Driven by Data: The Podcast

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 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 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

In Episode 35 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Asheeka Hyde, Head of Trading Analytics and Data Science at Dunhelm, where they discuss tangible advice on how to be a better communicator to drive value, which includes;

• Having Data & Analytics as a key pillar of the organisation
• How to achieve executive alignment
• Why most executives are already bought-in
• Why it’s important for executives to actually experience the benefits of Data & Analytics
• How to demonstrate value as early as possible
• The importance of making data problems visible to the execs
• Why you have to truly inspire people
• Why “quick wins” are often merely for winning trust
• Understand what we mean by “value”
• The importance of saying ‘No’
• Why you need to change your communication depending upon the maturity of your organisation
• Why you need to get the execs to prioritise for you
• The differences to consider between organisations with a clear business strategy and ones without
• How there is more than one way of communicating and influencing
• Why working with a comms professional changed her communication style
• Why consistency of communication is absolutely critical
• Understanding if you are the right person to communicate the message you want to deliver
• Why your communication needs to be thoughtful
• If you want 80% of people to leave a room with the right message, you need to tell them 5 times
• Why you have to find different ways of saying the same thing
• The importance of utilising internal comms teams
• The know, do and feel communication framework
• The importance of testing if your message is landing
• Why, if you don’t tell your story then people will create their own

In Episode 34 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Steve Pimblett, Chief Data Officer at The Very Group, where they discuss how to move data from a cost centre to a value creator, which includes;

• A transformation journey that has been ongoing for over a century
• Why some D&A teams are still seen as a cost centre and not a value-creating function
• Why demonstrating value creation is a primary responsibility of a Data Leader/CDO
• The tangible things that Steve has done to be seen as a value-creating function
• The 4 key pillars of their Data Strategy and measuring the capability maturity
• The value-creation measurement framework they’re using and how that helps to communicate
• Why you have to connect data and insight to action
• The importance of talking in outcomes and the benefits of those outcomes, and not data
• Why it’s imperative to have an operating model that supports value-creation
• A Joint-Venture model to prove value and take to an investment board
• How they’ve used hastags to demonstrate the value of Data & Analytics as an enabler to the business functions in those JV’s
• Why ‘data as a product’ has bridged the communication gap and acts as a client success manager
• Why PR has been critical in the success of the D&A team and how external validation has helped