In Episode 30, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Sol Rashidi, Former Chief Data, Analytics & AI Officer at various Fortune 100 organisations and now advisor, where they discuss what really causes many of the Data & Analytics industry's challenges and the importance of perception, which includes;

• Starting out as a Data Engineer
• Being a translator before the translator skillset was recognised
• Being a techno-functional Data Executive
• Helping to launch IBM Watson
• Why you’re never brought in as a CDO when things are going well
• Why your value has nothing to do with what you can build
• Why success has nothing to do with your competence in the data space
• Why you’ve only got 6 months to build the perception of value as a Data Leader
• The framework of understanding what are common, core and local data challenges
• Putting wins on the board amongst conflicting agendas
• Over 70% of organisations don’t understand the value of a CDO yet
• The importance of asking your stakeholders what they think your job is
• Understanding who and what you should prioritise
• What we actually mean when we talk about 'good communication' and ‘getting out in the business’
• Why you need to create function-specific strategy documents for each key stakeholder
• The importance of talking in the language of your stakeholders
• Why you should always talk about their needs and requests
• Creating brand equity by ensuring your stakeholders feel heard and understood
• The catalyst for writing her best-selling book
• Having 40 AI deployments in production at in enterprise organisations
• The 3 key reasons why organisations change tact and don’t follow through
• Why data analytics work is the hardest to quantify in business
• The three measurements of value and ROI; financial, cultural and relevancy
• Landing different messages for different personas
• Why 60% of the day is committed to communication
• Why you presume that people know what you’re doing but they never do
• Why data and analytics people don’t get the correct training to be successful at the executive level
• Why it’s less about IQ and more about EQ, BQ and SQ
• Why you need to report to ‘the business’ if you want to be respected, but, why it’s easier to do the work under IT
• Why you’ll always be starting from a deficit in perception if you sit within IT  
• Why having responsibility is different to having the authority
• What the future of AI will look like
• Why they’ll be a decrease in the amount of AI-based projects over the next 12-24 months  

Thanks to our sponsor, Data Literacy Academy.

Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.

If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.

At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.

From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.

We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.

Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

In Episode 29, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Evie Dineva, Group Head of Data Engineering & Data Science at Gymshark, where they discuss how to balance delivering commercial value through data, analytics and AI products responsibly and ethically, which includes;

• Being driven by the purpose of improving business performance
• Articulating the commercial value of what Data & Analytics teams do
• The importance of supporting people to be better at what they do
• Working for a brand as big and prominent as Gymshark
• The importance of being in an environment where company values are visible
• Common pitfalls as to why organisations fail to deliver commercial value with data
• Focusing on the why and not the how
• The importance of understanding your vision
• Why success is largely down to building strong relationships
• What good business partnering looks like
• The differences between tactical versus commercial business partnering
• Being advocated for and championed without having to be in the room
• Why the strategic initiatives often hold the bigger commercial gains
• Defining the measure of success before you define the solution
• The rise of Data & AI products and the difference it’s created
• Balancing the pursuit of commercial value with building responsible and ethical data & AI products
• The risks of neglecting ethical considerations
• Where accountability lies with humans and artificial intelligence
• The importance of humans in the loop
• The relationship between risk and literacy
• The relationship between authentic leadership and ethics

Thanks to our sponsor, Data Literacy Academy.

Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.

If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.

At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.

From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.

We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.

Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

In Episode 28, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Pete Youngs, Managing Partner at Ortecha, where they discuss the key considerations of designing and implementing the correct data operating model and its importance in data and analytics success, which includes;

• Why a data operating model is more important than your data strategy
• The day-to-day chaos of living without an operating model
• The relationship between D&A enablement and your operating model  
• Defining the MVP data operating model
• Data operating models in the absence of data strategies
• Why your operating model should be ever-evolving
• The confusion between operating models and team structures
• Why people are the most important part of your operating model
• Why your data operating model can’t conflict with the business operating model
• Trends around centralised versus decentralised structures
• The relationship between team structure cycles and the tenure of the CDO
• The importance of defining role profiles and managing with OKRs
• Why size and scale are important factors in defining the best data operating model
• Why many data operating models are created by data governance or strategy teams
• The relationship between data operating models and delivering value
• The importance of a value-driven mindset and having a value-case
• Balancing value realisation while building your data operating model
• Why not enough focus or time is put into successful implementation and adoption
• Why most CEOs would be shocked if they knew how much it actually costs to do it properly
• Why your data operating model needs to be rolled out iteratively across the organisation
• The symptoms of a successful data operating model and measuring success
• Why data products have changed the way data operating models work
• Why lack of adoption is often due to a lack of process
• The importance of selecting the right partners
• The top four pieces of advice to create the right data operating model
• The relationship between data operating model and data culture

In Episode 27, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Tom Betts, Group Data Director at Kingfisher Plc , where they discuss the complexities, challenges and opportunities of building a centralised data function at a group level to support multiple operating brands, which includes;

• His journey from DJ to Travel Agent to CDO
• Studying Artificial Intelligence in the early 2000s
• Organising a centralised data domain to serve a multi-brand business
• Being the first data leader at group level
• The benefits and challenges of starting from a blank canvas
• The challenge of attracting talent as a group company that people haven't heard of
• Building a data-led customer experience as a pillar of a corporate strategy
• Deciding which capabilities sit within the operating companies versus what is centralised at the group level  
• Working out where the biggest opportunities lie across multiple brands
• Adopting different ways of working within different teams
• The importance of meeting each operating company where they are and not having a group approach to everything
• Dealing with different; cultures, literacy, adoption and maturity across the different brands
• The core use cases that are scalable and reusable across different operating companies  
• Building an orchestration framework for Generative AI tools
• Using gamification as a tool for education and upskilling
• The benefits of building working prototypes to drive buy-in and adoption
• Building a customer-facing generative AI solution
• Understanding and mitigating the risks of a customer-facing GenAi solution
• Considering the risks of inaction
• Why you’ll always learn more from just doing
• Why the role of Chief AI Officer is not needed in isolation
• Why it’s important to have teams that are delivering DS/AI solutions to go as end-to-end as possible in a cross-functional way
• Why it’s faster to build things than it is to leverage what has been built

Thanks to our sponsor, Data Literacy Academy.

Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.

If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.

At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.

From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.

We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.

Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

In Episode 26, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Michelle Gansle, Chief Data, Analytics & AI Officer at McDonald's, where they discuss why, as one of the world's biggest brands, they still have a commitment to change and innovation and how Data & Analytics fuels that, which includes;

• 3 fun facts that people don’t know about McDonald's
• The data and analytics goals of McDonald's
• The size and scale of the D&A capability at McDonalds
• Defining the right operating model for such a large enterprise
• Key D&A use cases in the fast food industry
• Why prioritisation should be the easiest part of the job
• Why even the biggest companies need to optimise and innovate to be successful
• Why one of the world's biggest brands has a commitment to change
• The tangible impact that certain innovations like drive-thru’s and delivery apps have had on their business
• What the landscape looked like before and after the pandemic
• Building a foresight team to predict what may happen in the future
• The three-legged stool concept
• Why the McDonalds culture has always been tied to innovation
• How innovation is in service of the organisation's core business
• Why they view their size and scale as an incomparable advantage
• The double-edged sword of being a large business
• Why relentless curiosity will make you successful
• Understanding the difference between what you could do versus what you should do
• The benefit of having a seat at the table
• Why it’s imperative to understand what “the end” is, and why Data & Analytics is not it
• Who really are the competitors
• Why they’re rarely first to market but are often fast followers
• The role that GenAI will play at McDonald's
• The 3 horizons of Generative AI
• How D&A was mentioned 42 times at investor meetings

Thanks to our sponsor, Data Literacy Academy.

Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.

If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.

At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.

From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.

We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.

Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

In Episode 25, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Irina Mihai, Director of Data, Marketing Analytics & Decision Science at Adidias, where they discuss how to create an environment to ensure that the work of a D&A team is constantly visible, which includes;

• Coming from a non-STEM background and dealing with imposter syndrome
• The importance of branding the Data & Analytics team both internally and externally
• Having an internal decision-support culture
• The benefits of authentic leadership
• The importance of how to decide on which problems to work on
• Intentionally building a team to cater for areas where you have less experience
• Choosing the right KPIs to monitor performance
• Moving from being an individual contributor into a leadership role
• Ensuring you’re not a bottleneck for your team
• The importance of defining your team's purpose within the organisation
• Fostering an environment of psychological safety
• Why you should co-create your roadmap as a team
• The importance of having designated leads for each item of your roadmap as a team
• Why communication skills separate the good from the excellent
• Having a criteria to prioritise what projects to undertake
• Understanding the organisational strategic goals
• Knowing when and why to discontinue a project
• The benefits of having an organisational culture where challenge is welcome
• The importance of having an agreed model of communication to engage effectively with stakeholders
• Why the engagement and commitment of stakeholders is a key evaluation criteria
• The benefits both internally and externally of making sure your D&A team is visible
• Why you can no longer rely on the company brand to attract talent
• Why everyone needs to be responsible for their own visibility

In Episode 24, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Chris Bannocks, Group Chief Data Officer at QBE Insurance, where they discuss how they are productionising GenAI use cases from scratch within 8 weeks, which includes;

• Being a CDAO/Group CDAO in multiple organisations/sectors
• The importance of international experience
• Being allergic to the term ‘data strategy’
• The impact that Gen AI will have on business
• Why GenAI/AI isn’t the solution to every problem
• Harnessing the value that GenAI can bring
• The top and bottom line opportunities of GenAI
• Why GenAI raises the stakes further for D&A teams
• The requirements of the semantic understanding of your data organization
• Going fast and hard on one opportunity to prove it could be done
• Using different mediums to gather 300 potential use cases
• Building things to be reusable and scalable
• Measuring the addressable opportunity
• Why they didn’t have to quantify the value before they got started
• Standing up a technical spike within 6 days to show what could possibly be done
• Having a 12 week deadline to get it done from a standing start with no capability
• How that capability has now reduced time to production to 8 weeks
• The collaboration needed with each leader from different business units
• The importance of creating a working product in production
• Why they avoided focusing on efficiency and focused on increasing revenue instead
• Avoiding enthusiastic experimentation
• Why tight deadlines helped to make decisions quickly and focus on scope/MVP
• Why you should never start a piece of work without input from business stakeholders
• The challenge of ethical and bias considerations
• How they tackled GenAI education across the organisation
• The importance of having a human in the loop
• Building a team that can deliver
• Top pieces of advice for anyone about to embark on this journey

In Episode 23, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Caroline Zimmerman, Director of Data Product & Strategy at Profusion, where they discuss the research study she helped to conduct into how private equity companies are leveraging Data & AI to fuel growth and enterprise value, which includes;

• The catalyst for conducting the research study
• Why private equity has a very specific definition of value and how to measure it
• Why PE has a lot to teach the corporate Data & Analytics landscape
• The major differences between PE-backed firms and the rest when it comes to D&A
• Focusing on enterprise value
• Why time horizons are important and can create urgency with long-term thinking
• The differences between PE Data Leaders and others
• Why PE does ‘BI’ but not in the traditional sense
• The power of growth modelling and the relationship with investment/capital allocation
• The role of Data & Digital in value creation teams
• The career opportunities for Data Leaders in PE
• The two key ways that PE firms are using Data & Analytics across their portfolio
• Obsessing over understanding your most valuable customers
• Culture is still the main challenge to overcome
• The differences between PE firms who specialise versus those with diversified portfolios
• Why data monetisation affects multiple and not just profit
• Why horizontal investments into data infrastructure don’t exist in PE
• Why the D&A community should care about this research
• Why it still should be all about making better decisions
• Roles, titles and remuneration benchmarks of Data Leaders within PE
• Where you can find/access the research study

​A joint INSEAD research project by:

• ​Theodoros Evgeniou, INSEAD Business School
• ​Caroline Zimmerman, Profusion
• ​Olly Blaydon, Armstong International
• ​Shahbaz Alam, AWS

In Episode 22, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Simon Ferriter, CEO at Anmut , where they discuss why organisations are valuing their data like other balance sheet assets, which includes;

• The framework for measuring the value and fitness for purpose of your most important data
• The role of capital allocation in data assets
• How most organisations don’t understand which data assets are important to success
• If data teams lack the business/management acumen to communicate data effectively
• Why data isn’t treated or managed like other resources and assets in an organisation
• Not all data has equal importance to decision-making
• Why the 80-20 rule is likely in play when it comes to data
• Why data valuation is completely context-dependent
• The three financial methods for valuing data
• The importance of social impacts of data (environmental and community)
• The benefit of putting a financial figure on the value of data assets
• Why semantics around language are causing confusion
• Why the financial figure isn’t the end result, it’s what that allows you to do from there
• Why data valuation drives improved "value"
• Knowing which data asset is important for which business opportunities
• Why valuing your data captures the attention of the board and makes it their issue too
• The under-investment in data management capability and the overinvestment in technology
• Why the problem statements are fairly universal across industries and organisations
• Why complexity means intangible assets are overlooked and often undervalued
• Why accounting standards are no longer fit for purpose in the digital age of today
• If data should be on the balance sheet
• Investing in the upstream business process to prevent the need for new tools
• The benefits that organisations are seeing from valuing their data assets
• Why Anmut launched a product to help organisations to self-serve on this process

In Episode 21, of Season 4, of Driven by Data: The Podcast, we're airing the live interview that took place between Kyle Winterbottom and Ranil Boteju, Group Chief Data & Analytics Officer at Lloyds Banking Group which was recorded at the end of 2023 and then transcribed into 'Exclusive Leader Feature' article in the first edition of the Driven by Data Magazine, where they discuss how analytics practitioners are at the heart of value creation at LBG, which includes;

• The power of purpose
• Evolving views of value creation
• The future of analytics skills & value creation
• The potential and pitfalls of Generative AI
• Fostering a data culture
• Building an intentionally different team
• Whether the CDAO role will exist in 5 years

**Read the magazine here; https://orbitiongroup.com/driven-by-data-magazine-home/