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This is a profile from the 2021 version of the DataIQ 100.

The latest list is available here.

Sid Shah, head of analytics and insight - data intelligence, Condé Nast

Sid Shah, head of analytics and insight - data intelligence, Condé Nast

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

 

Data and analytics are important pillars supporting Condé Nast’s corporate vision and growth initiatives. Condé Nast is a global media company that produces some of the world’s leading print, digital, video and social brands, including Vogue, GQ, The New Yorker, Vanity Fair, Wired, Architectural Digest (AD), Condé Nast Traveler and La Cucina Italiana, among others.

 

The data and analytics capabilities support business groups focused on increasing audience engagement, advertising and consumer revenue business. We use data to identify opportunities across all titles with the help of initiatives designed to understand consumer behaviour and purchasing trends in a better way. Data is at the core of digital transformation with data products, technologies and processes unlocking intelligence and improving customer experience.

 

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

 

2020 was indeed a “different” year to anything we have seen. It tested many processes and systems and also helped us to gain a different perspective on collaboration.

 

The pandemic reinforced the importance and accelerated areas that are of strategic importance for the business. We were going through digital transformation well before the pandemic struck, the pandemic prioritised activities that were critical and are seen as an enabler for growth. From our data perspective, this meant we continued rolling out and consolidating our analytics, business information and customer data platforms.


We also saw a surge in demand from the business looking to understand the changing audience behaviour during the pandemic and impact on KPIs. With huge audience base across Europe, Asia, US and Latin America, there was a need to measure the changing customer interaction and purchasing behaviour during lockdown enforcement and easing across multiple countries.

 

We partnered with a number of internal teams and external partners to create a cohesive narrative that helped the business understand the “what?” and “why?”. We also put additional effort on data quality across all new processes and practices, which helped us deliver consistent data narrative.

 

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

 

With some level of normality in Asian markets, I expect the situation in the UK and other parts of the world will change for better soon. From a data and analytics point of view, I expect strong data adoption and engagement to continue within the business in 2021. With more valuable insights available to our stakeholders, I expect an increase in personalisation and optimisation activities. This will also help accelerate data programmes focused on standardisation and automation. We will also keep track of upcoming browser changes and how they impact measurement and targeting

 

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

 

Yes, I am keen to decipher how data could be used for finding solutions about the social injustice and discrimination issues present in today’s world. As an organisation, we always focus on identifying ways to use data for the betterment of society and to change perceptions. In the late summer of 2020, we conducted “data for good” hackathon, where my group and I created gamified audience search to lend support to initiatives fighting social injustice

 

What has been your path to power?

 

Following my degree in Physics and Programming in e-commerce tech, my first role within the data domain was in the finance team at a music publishing firm, where I was fortunate to learn different analysis and financial modelling techniques.

 

My subsequent roles were both consulting and in-house, where I had an opportunity to work with some of UK’s biggest banks, insurance, retail and media companies. During this period, I also started my leadership journey, where, along with hands-on duties, I started spending more time in management and planning.

 

I led teams that were embedded in business disciplines (and clients) in product and marketing space. I gained experience in developing a digital strategy, where data is used to improve marketing performance and conversions. I played an important role in building and growing a profitable data function and also started mentoring and coaching students and young practitioners, which helped me to develop emotional resilience and manage talent in my career.

 

I have been in my current role for four years, leading a global analytics function based in London, US and India to deliver insights, recommendation and data products.

 

What is the proudest achievement of your career to date?

 

In my current role, I had an opportunity to build a new global analytics function within an established business. We had to go through a data journey. This journey resulted in an improvement in the company’s efficiency across all parts of the business and also acted as an enabler to build new revenue-generating products. This involved setting up new processes and capabilities that are agile, scalable and respect existing practices, critical for the global business.

 

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

 

One of my goals in data is to create more data awareness among audiences and the general public by explaining what and how data is tracked and stored, and what is anonymised and personal data. Audiences should be aware of the choices they have and the impact their choices will have on the quality of the products and services they receive. This transparency will help the industry in the long term and eliminate the notion of black-box decision making.

 

How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?

 

At Condé Nast, data and analytics are closely aligned with the business and highly engaged stakeholders. We have brought the global business together around common goals, while focusing on customer needs. The democratisation of data and consistent narrative have helped build common understanding around performance and customer behaviour.

 

As an industry, a lot has changed during the pandemic. There is an increased data awareness among stakeholders with a strong appetite to understand changing audience behaviour.

 

Data and analytics teams should use this opportunity to offer relevant information that can support decision making. The key is to get data strategy right, it should align with business goals and priorities, while the data roadmap must consider various business initiatives and priorities.

 

In a dynamic trading environment, it is vital for the data and analytics team to be “agile” and your processes and structures should be able to support the business in responding to changing customer needs.

 

Lastly, ensure talent is part of your data strategy; people are key for success and it is vital to have talent with the right skills and attitude.

 

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

 

The crucial first steps are having a data-first mindset along with robust data literacy and training programmes. You then need to focus on capabilities and processes to ensure data and insights are available across the organisation. There should be an additional effort to maintain data quality as that builds trust and helps to improve engagement.

 

I also think there should be more collaboration between business and data teams in model building. Analytics teams should explain modelling choices made and develop common understanding around algorithm outputs.

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