Papinder Dosanjh, head of data science and machine learning, ASOS

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

ASOS’ mission is to become the world’s number-one online retailer for fashion-loving 20-somethings. As a global online-only retailer, we have a huge amount of data that we can use to drive improvements in how we interact with our customers across our platform, and the experience which we offer them. We achieve this through the application of data science and experimentation. We’re also starting to embed these tools to help decision-making in other parts of the business, whether that’s in retail or in our supply chain, to help us achieve our mission and our purpose.

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

As the world changed, the lives of our customers, employees and suppliers did too. We had to adapt quickly, reviewing all of our initiatives to ensure we could support the business in data-driven decision-making as we adapted to the rapidly changing consumer trends. We increased our focus on time-series forecasting, experimenting with new machine learning frameworks to diagnose and predict changes in demand. We also used our research in experimentation and our applied experimentation frameworks to inform scalable and robust design and measurement approaches.

As expected, we had to adjust and introduce a new way of working, supporting our data teams to fully transition to remote working and successfully onboard new joiners. We also embedded cross-functional working so that we were able to deliver timely and integrated solutions. We definitely learnt a lot, but virtual team activities were a highlight of the year and helped us to stay connected.

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

My expectations are positive, despite the ongoing challenges we all face. We’ll continue to invest and scale our data science and machine learning teams, supporting the business’ global growth and transformation initiatives with data-driven products and capabilities. We will also continue to focus on implementing intelligent automation into our business processes to help drive business efficiency.

During 2021, our data initiatives will continue to support our business strategy and ASOS’ vision, and we’ll continue weaving data into the fabric of the company. We’re planning to enable this by improving data literacy across the organisation, ensuring that we’re using data to help us make as many decisions as possible.

I’m also looking forward to welcoming new talent to ASOS as it’s a great place to develop your skills in data science using the latest technologies from both Microsoft and the open-source ecosystems. We’ll also continue our academic partnerships with UCL and Oxford-Imperial College to help us stay at the cutting edge of AI research and innovation.

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

It is definitely part of our agenda. ASOS has fantastic data assets and is a great place for talented people to learn, share and collaborate with others across the industry. Previously, we provided a hands-on virtual machine learning training session led by our senior scientist and engineer, which 300 people attended. We’ve also provided coaching through STEM initiatives, as part of our diversity and inclusion initiatives. We have a role to play and will always take opportunities to share our skills for good.

What has been your path to power?

I started my career at a start-up specialising in geo-location solutions for media, retail and telecoms clients, before joining leaders in customer science dunnhumby. During my time there, I helped high-profile FMCG companies use shopper data to build relevant category, trading and shopper marketing strategies, and as senior product manager I was responsible for developing a personalisation capability for a major supermarket across its e-commerce, loyalty and CRM functions.

I then decided to move on to Accenture to build experience of different industry verticals. My role covered global digital transformation initiatives, including delivery of cloud-based big data platforms and digital messaging capabilities. Transformation was also a theme at my next job in business strategy at TUI, where my focus was on defining the global “one” analytics strategy for the executive board and championing the creation of an analytics centre of excellence.

Now at ASOS, I’m responsible for executing the business and technology transformation behind our data and AI strategy. We’re working to embed data science and machine learning across all areas of our customer experience, and also to support the optimisation of back-end functions through data, alongside our in-house data scientists, big data, and software engineering teams.

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

My team aims to leverage data to support ASOS in becoming the world’s number-one online shopping destination. My goal is to ensure that I support this purpose by ensuring that “data is pervasively woven into the fabric of ASOS”, so we can personalise the experience for each customer and drive better decisions across the business.

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

Developing a data culture is a fundamental part of any data strategy. As a data team, you need to lead by example by amplifying the successes that point to areas of value. This helps to build advocacy and sponsorship, securing investment for formalised data skills and focused literacy programmes. There needs to be a clear ROI benefit.