System (HDSS), run by the Medical Research Council/University of the Witwatersrand Rural Public Health and Health Transitions (Agincourt) Research Unit. This is an annual census performed in a poor rural region of South Africa, collecting information on births, deaths, migration, and many different health aspects. The results of this analysis provided more robust and reliable estimates of the fertility patterns within the Agincourt study area that are free from unjustified assumptions of linearity.

The researchers hope this work will encourage others working in fertility modelling to look beyond standard methodology and be more thoughtful about what methods they use and the assumptions they make when using these methods.