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Craig Suckling, EMEA analytics platform strategy lead, Amazon Web Services

Craig Suckling, EMEA analytics platform strategy lead, Amazon Web Services

How is your organisation using data and analytics to support the corporate vision and purpose?

 

AWS is customer-obsessed and we focus on understanding our customers and innovating on their behalf. This requires a high focus on data to gain insight on our customers’ needs and to proactively infer where we can create future value for them.

 

Data charts out the iterative and continuous evolution of our strategy and vision across the business, and we use tenets as a mechanism to embed strategic purpose into everything we do. The signals derived in our data constantly inform the evolution of our tenets and continuously shape and improve our corporate and customer vision. Some 90% of what we build is driven by what customers tell us matters, and the other 10% are things we hear from customers where they may not articulate exactly what they want, but we try to read between the lines and invent on their behalf.

 

2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?

 

The Covid-19 pandemic forced a lot of organisations to be more agile in decision-making, innovate on their feet, and maintain stability in operations - all in the face of remote working, spikey demand and a fluctuating market. As a result, many organisations turned to the cloud to quickly build propositions that differentiate their business and gain greater insight and intelligence to pivot their business proactively in an unpredictable economy.

 

We helped customers to quickly access a broad set of data that enables them to make faster and better decisions, share insights quickly, and apply intelligence across siloed business lines. We also focused on lowering the barrier to machine learning across organisations, enabling automation and the ability to optimise business actions, for example, scenario planning, supply chain optimisation or customer personalisation.

 

Importantly, we are continuing to work with our customers to increase data literacy and integrate data with business innovation across the enterprise to solve fast changing commercial priorities and to inform and shape business strategies that remain in flux.

 

Looking forward to 2021, what are your expectations for data and analytics within your organisation?

 

We are seeing a data explosion. Today, we generate more data in one hour than was created during all of 2000 and more data will be created in the next three years than was created over the past 30.

 

In 2020, whether you were a data scientist or not, we all got a glimpse of this growing data curve as scientific researchers, pharmaceutical companies, governments, and healthcare institutes turned every resource toward developing vaccines, novel treatments, and other means to help the world stay healthy during the pandemic. All of these efforts required generating and processing vast amounts of data.

 

Whether in healthcare or other applications, the only realistic way to handle all the information we are seeing is to use ingestion and aggregation tools, married to ML models that can help make sense of it. It’s no wonder then that in 2020 ML went mainstream. ML has historically been a computationally-heavy workload that’s incapable of running anywhere but on the most powerful hardware. However, with advancements in software and silicon, this is changing. Using a combination of AWS technologies, we’ll see hardware and software working together at the edge to have a bigger impact than ever for customers in 2021.

 

Is data for good part of your personal or business agenda for 2021? If so, what form will it take?

 

Yes, AWS is collaborating with a network of institutions worldwide on data for social good in the fields of health, community and social innovation, building intelligence and solutions that are publicly available for use.

 

As an example, as part of our response to Covid-19, we worked with the National Health Institute’s National Centre for Biotechnology Information to create a Coronavirus Genome Sequence Dataset to support Covid-19 research. The dataset provides researchers with quick and easy access to coronavirus sequence data at no cost for use in their research. We also recently announced our ambition to help 29 million people around the world grow their tech skills with free cloud computing training by 2025, including Amazon’s Machine Learning University, to help alleviate the skills gap which has grown as a result of the pandemic.

 

What has been your path to power?

 

I fell in love with code at university while studying computer science. I had been a graphic designer before university, and when I learned to code, it became a new way for me to manifest my creativity. After graduating, I cut my data teeth as a consultant, working on some of the largest enterprise analytics deployments around the globe at that time.

 

After several years of large programme delivery, I moved back to my home country, Zambia, where I got a taste for entrepreneurship by founding a digital marketing start-up which used ML to personalise the customer experience.

 

I broadened my strategic thinking skills leading an analytics strategy consulting practice in the UK before going on to be head of data for IAG loyalty, where I used data and ML to create unique engagement occasions for 100 million customers across 16 airlines and 1,000 partner brands.

 

This variety of experience gave me the foundation required for my current role at AWS, where I am the EMEA regional lead for analytics platform strategy. In this role, I work closely with our customers from the youngest of start-ups to FTSE 100 enterprises to help them to reinvent and differentiate their businesses with data in a fast-changing world.

 

What is the proudest achievement of your career to date?

 

In my current role, I am incredibly proud to get the chance to interact and innovate with a wide variety of businesses, from start-ups to multinational corporations across Europe, the Middle East and Africa, and help them to apply data, analytics and AI and ML to challenge and transform their industries, economies and societies.

 

I get the chance to work with so many passionate and talented customers who are focused on improving our world with data, and it is a privilege to be able to build with them and see the tangible difference they are making.

 

Tell us about a career goal or a purpose for your organisation that you are pursuing?

 

My goal is to help companies to think big and to innovate boldly with data so they can reimagine the impact and opportunities their businesses can have and create a positive shift for our broader economy and society toward a more prosperous, fairer and sustainable place to exist.

 

Intelligent data automation, paired with human ingenuity, is revolutionising how we work, live and interact and the pace of this transformation is only going to move faster. The more we can create opportunities for organisations to build new value with data faster, the more positive the outcomes we will see for all.

 

What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?

 

Building a sustainable data culture requires a combination of top-down and bottom-up change strategies. From the top, strong leadership needs to set big audacious goals for data in the business and ensure that teams don’t get paralysed with analysis before they begin. They also need to focus on solving their most compelling business challenges with data by starting small and scaling fast.

 

From the bottom, start by creating small, cross functional teams that bridge technology and the business and who will act as the evangelists for a new data-first culture. Include the data sceptics and focus on delivering value quickly for those first compelling use cases. The process of delivery not only proves value but, importantly, creates experiential learning for both the business and technology teams for how to work effectively together with data to deliver business outcomes. This ignites the pilot light to scale broader cultural change incrementally, business use case by use case.

 

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