financial fraud
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The recent Transform Finance ‘Virtual Fraud in Financial Services’ event offered some fascinating insight into the risks facing the sector and how organisations are investing in advanced technologies to detect, prevent and tackle fraud.

An important and recurring theme was the role of data analytics in meeting the challenges presented by rising levels of fraud and the increasing sophistication of fraudsters. Bringing insight and experience to life for attendees, Mango Chief Data Scientist, Rich Pugh, was joined by Sandra Peaston, Director of Research & Development at Cifas to discuss their use of data and intelligence to support fraud prevention.

Cifas is the UK’s leading fraud prevention service, managing the largest database of instances of fraudulent conduct in the country. Its members are organisations from all sectors, sharing their data across to reduce instances of fraud and financial crime.

As a data-centric organisation, Cifas wanted to develop deeper insight into emerging fraud trends, understand which were the most significant and then quickly share that information with its members for further action.

Getting ahead of the game was key, and as Sandra Peaston described, “We wanted to use our data to speed up the early-stage intelligence process so our members didn’t need to report trends to us. Unlocking the power of the data we already hold was the challenge that took us to Mango.”

Having been approached by Cifas, Mango quickly deployed a team of data scientists to establish the right technical environment. As Rich Pugh explained, “The Cifas team has amassed some incredible data assets, but with many areas of potential focus the key question was: where could we deliver quick impacts against their priorities?”

The Mango project team focused on two core areas. The first was a ‘Match’ project, built to reduce false positive rates and improve the Cifas rules engine. This was supported via the development of a probabilistic matching engine prototype, designed to improve the existing matching and reduce member friction.

The second part of the solution was an ‘Intelligence’ project. This focused on the development of a fuzzy search capability and a signal detection tool to automate the previous manual fraud detection processes to uncover hidden and emerging fraud patterns. This insight would then be used to enrich intelligence and feedback to members.

As Sandra explained to event attendees, “We needed an intelligent way of dynamically identifying an emerging fraud trend, and key to this was the speed at which this happens. By working with Mango to uncover the huge power that sits within our data to a level of granularity that we couldn’t manage before, we can help members to prioritise and make them more efficient.”

Together, Cifas and Mango have deployed a best-practice framework using intelligence tools that demonstrably reveal hidden patterns that human beings would struggle to detect. Looking ahead, the teams will continue to innovate and use data science to unlock insight relating to fraud and e-crime, refining algorithms over time to become even more effective in countering criminal activity and finding ways to stay ahead of malicious actors.

world environment day
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First held back in 1974, World Environment Day has become a powerful way for the United Nations to engage with “governments, businesses and citizens in an effort to address pressing environmental issues.” This year, a key theme is #GenerationRestoration and also sees the launch of the UN Decade on Ecosystem Restoration: a global rallying cry for everyone to do their part in healing the planet.

Back in the 70s, the prospect of a looming global environmental crisis was, for most people, simply not among the major issues of the day. Experts and activists aside, few could have imagined the pace at which events would develop and how urgent the need for action would become.

In a similar way, half a century ago, the idea that technology could have a positive impact on protecting the planet was much closer to science fiction than reality. Today, however, the world looks to digital innovation as one of the main strategies to combat climate change, with data science among the industries now playing a vital role on both a macro and micro scale.

Globally, data scientists blend human expertise with technology to assess data and review the impact of problems causing climate change. This insight informs government policy, which then filters across the economy and society to deliver meaningful impact. In the UK, for example, it is now national policy to cut carbon emissions by 78% by 2035, and data science will play a key ongoing role in the further development of policies in the years ahead.

On a day-to-day basis, businesses everywhere will need to make a major contribution if this target is to be reached. The sustainability of every organisation depends on addressing the impact of its operations across the supply chain. Everything from water consumption, pollution and plastic reduction, to carbon emissions, waste and recycling, is part of the equation – and data science modelling is increasingly being used by businesses to assess the likely impact of their actions and the quality of decision-making.

In recent years, the Mango team has worked on sustainability projects to monitor and measure world poverty, reduce water waste and to understand the proportion of electricity generated using low-carbon sources. We remain committed to broadening the availability of data science expertise and technology to make a difference to ensure data science empowers #GenerationRestoration.

Delivery by Mango

Protecting and preserving biodiversity

Mango built and mentored several data science production projects across the ONS including the United Nations funded Sustainability Development Goals, a system to monitor and measure world poverty based on 19 sustainable goals, from ending hunger and poverty to achieving sustainable energy and gender equality to protecting and preserving biodiversity. Data science is a powerful tool which can be used to inform businesses and improve their water consumption as well as having world-wide applications in reaching the UN targets of providing clean, accessible water to all.

Reducing water waste

Mango helped i20 realise their data capabilities but develop a solution that greatly improved the performance of their smart network solutions, leading them into the world of AI and data analytics. This has enabled water companies to shift to conditional based maintenance and reduce the number of water leaks. One client reduced leakage by 15% in the north of their city within 2 weeks of using the solution.

Enabling the adoption of renewable energy

Britain’s first all-digital, renewable energy supplier Pure Planet choose to work with Mango to harness their data to drive data-driven pricing solutions and help to drive service efficiency. Mango added value in terms of broadening the scope and skills of the data science team and in helping them to establish common frameworks and processes to make data science easier with repeatable and scalable models.

Assessing the proportion of low carbon sources of energy

Mango were involved in a project that assessed the proportion of electricity generated using low-carbon sources including solar, wind, hydro or nuclear. All the data and deployment workflows were developed to schedule daily updates of carbon intensity data and re-deploying the app when the data was pushed to main branch.

Data science is used widely in business as an integral part of a businesses to positively impact change in a number of ways https://earth.org/data_visualization/ai-can-it-help-achieve-environmental-sustainable/

Data scientists, looking to add their support to the wider effort to protect the environment, can get more information from the Open Sustainable Technology website which provides a list of all sustainable, open, and actively maintained technology projects worldwide and details of how to get involved.

Data Science Competency for a post-COVID Future
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Written by Rich Pugh, Chief Data Scientist, Mango Solutions (an Ascent company)

The COVID-19 pandemic disrupted supply chains and markets and brought economies around the globe to a standstill.

Overnight, governments, public sector agencies, healthcare providers and businesses needed access to timely and accurate data like never before. As a result, demand for data analytics skyrocketed as organisations strived to navigate an uncertain future.

We recently surveyed data scientists working in a variety of UK industry sectors, asking them about:

  • how their organisation’s reliance on data changed during the pandemic
  • how their teams are having to re-align their skills sets to deliver the intelligence that’s needed; and
  • top trends on the horizon as organisations pursue a data-driven post-COVID recovery.

What they told us offers some interesting insights into the fast-evolving world of data science.

Decision intelligence gets real

Our findings highlight how the sudden disruption of the COVID-19 pandemic brought the importance of data analytics sharply into focus for business leaders and decision makers across the enterprise.

Almost two-thirds (65%) of those surveyed said that demand for data analytics rose across their organisation. The top request areas for problem-solving and enabling informed strategic decisions included:

  • Immediate crisis response (51%) – risk modelling, digital scaling and strategy as organisations looked to make near-term decisions to address key operational challenges.
  • Informing financial/cost-efficiency decisions (33%).
  • Logistics/supply chain (26%).

As reliance on data became mission-critical, data scientists in some industry sectors were at the nerve centre of COVID-19 response efforts as organisations looked to solve real-life problems fast.

Data scientists are adapting their skills sets quickly

As organisations beef up their data strategy to better prepare for future disruptive events and thrive and survive in the new normal, data scientists are having to adjust to new ways of working and adapt their skills sets fast. Indeed, 49% of data scientists say their organisation is now investing in building their internal capabilities through learning and development programmes, with 38% actively recruiting to fill gaps.

Now part and parcel of the enterprise decision-making team, data scientists confirm they are having to hone their business and communication skills to ensure they are able to support business leaders across the organisation better. Indeed, an impressive 34% identified working more effectively with business stakeholders was now a top priority. With data now being used more broadly across the organisation, one-third (33%) of the data scientists confirmed that they plan to boost their own communication and business skills so they can interact more cohesively with business leaders – and collectively identify the right problems to solve for their organisation.

Top data trends for 2021

As organisations continue to push ahead with operationalising their data and analytics infrastructures to handle complex business realities, data scientists are scaling up their deployment of machine learning algorithms to automate their analytical models.

According to our poll, upskilling their machine learning (ML) skills was identified as the #1 priority for 45% of data scientists as they look to accelerate their AI and ML computations and workloads and better align decisions throughout the organisation.

Similarly, big data analytical technologies (such as Spark, Storm and Fink) was the top priority for 39% of UK data science teams, as was getting to grips with deep learning (39%) as analytics teams look to jointly leverage data and analytics ecosystems to deliver coherent stacks that facilitate the rapid contextualisation decision-makers need.

Finally, with more people across the organisation becoming increasingly dependent on data-driven decision making, data scientists are having to find new ways to present data in ways that business teams will understand.

In a bid to democratise data and support faster decision making on the front line, they’re working on increasing their skills in areas like data visualisation (27%) and modelling (23%) so they can tease out trends, opportunities and risks in an easily digestible way that makes it easy for decision-makers to consume and engage.

New opportunities on the horizon

In a post-COVID world, organisations are looking to tap into an increasing number of data sources for the critical insights they’ll need to tackle emerging challenges. In response, data scientists are having to extract and analyse data quickly – even in real-time – and in the right way. Integrating data-driven insights into the decision-making process.

In response, data scientists are having to upgrade their technical and business skills as organisations look for efficient and innovative ways to use the big data at their disposal.

In summary, the research highlights both how important it is to align central data communities in order to boost and demonstrate value across the business, while ensuring that investment in L&D programmes is fully aligned with developing trends and business objectives.

 

 

maths & statistics awareness month
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April marks Mathematics and Statistics awareness month #MathStatMonth in the USA, with the aim of increasing the level of interest in these subjects. Working in an increasingly data-driven world, the ability to harness meaningful insights from data is an essential business and requires specialised data science expertise.

Data science is the proactive use of data and advanced analytics to drive better decision making. This ‘proactive’ use of data is what distinguishes data science from traditional ‘statistical analysis’ and needs to be an active part of an organisation in search of insight, better decision making or improvement.

Data science as a career choice for maths, statistics, and science graduates

Many graduates from maths, statistics and science backgrounds are increasingly attracted by a career in data science. Our current graduate placement Student, Elizabeth tells us more about her early interest in data science and why it presents a natural career path for those interested in mathematics and statistics. “Data science combines the skills and applications of mathematics and statistics with the use of big data and innovating technology to solve a variety of problems. I’m particularly interested in providing solutions to real-world problems and communicating these results at a high level within a business”, says Elizabeth.

“Throughout my placement I have seen the application of using mathematics and statistics within data science projects in performing exploratory data analysis to creating statistical models. My personal interest is in different types of statistical models, and I am due to study Time Series and Bayesian statistics in the final year of my degree”.

Elizabeth has benefited from seeing how mathematics and statistics have been used to model complex situations and improve business decisions from the optimum timing of routine maintenance, saving unnecessary reactivity and costs to creating descriptive, diagnostic and predictive insights which delivered great value and significant return on investment during her time at Mango.

Growing demand for data science

With the demand for Data Scientists still on the rise into 2021, the pandemic has created an even more urgent need for rapid decision making, informed and supported by constantly changing data sets, backed by effective visualization (highlighted by the World Economic Forum (WEF) in July).

Rich Pugh, Mango’s Chief Data Scientist summarises, “Leaders increasingly understand the potential of using data to create smarter, leaner, more engaging organisations. As such, we are still seeing growing demand for “data scientists” who are able to turn that data into acumen in a repeatable and scalable way. As a multi-disciplinary practice, “data science” relies on the combination of “advanced analytics” and “computer science” skill – this, combined with an ability to creatively explore challenges that can be solved, is at the core of realising the value promised by data science”.

“At it’s core, data science relies on mathematics and statistical rigour to provide robust algorithms that can be relied upon to solve often-complex challenges. As interest in data science continues to grow, the work at the Royal Statistical Society becomes increasingly important – to drive the discussion around statistical governance, and the correct and ethical application of statistical routines”, Rich concludes.

demand forecasting this easter
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Using data to accurately forecast demand for chocolate this Easter

Easter is a significant holiday for many businesses especially within the UK. The holiday period brings an increase to food and drink sales, with Easter being the second most popular period of the year for chocolate consumption. Many Britons book holiday trips in this period as well, making it an important time for the leisure industry.

Data science enables businesses to effectively plan for this busy period. Analysis of historical sales data can be used to predict future demand, allowing businesses to accurately plan stock levels; real-time analysis provides visibility of the state of a product, enabling businesses to quickly resolve issues regarding the manufacturing of products like chocolate bunnies.

Accurate forecasting to match demand

Demand forecasting is a commonly used approach which allows businesses to effectively predict future sales, plan and schedule production, improve budget planning, and develop efficient pricing strategies. Predictive analysis is used to understand and forecast demand over time, helping businesses make well-informed decisions.

Adapting in line with the coronavirus pandemic

The COVID-19 pandemic has brought great challenges within businesses. Easter brings challenges itself with the date of the holiday moving each year, however in 2020, businesses were simply not prepared for the impact of the pandemic. Easter egg sales fell by £36 million with many retailers having to sell lots of eggs at discounted prices. Some retailers were also unprepared for the boom in online sales and were not able to meet demand. On the upside, many businesses are better prepared for this year’s Easter period, with many focussing on online operations. Through demand forecasting techniques and last year’s data, businesses have been able to better prepare for this year’s demand. Many, for example Hotel Chocolat, are offering a limited range of Easter eggs this year.

As well as benefitting the retail and leisure industries, demand forecasting is used by other organisations over Easter. The NHS use forecasting techniques to predict demand and capacity for their services. This has been particularly important during the pandemic. In the January peak, NHS hospitals were caring for over 34,000 COVID-19 patients in England, approximately 80% higher than the first peak in 2020. Demand forecasting and mathematical models are being used to predict hospital bed demands frequently, tailored to specific hospitals, to help the NHS and government plan for future holiday periods such as Easter.

Demand forecasting is an effective approach that is being used by many businesses to plan for this year’s Easter holiday. Data-driven businesses can make well-informed decisions for the future, and as a result many will be better prepared this Easter.

Can we help with any aspect of your demand forecasting? Read our case study to find out how we have helped other companies with this.

world water day
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As we celebrate World Water Day, we consider the lack of access to safe and affordable water – a dangerous reality for billions across the world. It has a damaging effect on not only the health of billions of people but also on many aspects of their lives. With climate change comes droughts, floods and scarcity of water, bringing with it social and economic devastation. For example, clean water and sanitation is an important factor in reaching equity amongst gender.

By 2030, the UN aims to achieve universal and equitable access to safe and affordable drinking water and adequate sanitation and hygiene for all. To reach these targets, it is vital that businesses create and achieve their own targets for water consumption to help make a positive change. Unfortunately, many of these targets are not being met.

Using the power of data to make a positive change

In data-driven world, data science allows us to harness the power of data to make positive change. It can be used in several ways to improve water quality and water consumption around the world:

  • The innovation of machine learning can be used to improve the way in which water is collected and transported to reduce CO2 emissions. Moreover, it can be used to improve the treatment and utilization of water.
  • Real-time monitoring gives communities the power to ensure water is safe to drink while saving on resources.
  • Data analysis allows predictions to be made about the quality of water given a number of factors like weather and pollution. This allows for better planning when it comes to supplying clean drinking water to those in need.
  • Identification of water supply issues can be significant in preventing the spread of diseases through water supplies.

Mango realises the importance of using data to help other businesses bring positive change to the world. Data science can be used to inform businesses on their water targets and make steps towards reaching them. As well as harnessing data, it is equally important to involve stakeholders in decision making to identify, understand and overcome water challenges.

Reducing water waste

Water waste is a problem that many businesses face, with more than 25% of water wasted being due to leaks. This can be significantly reduced through the use of data science and in turn help businesses reduce their water consumption.

One company, i20, provides smart network solutions designed to help water companies reduce their leaks and bursts, energy use and CO2 emissions. The company recognised that it was collecting a large amount of data but were not harnessing it. Mango were able to not only help i20 realise their data capabilities but develop a solution that greatly improved the performance of their smart network solutions, leading them into the world of AI and data analytics. This has enabled water companies to shift to conditional based maintenance and reduce the number of water leaks. One client reduced leakage by 15% in the north of their city within 2 weeks of using the solution.

Data science is a powerful tool which can be used to inform businesses and improve their water consumption as well as having world-wide applications in reaching the UN targets of providing clean, accessible water to all.

Find out more about how Mango has helped i2o harness their data.

 

Global Recycling Day
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It’s Global Recycling Day today and a day to raise awareness of the importance of recycling and how crucial and lasting change can help preserve the future of our planet. Recognised in the UN’s Sustainable Development Goals 2030, we are already seeing many individuals, governments and organisations taking direct action to support the global green agenda.

Founded by the Global Recycling Foundation, this year’s theme is #recyclingheros and recognises people, places and organisations that inspire us – demonstrating positive action.

From plastic pledges and recycling,  to waste targets, businesses are positively impacting the environment, and data science is being used positively to reduce environmental impact and financial costs – aligned to their corporate responsibility. There are many examples of data analytics applications that can play just a small part in decelerating the process of climate change – the more focus that organisations place on this, the brighter the outlook for our planet. We decided to take a look at some of the positive use cases.

Food waste

Think about the waste problem in supermarket fresh food sales. Many businesses are using data science to help the UK meet its target of eliminating food waste to landfill by 2030. Analytics of weather patterns can help supermarkets ensure they have the right amount of seasonal produce to meet demand for a particular weather period without wastage; and enhanced analytics of customer weekly shopping habits would mean the store could ensure it has met demand without having surplus fresh food.

Gousto, a British meal kit retailer, implemented forecasting algorithms in an effort to reduce their food waste. They were able to predict demand and analyse seasonal trends to better manage their fresh food stock. Forecast modelling allowed the business to not only predict with a high degree of confidence the number of orders they would receive in future weeks, but also predict the performance of existing and new recipes.

Plastic waste

Plastic waste posing a considerable threat to our planet, with 8 million metric tons of plastic being added annually to the world’s oceans. That is why many businesses in the UK have come together to work towards having all plastic packaging recyclable, reusable or compostable by 2025. One such company is Tesco who are rolling out collection points for soft plastic packaging in their stores. Tesco’s efforts should help the public in their efforts to recycle as well their own.

Outside of the UK, many companies are also reducing their plastic waste and increasing their recycling, with many also helping the public do so. The Gringgo Indonesia Foundation, with the help of Google, have used AI and machine learning to create an app to help better classify waste items. It can be used by businesses and the public to help improve their recycling. With the use of data science, within a year of launching the app, recycling rates were increased by 35% in their first pilot village.

Space junk

Space junk poses a danger to astronauts in orbit, the world’s network of communication and weather satellites. Luckily, data science is here to help. NASA have been developing technology to remove space junk. Using machine learning algorithms, NASA are working towards improving the detection of space junk for removal.

Clinical waste

Since the start of the COVID-19 pandemic, there has been an increase in single use plastics and clinical waste. With only 15% of clinical waste being hazardous, there is a massive opportunity to reduce and properly manage clinical waste using data science. From reducing the number of unnecessary hospital appointments to the size of some healthcare equipment, a positive change can be made.

Reducing waste and recycling is vital for the future of our world. Data science provides many tools for creating and implementing solutions, and with data-driven businesses striving to reduce their waste, the future looks bright.

To discuss any use cases to align your recycling goals, contact us.

Author: Elizabeth Brown, Professional Placement Student at Mango

British Science Week
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As a data science consultancy, we’d like to celebrate British Science Week #BSW21 and the innovation in science, technology, maths and engineering, as well as the diversity of these roles. Many of our graduate consultants join Mango from a Maths and Statistics background, but also equally from a science background where many of the data and analytic approaches, including R are introduced.

Can data science be classified as a Science? We asked our Consultants, and the answer was a resounding ‘yes’, as our Graduate Data Scientist, Elizabeth Brown explains. “In my opinion, Data Science is a Science. The goal of Science is to gain a better understanding of the world around us, to explain why things happen or to describe the relationship between concepts. A big part of science is taking this understanding and applying it to real world situations, whether that be making advancements in medicine as we have witnessed with the vaccine development, or a modern way of introducing scientific methods to automate processes and make more intelligent decisions – ‘innovating for the future’, just as the theme for British Science Week this year. Like a science, we make observations, come up with hypotheses and through experimentation, test our hypotheses”.

Rich Pugh, Mango’s Chief Data Scientist agrees, “When done right, data science should be based on, and resemble, the scientific method. We formulate a “hypothesis” (although the structure of this can vary across application), then we use data to test that hypothesis”.

“Data is everywhere and being able to use it effectively to improve our understanding of the world is very exciting – expanding data-driven decision making, scientific discovery and  automation”, explains Elizabeth.

The growing capabilities of AI and machine learning are paving the way for real world solutions such as self-driving cars, much needed fraud prevention and addressing climate change. Fundamentally, data science isn’t just solving business problems, as a career it can support initiatives to create a healthier, greener and kinder world.

If you are interested in a data science career with Mango, click here to find out more.

International Women's Day
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On International Women’s Day, we’d like to celebrate the achievement of our own talent, raise awareness against bias and take positive action for equality. At Mango we believe in creating inclusive and diverse workplaces. A workplace that offers challenges and an active learning environment.

Kasia Kulma, one of Mango’s Senior Data Scientist’s, reinforces the many benefits that diversity brings to the workplace, her opinions are shared and published in Diversity Q, FE News and Education Technology.

According to Kasia, “parity in tech companies can be hugely beneficial to the industry as a whole be it in respect to gender, ethnicity, age, sexual orientation or other. Some of them are rather pragmatic, for example, by embracing a more diverse talent pool we can address talent shortages and progress to closing the talent supply/demand gap. More fundamentally, though, diversity brings a variety of perspectives which has a knock-on effect in increased creativity and thus faster problem solving and improved products. The company culture can, benefit significantly too. By helping employees feel included, no matter their background or gender, it can break down barriers and reduce the fear of being rejected”.

“This is a great way to empower your employees”, says Kasia and “harness their ideas and thoughts and attract talent”.

Closing the diversity gap

When you increase the investment in training for women to fill the corporate need, we believe it goes a long way to the overall goal of closing the gap once and for all.

According to Kasia, “the tech industry is very dynamic and it could offer the most creative and stimulating of environments. It gives you the flexibility to work cross-industry or to specialise in one area if you like. You could work on the bleeding edge of innovation and devote your time and career to something you really care about.”

“The most important advice I could give to an aspiring women technologist would be to look for employers that offer a supportive environment and embrace diversity – this way you’ll be more likely to spread your wings and learn. There are more and more tech companies that understand the importance and value that the workplace diversity brings, so join them… and enjoy the ride!”

Happy International Women’s Day!

If you’re interested in a career in data science,  you can find out more about Mango and check out our current vacancies.

 

NHS-R Community
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The NHS is one of the UK’s most valued institutions and serves as the healthcare infrastructure for millions of people. Mango has had the pleasure of supporting their internal NHS-R community over the last few years, supporting the initiative from its inception and sharing our knowledge and expertise at their events as they seek to promote the wider usage and adoption of R and develop best practice solutions to NHS problems.

According to a recent survey by Udemy, 62% of organisations are focusing on closing skills gaps, essential to keeping teams competitive, up to date and armed with the relevant skills to adapt to future challenges.  For many institutions, an important first step is connecting their analytics teams and data professionals to encourage the collaboration and sharing of knowledge. With ‘Data literacy’ fast becoming the new computer literacy, workforces with strong data skills are fast realising the strength and value of such skills across the whole organisation.

As the UK’s largest employer, comprising 207 clinical commissioning groups, 135 acute non-specialist trusts and 17 acute specialist trusts in England alone, the NHS faces a particularly daunting task when it comes to connecting their data professionals, a vast group which includes clinicians as well as performance, information and health analysts.

The NHS-R community was the brainchild of Professor Mohammed Mohammed, Principal Consultant (Strategy Unit), Professor of Healthcare, Quality & Effectiveness at the University of Bradford. He argues,  “I’m pretty sure there is enough brain power in NHS to tackle any analytical challenge, but what we have to do is harness that power, promoting R as the incredible tool that it is, and one that can enable the growing NHS analytics community to work collaboratively, rather than in silos”.

Three years in and the NHS-R Community has begun to address that issue, bringing together once disparate groups and individuals to create a community, sharing insights, use cases, best practices and approaches, designed to create better outputs across the NHS with a key aim of improving patient outcomes.  Having delivered workshops at previous NHS-R conferences, Mango consultants were pleased to support the most recent virtual conference with two workshops – An Introduction to the Tidyverse and Text Analysis in R. These courses proved to be a popular choice with the conference attendees, attracting feedback such as “The workshop has developed my confidence for using R in advanced analysis” and “An easy to follow and clear introduction to the topic.”

Liz Mathews, Mango’s Head of Community, has worked with Professor Mohammed from the beginning, sharing information and learnings from our own R community work and experience.  Professor Mohammed commented:

“The NHS-R community has, from its very first conference, enjoyed support from Mango who have a wealth of experience in using R for government sector work and great insight in how to develop and support R based communities. Mango hosts the annual R in Industry conference (EARL) to which NHS-R Community members are invited and from which we have learned so much. We see Mango as a friend and a champion for the NHS-R Community.”