We worked with the UK’s independent advertising regulator to shape their next phase of its investment and digital evolution over the next five years.

Faculty’s strategy is the backbone of the ASA’s latest Data Science Plan, which include developing and deploy new capabilities in AI and machine learning that will set new standards in the regulation of online advertising.

Customer

The Advertising Standards Authority (ASA), the UK’s independent advertising regulator.


Problem

The ASA has regulated paid-for online ads – pop-up, banner ads and paid search – since the dawn of the internet. Following an extension of its online remit in 2011 to cover marketing claims on companies’ own websites and in social media space under their control, the balance of the ASA’s work has increasingly shifted to responding to and tackling online ads. 

By the end of its five year strategy in 2018, the ASA had already put more proactive regulation at the heart of its work, with a particular focus on taking action in the round rather than on a case by case basis. That focus has continued with its new strategy, ‘More Impact Online’. 

The ASA has a dynamic programme of initiatives underway, harnessing new technologies, undertaking ongoing monitoring sweeps across media and working ever more closely with tech giants and social media companies to continually improve and bolster this important work. Its key aim is to better regulate online advertising, as well as being – and being seen to be – at the forefront of online ad regulation.

As part of the ASA’s work in this area, Faculty was asked to develop a roadmap for the role of AI in this new, digital future.


Solution

Through a series of in-depth interviews with key stakeholders, coupled with our own expertise in the real world application of AI, we created a clear picture of the organisation’s needs in five key areas: people and capabilities, governance structure, processes, technology, and culture. With this information in hand, we worked with the ASA to develop a practical plan which would help it achieve its ambitious goals. This strategy was divided into three phases, each one laying the groundwork for success in the next. 

The first phase, ‘Walk’ was designed to establish a strong foundation for AI and machine learning, and create ‘quick wins’ that drive efficiency and prove the value of investment. Recruiting for key strategic and technical roles will be key to success here, as the ASA establishes and shapes its new data science function.

In the ‘Run’ phase, efficiency gains will multiply and the ASA will find new uses for AI that boost its effectiveness, too – vital for an organisation of its size, with so many ads to oversee. More developed data science capabilities propel this change, preparing the ASA to take on more complex projects, such as developing predictive models for ‘high risk’ complaints. 

In the final phase, ‘Soar’, the ASA will focus on achieving an industry-leading standard of AI regulation.  Powered by an experienced data science team and a well-developed data infrastructure, the ASA will be able to tackle highly complex projects. Most importantly, the majority of its action should be efficient, effective, proactive, and driven by a clear, impactful purpose. 

 


Impact

Today, Faculty’s strategy is the backbone of the ASA’s latest Data Science Plan, helping to shape the next phase of its investment and digital evolution over the next five years. Based on this plan, the ASA will develop and deploy new capabilities in AI and machine learning that will set new standards in the regulation of online advertising.