In Episode 45 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is rejoined by, Samir Sharma, CEO & Founder of Datazuum, where they discuss how to really understand business objectives and align a data strategy that you can operationalise, which includes;

• Defining, creating and operationalizing your data strategy
• The ‘Data Strategy Canvass’ and the purpose of existence
• The catalyst for creating it
• Why business teams and data teams are talking different languages
• The reasons why data strategies don’t often align with business strategies
• Why asking the right questions is the critical component
• How recent research has shown that only 6% of data strategies made any reference to business value generation
• The 3 questions to answer about every use case
• The difference between benefits and outcomes
• Why many organisations don’t have clearly defined business strategies
• How you can understand what the business objectives really are
• Why you don’t need to be at the decision-making table to aligning data strategy to business strategy  
• The 3 buckets that all value levers are tied to in the eyes of “the business”
• Why too many focus on data use cases and not business use cases
• The value discrepancy between business leaders and data teams
• Why most organisations don’t assess Data Leaders for the skills they actually need  
• Why reporting lines don’t matter
• The 7 steps to align a data strategy to business objectives

Link to Data Strategy Canvass: : https://www.linkedin.com/posts/samirsharma1_data-valuecreation-business-activity-7101161956320907266-GlNT?utm_source=share&utm_medium=member_desktop

In Episode 44 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by, Dan Kellet, Chief Data Officer at Capital One where they discuss how to strike the balance between driving innovation while delivering day-to-day, which includes;

• The benefits of working in one organisation for 23 years
• How a data and analytics journey evolves inside an organisation over that timeframe
• Why so many things are different but a lot of things are still the same
• What innovation means in a global organisation
• The relationship between innovation and value
• Quick Wins V Innovation
• The benefit of having a clearly defined business strategy
• Why innovation is all about people
• Why relationship building is one of the most important skills to success
• The impact a team structure has on realising value
• If team structures play a part in being able to innovate
• The benefits and challenges of a centralised versus fragmented team structure
• How to spend your time to strike the balance between delivery, innovation and value
• Advice on how to reprioritise with innovation in mind

In Episode 43 of Season 3, of Driven by Data: The Podcast, we’re sharing the conversation that Orbition Group’s very own Kyle Winterbottom and Catherine King took part in for the DAMA UK and BCS Diversity in Data Conference, hosted by Jenny Andrew, which includes;

• A snapshot of the Data & Analytics talent landscape today
• Current trends in Data & Analytics talent
• Encouraging more women into Senior Leadership
• How to create truly diverse teams  
• The importance of Non-STEM routes into Data
• The need to raise awareness at earlier ages
• Why we should be striving for diversity of thought
• How most organisations confuse DEI & representation
• The role of non-technical roles in diversity
• The importance of mentorship
• How to utilise events and external networking opportunities
• Battling Imposter Syndrome
• The impact job descriptions have on diversity
• What do companies mean by hybrid working in 2023
• Fixing a flawed hiring process

Video link to conference: https://www.youtube.com/watch?v=ZzmE9P-JD0s&t=18s

In Episode 42 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by, Scott Hirleman, CEO and Founder of Data Mesh Understanding and host of 'Data Mesh Radio' podcast where they discuss, the current Data Mesh landscape and how that's been impacted by Generative AI, which includes;

•  What Data Mesh is, and what it isn't
• The current state of play in the Data Mesh landscape
• What has worked in relation to extracting value from Data Mesh
• The organisations that have been very successful in implementing Data Mesh
• The common use cases that make it applicable
• If Data Mesh is right for your organisation, or not
• Why you would consider taking the Data Mesh route
• The impact of agility and speed
• The struggles of implementing at scale
• What to do and what not to do
• Why Data Mesh has been drowned out by Gen AI
• The relationship between Data Mesh and Gen AI
• Why the D&A industry is obsessed with chasing the "new shiny"
• How to prevent ourselves from doing so
• How to leverage our businesses' enthusiasm for the "new shiny"

In Episode 41 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by, Beth Bauer, Founder and CEO of PosiROI, where they discuss, the 4 key dimensions required to deliver innovation and value at scale, which includes;

• Why feedback loops are critical to driving innovation and a data-informed culture
• The importance of meeting people where they are
• Why value means different people to different people
• Why value always needs to translate to money eventually
• How the 1st steps of value creation are unlikely to be related to money
• Why we need to recognise there are different value points
• Why having the data culture that we want can create power struggles
•  The 4 dimensions that underpin the journey toward value creation
• Why Sales, Marketing and Speed define whether your innovation will be successful
• How innovation occurs in silos within the same organisations
• The ADEPT framework for strategies that assist with the acceleration of the 4 dimensions in a data-informed culture
• Why value of data needs to be measured against the number of use cases it can solve
• Why trust is the anchor to everything
• Why relationships will always win over data in building trust
• Building a high-performance team that creates value with data
• Why data is a team game and not just a data-team game
• To build a data-informed culture you need a sales and marketing capability

In Episode 40 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by, Deepak Jose, Global Senior Director, Head of One Demand Data Analytics Solutions at Mars Wrigley, where they discuss how to create a value-first mindset to break down organisational silo’s, which includes;

• Creating a single source of truth
• The ‘one-demand’ mindset
• How the concept of Ikigai led him to Mars
• How to understand, identify and prioritise business problems that add value
• Moving from reducing costs to creating profit and growth
• The importance of building relationships with functional leaders
• The 70, 20, 10 principle which dictates where investment and resource is directed
• Being “value-driven” despite the hype of being “data-driven”
• What constitutes value
• The concept of the 'balance scorecard' to create KPI’s that generate value
• The story of the Honduran Bridge and the relationship with Data Products
• White Box Building and Interoperability
• Investing in Change Management
• Why value-realisation is a team sport
• Why you need to build to adapt not build to last to break down silos
• Building a Gen AI Operating Model that drives a value-first approach
• The Gen AI Framework; do things, do things better and do better things
• The learnings of a 20+ year career of working at giants like Coca-Cola and Mars
• The importance of challenging the status quo
• Why you should be a Gazelle and not a Lion!

In Episode 39 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by, Allison Sagraves, Founding (former) Chief Data Officer at M&T Bank, and Board Advisor, where they discuss the role of the CDAO in the new era of AI and why they are set-up to fail, which includes;

• 91.9% of firms report that they have achieved some measurable value from their investments in data and analytics,
• 23.9% say they have created a data-driven organization
• 20.6% of firms report having established a data culture
• Between 2012 and 2023, companies having appointed a CDO grew from just 12.0% to 82.6%
• Only 35.5% of major companies report that the role is successful and well-established
• Just 40.5% say that the CDAO role is well understood within their company
• The three generations of CDO to CDAO and the pending CDAIO role
• The functional evolution of the CDAO role
• Why the goalposts keep moving for the CDAO
• The need for defined success metrics
• Why the Data & Analytics industry is always under construction
• Why we’re too glass half empty and there’s too much focus on what we’ve not achieved  
• The need to quantify what value is and communicate the value we’ve achieved
• The “build it and they will come” mentality
• How we no longer need to sell the simple concepts of data
• If you’re still having to convince people then you’ve got the wrong people in the company
• Whether reporting line impacts the effectiveness of the CDAO role
• The hardest thing for any CDAO to figure out is identifying what problem you actually need to solve
• What’s wrong with the CDAO role as of today
• What needs to happen to address those issues
• Moving into the AI era as a CDAO
• The skills needed to be a modern-day CDAO

Link tot he article discussed in the episode:

https://hbr.org/2023/06/why-chief-data-and-ai-officers-are-set-up-to-fail

In Episode 38 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Sami Rahman, Head of Data Engineering and Data Platform at Penguin Random House, where they discuss how to build an MLOps capability that drives business benefit, which includes;

• His journey from Business Psychologist to MI5 reject to Data Leader
• Being told to give up because he would never work in data without a computer science degree
• Being unemployed for 1 year and receiving 326 rejections
• Building an entire MLOps system for £50,000
• Reducing the time to build models from months to days
• Reducing the time to productionise ML models from 5 months to minutes s
• Generating a 200% increase in performance across all 12 measures of success
• Why MLOps forces you to think about how the model will drive value
• How MLOps can be beneficial across the whole D&A value chain
• The differences between MLOps and AIOps
• Why MLOps isn’t new DevOps
• The future of MLOps and the relationship with Genertaive AI
• Choosing the right MLOps tech and tooling
• Why you need to explain MLOps in less than 2 sentences
• When you should start your MLOps journey
• The usual pitfalls both technical and business that people should be aware of
• The ethical considerations
• AI Explainability - how to understand the outcomes in a business context
• Why we should build an “evil” AI to tackle bias
• The skills you need to execute successful MLOps

In Episode 37 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Lena Mass Cresnik, where they discuss how organisations can develop a Generative AI strategy, which includes;

• The 7 components of a Generative AI strategy
• Generative AI as human intelligence augmentation
• Organisational ROI for using Generative AI tools
• The considerations of developing a Generative AI strategy and roadmap
• Financial Services and Fintech Generative AI business use cases
• The need for upskilling existing staff
• The role of organisational design and operating model in relation to Generative AI
• Measuring the performance and impact of Generative AI models
• The level of expertise or skills required within the data team to successfully execute a generative AI strategy
• The risks of Generative AI
• The differences to consider across different sectors
• The increase in hyper-personalised content
• The role that Generative AI will have on the Data & Analytics job market
• Where Data Leaders should start

In Episode 36 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Andy Cotgreave, Senior Data Evangelist at Tableau, where they discuss the role of data visualisation in driving change and realising value, which includes;

• Why successful data analysts often have varied backgrounds
• Why communication is not a soft skill
• How data visualisation is a language
• The impact that dashboards can have when presented effectively
• How even the most average dataset is highly subjective
• How it is so easy to tell different stories with the same data
• How the pandemic provided both examples of how you can strive to be neutral or enforce an opinion
• The art of creating effective dashboards
• The role of data visualisation in driving change and realising business value
• How, many executives use poorly presented charts in their keynotes
• Four practical tips for better presentation with data visualisation
• Why he disagrees with Seth Godin
• Why you should think about changing your visualisations even if the data is the same
• Who should care about storytelling with visualisations
• The importance of aesthetics
• Why different audiences require different dashboards
• The impact of data democratisation and self-serve on data visualisation
• Some key people of influence to follow in this space