global data science
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2020 has been a year for the history books – unfortunately though for reasons we’d all prefer to forget! Many businesses have experienced a really tough year, but rather than seeing it as one long crisis, I prefer to view it as many different waves of mini-market changes.

To explain, factors like lockdown rules and related government guidance that have and continue to change in accordance with the severity of the Covid-19 pandemic, has led to many different market environments. It’s a constantly evolving reality and those companies who are best able to predict and adapt have been able to steal a march against more flat-footed rivals –  online retailers that now have the definite edge over bricks and mortar retailers are a perfect example. 

Looking inward

As a business owner, the crisis has been a time of doubt, and has prompted an in-depth analysis of costs and revenues. Many organisations have been forced to explore ways of creating more value with existing or fewer resources. Trimming waste from budgets, and ensuring ROI, has been essential for us and many others, and there is a strong desire to embed a data-driven approach to areas that previously might not have been considered. At Mango, conference budgets for instance have been transferred and utilised elsewhere in the business, allowing our data science teams to widen their approaches and deliver more value. 

Implementing a data-driven approach allows organisations to optimise their business effectively, which has helped them to make quicker, effective decisions. In fact, a recent report by Sisense found that 49% of respondents surveyed said analytics were more or much more important than before COVID-19. The changed circumstances has led to a requirement for more agile approaches backed up by predictive analytics. 

Whilst many organisations were in crisis mode in the early parts of the year, the new circumstances have allowed time for consideration and change. Business as usual was never going to be as effective in a swiftly transforming world, and it has created an opportunity for companies to try different things, bring forward innovation and change approaches to markets. We’ve seen technology providers embrace the opportunity by speeding up release cycles and driving their engagement with totally different markets. The ease with which my mum started using Teams for video calls was a fascinating compliment to the developers of that product and I’ve no doubt that the digital revolution for marginalised groups such as the elderly has been enhanced massively.

Looking outward

We work within a range of styles with our customers – some prefer to completely outsource, while others look to us to develop and enhance an existing team. When lockdown bit early, many companies immediately put a halt to recruitment processes, which meant that in order to execute workloads, we were able to help create data science teams for customers to deploy and maintain momentum around data-led initiatives.

Several months on and as we face renewed restrictions, I believe that this time around a lot of organisations will regard it as an opportunity to roll out new methods and move further towards harnessing the power of data science. Covid-19 has provided a stimulus to boards to be creative and flexible since all businesses have been affected. It’s an ideal opportunity for organisations to step up and adapt their business model to take advantage of areas such as innovation and data science, which might well have been on the agenda, but were probably tucked away a bit further down ‘for review’ in a few years’ time. Taking action and investing now is vital and a relative “free hit” for leadership teams.

Virtual is going to be totally dominant from now on. Those companies who have embraced it wholeheartedly will have a massive advantage, and I think we’ll see an acceleration in the adoption of online only business in pretty much every aspect of our lives. We see this as beneficial for Mango in that a transition to a digital approach to business necessitates a primarily analytic led strategy.

Looking forward

With most organisations moving towards a less office-based environment, there are opportunities to change styles of working and this will include how analytic code is held and distributed. This may well involve outsourcing of analytic development, where virtual teams can become extremely effective. In the future we are likely to see more confederacy in teams enabling organisations to extend teams and create focused high delivery groups from different resources. I think we’ll see much more team augmentation with increasingly effective outcomes. It’s exactly why now is the time to invest in data science initiatives.

Author: Matt Aldridge, CEO at Mango Solutions

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We recently launched a survey which looks into how business restrictions impact the commercial usage of R. We want to know if your company has concerns around the use of an open source language – many respondents have already replied that management is a key blocker in being able to use R at work. If you have any other reasons why you are not able to use R, or other concerns we would like to hear from you.

If you have a free minute, please complete our short survey.

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Get ready. The workplace of the future has arrived more suddenly than anyone could have imagined. When it comes to “where”, “when” and “how” we work, behaviours have shifted across all of the world’s economies.

Our partners, NineFeet Tall, share four key business planning strategies to consider when faced with the impact of the new way in which we are working, as well as the opportunities this will bring.

The Workplace of the Future – Four Essential Strategies To Get You There

Join our free webinar:

Why Data Should be at the Heart of Your Evolution



race to become data-driven
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Many companies are investing in some sort of data project – data analytics, big data, AI, machine learning data science. However, independent data projects do not make you data-driven.

The race to secure a data-driven and robust future is instead an integral part of a strategic journey, where you look to position data to empower and deliver on your business objectives.

As we return to our new normal, the importance of deeper insights has perhaps never been so critical to our decision making. Organisations are under pressure to make the right decisions to enable them to survive and transform their business model in the most appropriate way – this can only be achieved using data and analytic techniques to turn data into value in a repeatable, business-focused manner. Unfortunately, there is no simply plug and play solution to becoming data-driven. Instead, it’s about taking a data-driven approach across the business, putting the information and critical skills you have at the heart of the strategy, supported with the right technology to deliver the fundamental insights you require to not only survive but also thrive in this increasingly competitive landscape.

Here are some top tips that can help businesses succeed with their race to be data-driven:

Embrace a data-driven Future

The race to be data-driven has never been so important with so many businesses emerging from this period faster and hungrier having invested in data and analytics – this produces a new competitive landscape where the more intelligent, efficient and engaged organisations will hold a significant advantage. The need to be data-driven requires leadership alignment and a cultural shift to instigate success, and it needs to happen now. Driving champions that can help instigate data-led actionable change is of paramount importance for the commercial future.

Align Data Investment to Business Outcomes

Data investment has to align with agreed measures of success in business terms. Does the immediate strategy require cost reduction, revenue generation or creating richer experiences to regain customers? Prioritisation at this stage becomes incredibly important. What decisions will drive the most effective results and what is the potential impact of each decision to the organisation? By knowing, defining and sharing a set of goals, it becomes clearer what the company is working towards, and ensures that all stakeholders and teams share a common understanding of what data-driven success looks like.

Upskilling your data and analytic talent

Ensuring you have the right team and skills to scale your analytic initiatives is perhaps one of the most significant challenges you’ll face. What resourcing model is right for the business and how might you best establish a core, centralised best practice team of data professionals? – one community striving in one direction to empower the business and implement data-driven success. A data-driven company is one where the entire organisation leads with data, where data literacy is spread through every tier of the organisation. Defining the skills and competencies against those critical dependencies is essential across every level of your workforce.

Use data to inform any transformation

Workplaces are changing. To evolve effectively and become more agile decisions need to be driven by data. Whether these decisions involve the application of new technology and automation, further investment around digital collaboration or more innovative processes, any implementation needs to be based on actionable data.

Thriving and surviving with a data-driven data strategy is key for success in today’s competitive market, because it presents the ability to make informed decisions and transform quickly based on real insight.

Join Rich Pugh, Chief Data Scientist at Mango and Simon Adams, Change Consultant at Nine Feet Tall, as they discuss the importance of being data driven in this increasingly competitive commercial landscape and why putting data at the heart of your business transformation is imperative if you want to survive and thrive.

The focus for the webinar will be on:

  • Why are organisations racing to become “data-driven”?
  • What exactly does a data-driven organisation look like?
  • What happens if we don’t get there quickly enough?

Join this webinar


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We caught up with one of our VirtuEARL speakers and EARL regulars Jeremy Horne on what we can expect from his VirtuEARL talk and how he thinks the R community has adapted since lockdown.

You’ve presented a few times now at EARL, what makes you come back each time?

​I’ve said it for several years now – EARL has become the “must go” event of the R calendar – not only have I presented a few times, but I’ve been fortunate enough to attend every EARL since it started in 2014 and on each occasion, I’ve taken something new away to try with my clients – and indeed, the quality of the talks and use cases grows better and better each year – so I’m looking forward to some more excellent talks this year too.

How has the R community adapted since lockdown?

​Like every community, it was tough in the first few months. Events got cancelled (including my very own BrightonR user group 😞) and the interaction with other R users was limited to channels like slack – but with the realisation that we’re a long way off face-to-face meetups again, virtual user groups have been set-up and done quite well – there were some fantastic presentations at LondonR last month and we’ve finally got BrightonR off the ground again too!

Why are events like EARL and R meet ups important do you think?

​The networking – being able to talk to other like-minded R users and staying on the pulse of what they’re up to – this is the bit I miss terribly at the moment as it always gets me thinking about new things that I can do within R.

What can we expect to hear about from your EARL talk?

​I’m hoping you’ll take a few tips away on how you can improve your email marketing using R and specifically text analytics – and equally, would love to hear how you get on afterwards if you implement any of the techniques.

If you’d like to hear Jeremy’s talk and some other inspirational R based talks, then join us at VirtuEARL. The online Enterprise Applications of the R Language Conference taking place this October.

While you’re here – Please complete this short poll to help us evaluate how business restrictions impact the commercial usage of R.

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At this years’ online version of the Enterprise Applications of R Language Conference, we have four workshops fo you to join.

Tickets for half-day workshops are £90 and all profits will be donated to Data for Black Lives.

The Science (and Art) of Data Visualisation in {ggplot2} 

Hosted by Mango’s Nick Howlett and Joe Russell, you will discover the principles required to create powerful visualisations and understand how and why, they effectively and accurately communicate the stories inside data.

Using the powerful and expressive {ggplot2} package, you will learn how to apply these principles while exploring the common pitfalls to avoid when creating your own visualisations.

Text Analysis in R

Many companies have a large amount of data stored as text that is not being used effectively. In this introductory workshop, we will show how you can get started with analysing text data – from simple manipulation through to sentiment analysis. By the end of the course, attendees will have a good understanding of the techniques, as well as how to implement them in R.

Good practices for {shiny} development using {golem} – An Introduction

During this workshop, Colin will give you the keys to get started with {golem}, so that you can now start your next {shiny} application on solid ground. This workshop is designed for {shiny} developers who want to understand and master {golem} philosophy and general structure, and to learn the best practices for building {shiny} applications that will be sent to production.

A quick introduction to tidymodels – JUST ANNOUNCED

Our last workshop to be announced will be taught by RStudio’s Max Kuhn over two consecutive afternoons. This workshop will introduce the basics of fitting models with the tidyverse. A basic case study will be used to demonstrate how to create models, engineer model features and evaluates performance using resampling.

Tickets are limited for our workshop places, so make sure you don’t miss out!

Buy your tickets here.