In Episode 22 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Vin Vashista, Founder of V Squared and a LinkedIn "Top Voice", where they discuss how to deliver tangible ROI from your data and analytics initiatives, which includes;

• How Vin reached 160K Followers on LinkedIn and became a “Top Voice” by writing about data monetization
• Why he wanted to write a book that was a single blueprint in a book; “From Data to Profit”
• Why 70% of data teams are NOT delivering any returns for their organisation
• Why genuine ROI will keep the hype and boom going  
• Why you need to hire differently to monetize data
• How to identify the first green shoots of value creation
• The biggest problem is that we don’t connect the technology to the strategy
• Why it’s imperative to get C-Suite sponsorship if you want to be successful
• Why you have to delvier ROI incrementally and not wait for a big bang
• If you let technology drive strategy you end up with more technology
• Why you need a prioritization framework
• Why the frustrations of data and C-Suite professionals is the same root cause
• Why you need an opportunity discovery framework that involves the whole business
• Why business teams know where the opportunities are but they have no way of articulating their needs
• Why data teams aren’t the best people to decide what the business should be doing
• How we confuse strategy and tactics
• Why we need to interrogate our data & analytics ideas like a shark tank pitch
• Why most C-Suite Leaders think the data team needs to be managed as it can’t be accountable for its own value creation
• Why you need a Data Monetization catalogue
• The 3 slide sales deck that Execs keep falling for
• The 9-figure ROI use cases
• Why there are so few people who can connect hype to revenue
• Why C-Suite executives are transfixed on ROI yet still invest in data projects that don’t deliver any ROI
• Why many Data Leaders are great strategic leaders yet most don’t actually lead the strategy
• Why to be a successful CDO you need to have come from a Data role/background, but shouldn’t be hands-on
• Why we should train our technical people to be more than just more technical
• Why moving forward people who can’t prove ROI won’t have a place in the organisation
• Why data teams will be the growth engine for most businesses over the next 5 years
• The misunderstanding that you can clean your way to valuable data  
• Why you need a product-first approach to data
• Buy-in = TRUST
• Why 'track record of success' is the  only way to C-Suite sponsorship

In Episode 21 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Hannah Davies, Head of Data Academy at Admiral Group, where they discuss what it takes to build an effective Data Academy, which includes; 

• The importance of stakeholder engagement 
• Why it’s always about people 
• The journey of building a Data Academy community of 700 people 
• Why a Data Academy is so much more than training 
• Why the first hire into the Data Academy was an engagement and content officer 
• Having the ability to remove silos 
• Why data is the answer 
• The force that brings together; literacy, adoption, upskilling, development, community
• The different ways of working with different sizes of data teams 
• Being a great place to work for data professionals 
• The importance of giving people a way to engage without forcing it on them
• The 5 key pillars of the Data Academy 
• Why the element of community is her proudest achievement 
• What the community is made up of 
• How to cater for different audiences 
• Why many people have “taught fear”
• Removing the barrier of making a business decision with data
• How to change mindset and build confidence 
• The difference between data training and data culture 
• Tackling culture, adoption and literacy 
• Things to think about if you’re in the process of building a Data Academy 
• Upskilling, reskilling and retention  

In Episode 20 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Tiankai Feng, Data Governance Leader and former Senior Director of Product Data Governance at Adidas, where they discuss the importance of making data more fund and how to drive results through creativity, which includes; 

• The importance of making Data more fun 
• The steep learning curve and benefits of moving into governance from analytics 
• Why ‘use-case thinking’ is the most exciting but difficult part of Data Governance 
• How Data Quality is completely subjective based on usability 
• Why creativity and data are often seen as a paradox 
• Why creativity is all about mindset 
• Why urgency and frustration led him to bring creativity into his data role 
• How the enemy of creativity is common sense 
• The benefits gained from bringing this level of creativity to the data team  
• Why there are always ways of doing things differently in Data & Analytics 
• The value that creativity brings to communication 
• How you can use unconventional formats to communicate the value of data
• How you can improve communication, collaboration and PR by being creative
• How you can increase literacy by thinking more creatively 
• The area it has been the most effective in the organisation 
• Leadership sponsorship and stakeholder advocacy 
• Where you should start to think about where you can be different/creative 
• How you can channel your inner creativity 

In Episode 19 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by CJ Anderson, one of the most recognised Data Governance advisors in the UK, where they discuss the importance of tackling Data Governance from the bottom up, which includes; 

• CJ’s journey from a librarian to one of the most recognised names in Data Governance
• Why most legal organisations' clients are far more data mature than they are
• Why the role of Data Governance isn’t about enforcing policies
• Why you want the most junior people to be having the Data Governance conversation
• The importance of opening the lines of communication
• DG is about helping to change the perception of Data
• The importance of the data sausage machine
• Why Data Governance is your Lego green mat
• The importance of using language that makes sense to your audience
• The challenges that most data-immature organisations face on their journey to data maturity
• How operational processes happen in silos and why cross-functional working isn’t common
• Why job titles matter
• Why you should start small and at the bottom
• Why data maturity is a marathon and not a sprint
• The two differing Data Governance approaches
• Why most organisations only have 1000 data points they truly care about
• The relevance of the Silk Road story in data stewardship
• Why Data Governance doesn’t work while sitting in IT

In Episode 18 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Sarah Schlobohm, Head of AI at Kubrick Group, where they discuss how not to do Machine Learning and why organisations are getting it wrong, which includes; 

• The frustrations as a hiring manager in the ML space 
• The most common mistakes organisations make when implementing AI 
• The importance of engineering in ML
• Why so many ML projects don’t make it into production 
• Why you need to think about the whole lifecycle and ecosystem 
• The different challenges from the technical side to the business side
• Why you don’t want to be a solution looking for a problem 
• Why you should fail and do so fast 
• The importance of knowing when to give up 
• Balancing the business strategy and the hype of AI 
• The signs that you’re not ready for AI/ML
• Why you should do some analysis to identify relevant use cases
• Why you should have the technical skills in the room before the ML decision is made 
• The future of ML tooling 
• Why the cost of ML is drastically underestimated and the impact that has on ROI 
• Why the amount of time and effort that should go into Data Governance is underestimated 
• The role of MLOps 
• Why there’s no substitute for domain expertise 
• The pros and cons of different reporting structures 
• AI Ethics and the examples of where things have gone wrong
• The practical steps that organisations can take to improve Diversity & Inclusion 
• Why diversity is a cultural challenge
• Why women shouldn’t be pushed into non-technical roles 

In Episode 17 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Colm O'Grada, Director of Data & Analytics at Tines, where they discuss the differences in building a high-impact Data & Analytics capability between a large (Google) and small (Tines) organisations (Tines), which includes; 

• The key differences between building teams in big organisations to small teams
• The journey from Google to Tines
• Contrast with ‘adopting’ teams in larger companies
• The pro's and cons of having a much smaller bench
• Being the first data hire in a growing organisation
• Why you need to be more versatile in a smaller company
• The importance of being hyper focussed
• Focusing on breadth versus depth
• Why trends don’t really matter for most companies
• What trends might mean for data workers
• Organisational structure of data teams
• The cynicism around the current tech layoffs
• Why being invited to meetings is a sign of someone who’s doing their job well
• The importance of data in times of uncertainty
• Why all data functions aren’t built equally
• Getting the balance right between generalist V specialist roles

In Episode 16 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Benny (Clive) Benford, Chief Data Officer, Formerly of Jaguar LandRover (JLR), where they discuss the journey to realising £500m in commercial value through data and analytics, which includes; 

• The journey of building a Data & Analytics function at JLR
• How they unlocked and realised £500m worth of commercial benefit and value
• How to ensure the data team is consistently delivering value
• The importance of having a process of engagement
• How to prioritise the workload and the value the potential return of each project
• How to allocate/attribute value
• The mission statement of creating £1m of value per team member, per year
• Transforming decision-making across an entire enterprise
• Why it’s important for senior data leadership needs to wait for the right career opportunity
• Why the conditions are so important to success
• Why most business users/leaders don’t view data as something that can provide “value”
• Making the business case for large-scale investment
• Why you need to agree on the value before you commit to any project
• The impact of the hype in Data & Analytics
• Why there are so many instances where organisations are tech-first and value-last
• Who’s to blame for a lack of ROI
• Why it’s so important to have a range of skills and not just data/technical skills
• Why over 1/3 of the team didn’t have a technical skillset
• Why everyone underestimates the level of change required to deliver value
• The importance of a communication strategy and how to utilise it well
• How they quantified that if they could deliver all projects, there would be £1.2b of value
• The importance of your people knowing why they’re doing the work
• How they built an apprenticeship programme of 700 people (15-17% of all data apprentices in UK)
• Where the responsibility of the data team ends
• Why it’s better to start without the big infrastructure project
• Why they received funding to invest in people but had the technology budget cut

In Episode 15 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Paul Evangelista, Chief Data Officer at United States Military Academy at West Point, where they discuss how the armed forces are using Data & Analytics to drive innovation, which includes; 

• The role of Data in the current US Military Academy
• How Data has played a role in the military since the early 1900’s
• The maturity journey of Data and Analytics in the US military
• The trackers used to measure adoption and usage of Data & Systems
• What the success metrics look like in that environment
• The importance of empowering leaders at all levels
• The importance of culture and executive support
• Why becoming 'data-centric' is second on the priority list of the US Army
• How the armed forces innovate
• Examples of how Data was used in the World Wars
• Why the US Government is hiring leaders from the world’s biggest tech players
• How the US military has a culture of innovation of change
• The role of data on the war in Ukraine
• How they calculate ROI in their field
• Why we need to focus on decision literacy not data literacy
• The gap that exists in the D&A industry

In Episode 14 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Chun Schiros, SVP of Enterprise Data Science Group at Regions Bank, where they discuss the role of responsible AI in organisational transformation, which includes; 

• What data innovation in a traditional industry sector looks like
• The role of speed in data innovation
• The opportunity for partnerships between traditional banks and digital banks
• Why scalability beyond individual use cases will be the differentiator for success with AI solutions
• The importance of integration to become an AI-driven organization
• The core challenges of achieving scalability with AI solutions
• The mindset shift of being able to multiply the impact
• The prioritization tradeoff between benefit and cost
• The importance of being truly customer focused
• The guardrails that create a balance between innovation and ethics
• The role of DEI in responsible AI
• Why failure with AI Innovation is absolutely guaranteed
• The excitement around AI versus the fear of things going wrong
• The importance of having a culture where failure is accepted
• Why you shouldn’t think in terms of offense versus defense
• Why buy-in is directly related to the ability to demonstrate how you can help the organisation to meet strategic goals  
• Shifting culture to adopt Artificial Intelligence
• Prediction on AI trends over the next 12 months

In Episode 13 of Season 3, of Driven By Data: The Podcast, Kyle Winterbottom is joined by Leanne Fitzpatrick, Director of Data Science at Financial Times, and Andy McMahon, Head of MLOps at Natwest Group, where they discuss the current MLOps maturity, which includes; 

• The maturity of MLOps over the last 12 months
• Why getting ML into production is no longer the challenge
• Why the Ops component is now the major challenge
• What best practice actually looks like
• Why ML is more software than Data Science
• Why thinking about MLOps as products is helping the industry
• What does MLOps actually mean to business leaders
• The resiliency and risk elements
• Why design and processes are really what make or break MLOps
• Why we need rules of engagement
• Why we don’t have enough practitioner expertise
• The challenge of building scalable MLOps solutions
• The differences and similarities to software engineering
• Why companies will need to change their operating models to support their MLOps maturity
• The importance of domain expertise for successful MLOps
• The current tooling landscape
• The role of vendors play in the journey
• Build versus Buy
• Predictions for next 12-24 months