From gut feel to value impact: how the FT prioritises data initiatives

“Our Data & Analytics team isn’t as big as the FT’s”.

This is often the soft push-back from clients when we suggest they start looking into new metrics, data analysis or products to power initiatives (as the FT does), e.g. a Next Best Action model to increase engagement amongst subscribers or a subscriber LTV model etc. 

The FT Data & Analytics (D&A) team is 80+ people strong and includes data engineers, architects, scientists, analysts, market researchers, governance specialists and more - similar to comparable organisations.  This multitude of skill sets is a competitive advantage but comes with its own set of challenges.

Resources, whether human, financial or technical, are finite and efforts need to be made to avoid overstretching or wasting them.  

With 66% of publishers agreeing to using data, analytics and BI to inform product decisions and improve the audience experience (refer chart below), organisations should ask themselves whether they’re investing their resources in the right initiatives. 

The FT has recently hired Ayushman Saha, Head of Data Value, tasked, amongst other things, with introducing a Value Framework to help prioritise data-led initiatives based on their potential to generate Value for the FT.  Aim of this is to free the prioritisation process from subjectivity and gut-feel judgement to help teams focus their efforts on higher value initiatives. 

On average, 100+ requests are submitted to the Data & Analytics team at the FT on a quarterly basis (it’s a big team serving a wide variety of requests from an even larger number of stakeholders). These requests range from Product page redesign A/B test to a Next Best Offer AI-driven model to creating  Strategic Dashboards to AI Governance and can come from any department - App product team or the B2C subscription retention team or the Advertising team or the Editorial team and others.

Sizing each of those incoming requests in terms of the Expected Value helps prioritise them, relaying back the priority order to the Stakeholders. 

How do you decide what to move forward, pause or reject?

FT Strategies mostly rely on the Effort-Impact Matrix, which is well-suited, particularly for quick back-of-the-envelope situations, such as drafting a roadmap in a workshop.

This is (perhaps overly?) intuitive and convenient.  Does it capture the full picture? 

What about:

• adding new dimensions to the framework, like “feasibility” or “risk”
• calculating the realised value, once a project is complete, and comparing it against the estimated value
  
  

At the FT we combine it all in a single number (with the £)

The figure is quick and simple to calculate, comparable across projects, and enables the Data & Analytics team to identify the high-value initiatives before work is commissioned.

This figure is referred to as the “Estimated value”, and it consists of 4 components:

An example of the above in action could be an analytical request with a projected impact of £55,000, 90% chance of realisation, 15 days of effort and 70% contribution, might return an estimated value of £40,000.  

The resulting estimated value for each incoming request is compared against the existing pipeline, with higher value ones taking priority and the lower priority ones being communicated back to the stakeholders.  

Without going into the details (but please reach out if you’d like to), it’s fair to say that a lot of thinking, stakeholder input and past and present data have gone into the estimated value tool and the calculations behind it.

On top of the technical challenge, Ayushman is faced with a cultural “barrier” too. Since this Data Value concept is a relatively new initiative within the FT, he has been spending time with various business teams to educate them on the importance of treating data as an asset and how it can help the organisation to remain agile.  He continues to speak to other organisations to learn and share his experience and help the data community in nurturing the idea of data value.

What’s the feedback so far?

The new framework has now been live for 6+ months, and is constantly evolving based on the constructive feedback of the end users and the data being collected.  

"Creating a view of Estimated Data Value gives us visibility of the potential held within our data and the maximum opportunity that we can realise as an organisation with the right focus and prioritisation.  It also enables our colleagues across the business to clearly see the value of working together to unlock that value through targeted decision-making to better meet our audience's needs and, in so doing, our commercial outcomes."

 

Kate Sargent

Chief Data Officer, Financial Times

 

 

 

"At the FT, our data maturity means we’re no longer focused on convincing teams to use data, but on guiding them toward where it can deliver the greatest impact. Estimated Data Value helps us shift conversations from abstract potential to tangible outcomes. It brings commercial clarity to our data opportunities, enabling smarter prioritisation and more strategic decision-making. This approach is a key driver of our data strategy, ensuring we invest in the initiatives that matter most."

 

McKinley Hyden

Data Value and Strategy Director, Financial Times

As part of the D&A Value capture process, there is a Realised Value stage which captures the final outcome of each initiative in £s.  That view helps in two ways - identifying the effectiveness of initiatives and realising how crucial a role data plays.

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