Spectra Analytics - Consulting Services
Our Services


Spectra Analytics works across a broad range of industries from healthcare to marketing and finance. We aim to empower businesses by generating actionable insights from their data.

Our bespoke solutions may be implemented in new or existing proprietary systems or increase the flexibility and sophistication of standardised platforms.

Data Management

Data Management

This includes database management, data cleaning and enrichment from public and private sources (where possible) including social media

Data Analysis

Data Analysis

Providing business insights through mathematical and statistical modelling and machine learning.



Develop cutting-edge research for academia and business



Provide consultancy services for businesses on data analytics

Spectra work on fixed term projects and on a consultancy basis. Please contact us to see how we can help.

Here we outline some of our current work and ways in which data analytics are being used more broadly. Spectra would be excited to discuss the potential for these or any other research projects for your business.


Spectra has very close ties with Academia. We publish research papers, supervise postgraduate students and are regularly included as industrial partners in academic funding proposals. Most recently we participated in a successful bid to renew EPSRC funding for the UK Network on Emergence and Physics far from Equilibrium. We also active in training the next generation of data scientists through our internship programme and our training courses.

Our Clients

Spectra worked with the University of Warwick and the University of Coventry to implement algorithms to calibrate assessor scores for panel assessments. The purpose was to calculate the ‘true’ value of evaluations and estimate assessor biases.

We implemented the algorithms in Excel, Python and in an application. These are now being used by some universities to calculate student results.

These algorithms are available for general download from the Calibrate with Confidence site; which also explains in detail how these algorithms work.

“Because of [Spectra’s] excellent high-level provision, their outstanding customer services and their reliability, the AMRC plans to continue to engage Spectra Analytics for future scientific support.”

– Prof. Ralph Kenna, Coventry University


Finance produces a vast amount of data and is an avid user of data analytics. They produce extensive data from transaction records, customer service records, asset prices and research to name but a few. This data is being used to gain a better understanding of their clients, to predict their needs, to provide tailored services and prevent fraud and illegal activity. It is also being used for risk management, to assess market and counterparty risks and for investment analysis.

Finance is a major focus for Spectra due to our extensive background in investment banking.

Research areas include:

  • Quantitative & Behavioural Investment Analysis
  • Risk Management
  • Identifying Illegal Trading Activity
  • Data Visualisation
  • Data Mining

Spectra are developing new approaches to trading and risk management, some of which we have published as research articles. Such methods include applying Fuzzy Logic to stock picking, systematic trading strategies using Genetic Programs and using Self-Organising Maps to identify similar risk factors between countries.

Our Clients

XBZ is a financial brokerage company specialising in equities with whom we developed a system to automate trade reporting to comply with MiFIDII regulations; as required by the Financial Conduct Authority (FCA). By integrating data from a variety of sources we were able to automatically construct the required reporting analysis.

“We are very happy with the quality of Spectra’s work and were extremely impressed with the timely and efficient delivery of their solution. I could not recommend the services of Spectra Analytics more highly."

– Greg Lavey, XBZ

Fixnetix provides market data, trading access, liquidity venue connectivity and pre-trade risk services. We are currently collaborating to develop state-of-the-art algorithms to detect illegal trading and market manipulation in the financial markets.


Healthcare is one of the major producers (and consumers) of data. Data is constantly being produced from real-time medical recording equipment and health monitoring services. Medical facilities have huge databases of patient records. The amount of medical data is likely to explode over the next few years with wearable technology incorporating health monitors and the expansion of genome and exome sequencing for personalised medicine.

This data is being used to by medical facilities to monitor and treat patients and by governmental departments for oversight. Pharmaceutical companies and academics are using the data to develop new treatments and monitor the spread of diseases such as TB and Ebola.

Healthcare is a major concern to us all and a primary focus for Spectra. We build upon the experience of our CSO Dr Dan Sprague's background in epidemiology and his experince as a consultant for USAID where he advised healthcare monitoring and evaluation teams on the use of statistics and assisted in analysing healthcare behaviour and the health system in Uganda.

Our Clients

Spectra are currently working with the Liverpool School of Tropical Medicine on a Unicef funded project to develop a tool that will assist field researchers design surveys for health studies. We are also looking to build on Dr Sprague's PhD research to apply more sophisticated statistical methods to the surveys and visualise the results for policy makers. You can access the LQAS Sampling Plan Calculator here.


The hospitality industry produces large amounts of data on people's travel and interests. This is particulalry, true of Online Travel Agents such as Expedia and Booking.com who track hotel and flight prices in real time. This data is helping consumers find better accomdation at better prices but it is also helping hotels connect with their target customers and monitor their competition.

Our Clients

Bloc is a small upscale travel hotel chain with whom Spectra has been developing a new data analytics platform. The system boasts Artificial Intelligence powered predictive analytics automatically analyses data from a wide variety of sources - such as booking systems, online travel agents, airports, local events and weather - to optimise room pricing to maximise revenues. The system monitors and analyses business metrics in real time and improves efficiency and productivity by automating report generation.


Mathematical modelling has always underpinned the insurance industry but 'Big Data' and modern data analytics methods are moving far beyond traditional actuarial science. Rather than just concentrating on claim histories, demographics and physical data, insurers are now enriching their data to incorporate other factors. The "Open Data" movement has made vast government databases available to the public showing information on health, crime and education to mention but a few. These can now be used by insurance companies to construct even more sophisticated models.

Behavioural science has also become increasingly important for the insurance industry as behaviour has a significant impact on insurance claims. For example whilst some individuals may be genetically predisposed to certain medical conditions overall lifestyle choices tend to be the major determinant in an individual's health. Some car insurance companies are monitoring real-time driving behaviour of their customers. This has actually generated a behavioural change in customers to drive more safely; significantly reducing the number of claims. They have also found that customers who pay their bills on time are more likely to be safe drivers. This all leads to reduced costs for insurers and lower premiums for customers.

Insurance is a field in which Spectra is unique as we have experience in both advanced data analytics and behavioural sciences. Our directors have conducted academic research into the affect of behavioural biases on healthcare provisions and the affect on trading and asset price dynamics.


The legal industry has hitherto been somewhat isolated from the developments in automation that have occurred in other professions such as accounting and banking. This has been due to a number of factors such as an opaque structure hindering external influence, the nuance of language eluding machines and the difficulty in analysing large quantities of unstructured data. However, things are starting to change and some believe that the industry could be ripe for disruption. Legal Futures, a UK-based news resource, predicts that technologies automating the work of associates, herald the collapse of law in less than 15 years. Whilst many do not expect such an extreme outcome other experts also believe there will be significant changes with McKinsey & Co estimating that 23% of lawyer time is automatable whilst Levy and Remus estimate this is closer to 13%. If technology can only automate a small section of research then the effect will be marginal but if some or all of the tasks in analysis and production could be automated then the impact will be significant [Reuters].

Another interesting area is Law enforcement agencies who have a treasure trove of data at their finger tips that they are able to call upon to assist them in their activities.

One of the most amazing developments in this field is predictive policing which uses data analytics to identify potential criminal activity. It can be used to predict crimes, offenders and victims of crime. Wikipedia tells us that it has already been implemented by police departments in California, Washington, South Carolina, Arizona, Tennessee and Illinois. It is also being used by Kent County Police in the UK. The Los Angeles Police Department found its accuracy was twice that of its current practices whilst Santa Cruz, California reported a 19% drop in the number of burglaries over a 6 month period.

Academics in the Netherlands have been using mathematical models to examine criminal networks a.k.a. dark networks. They found that are inefficient and that simply targeting the most connected criminals may lead them to re-organise in a more efficient way. In conjunction with local police forces they investigated cannabis networks in Amsterdam. They found that it was far more effective to target individuals with specialist skills such as the electrician in charge of heating the cannabis plants.


Marketing is one of the most common areas in which data analytics are being applied. Companies are amassing a wealth of data from loyalty cards, monitoring our in-store and online shopping habits, Twitter and Facebook messages and our likes and dislikes. This is being used to improve our customer experiences and to predict our needs (or even convince us of our needs) to sell us products. They are also using network analysis to try to identify our connections and relationships to allow for more targeted, efficient and effective marketing campaigns.

Leading the way in this field is undoubtedly Amazon who try to store every piece of information they can about their customers and their behaviours. They claim to know so much about their customers that they considered sending orders before they have even been ordered! One can see that this could clearly be useful for regular purchases such as ink cartridges. Supermarkets are also active in this area often sending special offers to customers based upon their purchasing history.

Our Clients

Sole Trader is a website development company which focuses on sole traders across UK, USA and Canada. Spectra has been working closely with Sole Trader to improve the way in which they identify leads. Spectra developed an automated system to clean, validate and enrich - from external data sources - a client database with descriptive statistics and used customer segmentation analysis to identify the most likely customers to target.

“The SoleTrader.com team and I have always been very happy with the work Spectra have undertaken for us. We would not hesitate in recommending them.”

– Seb Lewis, SoleTrader

S6 is the UK’s largest network of FA-affiliated 5 & 6-a-side football leagues with over 30k members. We worked with S6 to increase customer engagement by creating a social media interaction with their website and analysing the efficacy of Facebook marketing campaigns.

“[Spectra] were instrumental in S6 being able to get a greater understanding of its client base and reinforcing the quality of the brand.”

– Rob Morgan, S6


Data is used to try to better understand the public and forms an important part of the media machine. It allows film and television studios to determine which shows to make, advertising companies to decide when to schedule their advertisements, news agencies to ascertain public opinion and media agencies to decide how to price their products. This data is collected from a variety of sources from social media to polls and website usage. This requires not only general data analytics techniques but also statistical analysis to determine the significance of their sample data.

Data analysis in this sector has been pushed to the next level by Netflix. They developed their highly successful political drama, House of Cards, by studying the viewing patterns of their customers. They specifically chose the director, producer and stars to increase their probability of success. News media organisations, such as Sky News, are actively using data analytics to try to garner public opinion prior to the British General Election in 2015. They found a relationship between shopping habits and political affiliations.

Spectra Analytics CSO Daniel Sprague has also been active in this area. Within academia he developed a statistical model to predict the probability of a product going 'viral'. It has proven particularly successful at predicting the spread of fads driven by online sharing, such as the number of people taking part in the ‘ALS Icebucket Challenge’ charity campaign and can also be used to predict the social media 'buzz' generated by movie releases and new products.

Sports & Leisure

Top sports teams are now regularly using data analytics to analyse the performance of the team, the players and oppositions. Premiership football teams use video cameras during games, and GPS during training, to monitor player performance. They can see if the players were correctly positioned and how far and how quickly they have run. They also record all of the passes, dribbles, shorts and goals etc. This can give them a significant advantage over their competitors.

In the 2014 football World Cup, Germany (the eventual champions) teamed up with software company SAP AG to develop a custom match analysis tool known as Match Insights. One of the ways in which they used the system was to speed up their play. They were able to do this analysing and visualising their average possession time which they reduced from 3.4s to 1.1s. However, the use of statistics in sports is nothing new. The film Moneyball, starring Brad Pitt, famously portrayed the 2002 Oakland Athletics baseball team. The team was assembled based upon statistical modelling. By doing this they were able to compete against much larger teams with far larger budgets.

Our Clients

S6 is the UK’s largest network of FA-affiliated 5 & 6-a-side football leagues with over 30k members. Spectra worked with S6 to develop a web app that provides a booking management system and an analytics system to monitor key business metrics. The system analyses employee productivity and performance and marketing campaigns. The app also provides a platform for increasing customer engagement and social media interaction.

“We are very happy with the quality of Spectra’s work and were extremely impressed with the timely and efficient delivery of their solution. I could not recommend the services of Spectra Analytics more highly.”

– Ross Spacey, S6

Technology & Telecoms

These sectors are two of the main generators of data in modern society with smart phones and everyday appliances (with smart sensors) tracking our movements and behaviour. The aim is to better predict and therefore cater to our needs; thus making our day-to-day lives easier.

Digital assistants, such as Siri (Apple) and Cortana (Microsoft), built into our Smart phones can remind us of specific needs at certain times and in certain places whilst fridges can now re-order produce such as milk when we run low. Data analytics is also being used to optimize the connection between conflicting wireless devices to increase speeds and reduce signal interference.


It is predicted that the Automotive industry will be the 2nd largest generator of data by 2015. They produce an abundance of data from vehicle and manufacturing sensors to customer and dealer information. They are using this data and analytics to produce better vehicles and develop better insights into their customers and businesses.

As a result of data analytics vehicles are now safer due to more advanced testing and better for the environment due to improved fuel efficiency. Vehicles can now automatically adjust settings for driving terrain to produce a smoother and safer ride; account for hazards and changes in weather conditions to produce safer driving experiences; for personalised driving experiences by uniquely identifying drivers.

Automotive companies are also using data analytics to streamline their processes which has resulted in increases in efficiency and lower costs. They can better predict future demand to facilitate capital expenditure decisions. Customers are also seeing the benefits of improved customer services because companies can better tailor their user experiences.

Our Clients

Spectra is part of a team that has won a European Commission grant to study the accessibility of the London transport network for mobility-impaired users.

The aim of the project is to analyse how mobility-impaired users utilise the network by tracking the mobile phones over a period of 3 months and then identify 'mobility black spots' which can be raised to relevant authorities.

You can view our progress as MobiliCityX.


Data analytics have always been important for utility companies as they attempt to manage supply and demand. For instance, electricity companies monitor TV schedules to predict when households will make coffee/tea during advertisement breaks. Whilst water companies analyse weather predictions to estimate if there could be water shortages when people start watering their gardens during the summer.

With the advent of smart monitors they are now in a position to develop ever more sophisticated models of human behaviour to try to predict demand. This will allow them to optimise their processes to ensure that they manage their inventory more efficiently. It should also lead to reduce costs for customers.

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