Despite unprecedented data abundance and widespread data science education, even experienced data professionals still struggle to interpret data effectively. They draw wrong conclusions, miss critical insights, or fail to communicate findings in actionable ways.

In this episode, Nicholas Kelly joins Dr. Genevieve Hayes to tackle the critical challenge of data interpretation - revealing why technical expertise alone isn't enough and sharing practical frameworks for transforming raw data into actionable business insights that drive real organisational change.

This conversation reveals:

1. The four primary challenges that make data interpretation so difficult [02:24]
2. Why ChatGPT and AI tools are changing the data interpretation landscape [06:23]
3. The "Five Whys" technique that ensures you're asking the right questions instead of wasting time on problems everyone already understands [17:32]
4. Why successful data projects don't end with presenting insights and what to do next [20:01]

Guest Bio

Nicholas Kelly is the founder of Delivering Data Analytics, a consultancy focused on helping organisations enable their teams to make smarter, faster, and more confident decisions through data and AI. He is also the author of Delivering Data Analytics and the recently released How to Interpret Data.

Links

• Nicholas's Website
• Connect with Nicholas on LinkedIn
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Can you clearly articulate what makes your data science work valuable - both to yourself and to your key stakeholders? Without this clarity, you'll struggle to stay focused and convince others of your worth.

In this Value Boost episode, Dr. Peter Prevos joins Dr. Genevieve Hayes to share how creating a compelling value proposition transformed his data team from report writers to strategic partners by providing both external credibility and internal direction.

This episode reveals:

1. Why a clear purpose statement serves as both an external marketing tool and an internal compass for daily decision-making [02:09]
2. A framework for identifying your stakeholders' true pain points and how your data skills can address them [04:48]
3. A practical first step to develop your own value statement that aligns with organizational strategy while focusing your daily work [06:53]

Guest Bio

Dr Peter Prevos is a water engineer and manages the data science function at a water utility in regional Victoria. He runs leading courses in data science for water professionals, holds an MBA and a PhD in business, and is the author of numerous books about data science and magic.

Links

• Connect with Peter on LinkedIn
• A Brief Guide to Providing Insights as a Service (IaaS)
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Internal data science teams face a unique challenge - they're providing an invisible service that only gets noticed when something goes wrong. This puts data scientists in the awkward position of having to market themselves within their own organization, without any marketing training.

In this episode, Dr. Peter Prevos joins Dr. Genevieve Hayes to share how he applied his PhD research in services marketing to transform his water utility's data team from "report writers" to strategic partners by positioning data science as "Insights-as-a-Service."

This episode explains:

1. Why treating data science as "Customer Satisfaction Engineering" rather than technical implementation shifts everything about team effectiveness [08:19]
2. How understanding both the financial and psychological "price" users pay for insights leads to dramatically better adoption [14:36]
3. The treasure hunt technique that transformed how stakeholders discover and engage with available data resources [18:17]
4. Why the mantra "99% of business problems don't need machine learning" can paradoxically increase your data science impact [22:29]

Guest Bio

Dr Peter Prevos is a water engineer and manages the data science function at a water utility in regional Victoria. He runs leading courses in data science for water professionals, holds an MBA and a PhD in business, and is the author of numerous books about data science and magic.

Links

• Connect with Peter on LinkedIn
• A Brief Guide to Providing Insights as a Service (IaaS)
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

When deadlines loom, it's easy for data scientists to fall into the trap of cutting corners and bending analyses to deliver what stakeholders want. But what if a simple framework could help you maintain quality under pressure while preserving your professional integrity?

In this Value Boost episode, Dr. Brian Godsey joins Dr. Genevieve Hayes to reveal his powerful "Knowledge first, Technology second, Opinions third" hierarchy - a  framework that will transform how you handle stakeholder pressure without compromising your standards.

In this episode, you'll discover:

1. Why this critical hierarchy gets dangerously inverted when deadlines loom and how to prevent it from undermining your credibility [01:05]
2. How to resist the career-limiting trap of cherry-picking facts that merely support executive opinions [04:09]
3. A practical note-taking technique that keeps you anchored to reality when stakeholders push for convenient answers [06:04]
4. The one transformative habit that separates truly valuable data scientists from those who merely validate existing assumptions [07:17]

Guest Bio

Dr Brian Godsey is a Data Science Lead at AI platform as a service company DataStax. He is also the author of Think Like a Data Scientist and holds a PhD in Mathematical Statistics and Probability.

Links

• Brian's website
• Connect with Brian on LinkedIn
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

The data science world has always been obsessed with tools and techniques - a fixation that's only intensified in the era of generative AI. Yet even as ChatGPT and similar technologies transform the landscape, the fundamental challenge remains the same - turning technical capabilities into business results requires a process most data scientists never learned.

In this episode, Dr. Brian Godsey joins Dr. Genevieve Hayes to discuss why the scientific process behind data science remains more critical than ever, sharing how his original "Think Like a Data Scientist" framework has evolved to harness today's powerful AI capabilities while maintaining the principles that drive real business values.

This conversation reveals:

1. Why the seemingly basic question "Where do I start?" continues to derail data scientists' effectiveness and how mastering the right process can transform your impact [01:15]
2. The three stages of the data science process that remain essential for career success even as AI dramatically changes how quickly you can execute them [11:07]
3. How the accessibility revolution of generative AI creates new career opportunities for data scientists in organizations that previously couldn't leverage advanced analytics [18:34]
4. The underrated troubleshooting skill that will make you invaluable as organizations increasingly rely on "black box" AI models for business-critical decisions [20:21]

Guest Bio

Dr Brian Godsey is a Data Science Lead at AI platform as a service company DataStax. He is also the author of Think Like a Data Scientist and holds a PhD in Mathematical Statistics and Probability.

Links

• Brian's website
• Connect with Brian on LinkedIn
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Even the most brilliant data analysis can fall flat when presented with poor visualisations. Many data scientists simply use default charts from their analysis software, missing the opportunity to create compelling visuals that drive understanding and decision-making.

In this Value Boost episode, Bill Shander joins Dr. Genevieve Hayes to share the design principles that can transform technical charts into powerful communication tools - even for those without formal design training.

This quick-hit episode reveals:

1. Why default visualisation settings in most software undermine effective communication [02:03]
2. The research-backed "preattentive response" principle that determines whether your visualisation succeeds or fails [05:17]
3. How the counterintuitive "do less" approach creates more impactful data stories [06:18]
4. A simple glance test to immediately evaluate and improve any visualisation you create [11:21]

Guest Bio

Bill Shander is the founder of Beehive Media, a data visualisation and information design consultancy. He is also a keynote speaker; teaches workshops on data storytelling, information design, data visualisation and data analytics; and is the author of Stakeholder Whispering.

Links

• Bill's Website
• Connect with Bill on LinkedIn
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Data scientists can often find themselves in a frustrating cycle - meticulously executing stakeholder requests only to discover what they delivered isn't what was actually needed. The disconnect between what stakeholders ask for and what truly solves their problems can derail projects and limit advancement of your career.

In this episode, Bill Shander joins Dr. Genevieve Hayes to reveal the "Stakeholder Whispering" approach from his new book - a methodology that transforms technical experts from order-takers into strategic partners who uncover and address true business needs.

This conversation reveals:

1. Why stakeholders struggle to articulate what they truly need (and often don't even know themselves) [06:32]
2. How the "Socratic method" creates breakthrough moments that help stakeholders discover their own requirements [11:00]
3. The six-question framework that strategically alternates between divergent and convergent thinking to reveal hidden needs [14:54]
4. Why approaching stakeholder conversations like a curious investigator rather than a cross-examiner builds trust and uncovers deeper insights [13:28]

Guest Bio

Bill Shander is the founder of Beehive Media, a data visualisation and information design consultancy. He is also a keynote speaker; teaches workshops on data storytelling, information design, data visualisation and data analytics; and is the author of Stakeholder Whispering.

Links

• Bill's Website
• Connect with Bill on LinkedIn
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Looking for powerful AI tools that can dramatically boost your impact, regardless of the size of the businesses you serve? 

You don't need an enterprise-size budget to transform your work and create massive value for your stakeholders.

In this Value Boost episode, Heidi Araya joins Dr Genevieve Hayes to reveal three high-impact, low-cost AI tools that deliver exceptional ROI for both your data science career and for even the most budget-conscious clients.

In this episode, you'll uncover:

1. Why Claude consistently outperforms ChatGPT for business applications and how to leverage it as your AI partner for everything from sales coaching to content creation [01:32]
2. How Perplexity delivers real-time research capabilities that save hours of manual work while providing verified sources you can trust [04:02]
3. How Fireflies AI notetaker creates a searchable knowledge base from client conversations that enhances follow-up and project management [07:56]
4. A practical first step to start implementing this maximum-value toolkit in your data science practice tomorrow [09:39]

Guest Bio

Heidi Araya is the CEO and chief AI consultant of BrightLogic, an AI automation agency that specializes in delivering people-first solutions that unlock the potential of small to medium sized businesses. She is also a patented inventor, an international keynote speaker and the author of two upcoming books, one on process improvement for small businesses and the other on career and personal reinvention.

Links

• Connect with Heidi on LinkedIn
• BrightLogic website
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

While most data scientists chase after scraps at the big business table, a hidden gold mine sits completely ignored. Small businesses are desperate for AI solutions but can't get help because everyone thinks they're "too small."

The truth? These overlooked clients - representing a staggering 99.8% of all businesses - are willing to pay real money for simple AI implementations that deliver jaw-dropping ROI. We're talking five to seven-figure returns from solutions you could build in your sleep.

In this episode, Heidi Araya joins Dr Genevieve Hayes to reveal exactly how data scientists can escape the soul-crushing enterprise world and build a thriving practice serving clients who actually appreciate your genius.

Prepare to discover:

1. Why AI implementations for small businesses can deliver dramatically higher ROI than enterprise solutions [12:16]
2. The three pre-built AI solutions that consistently generate the greatest value for resource-constrained clients [12:16]
3. A practical framework for identifying high-impact opportunities even when clients have minimal data [16:59]
4. The "AI receptionist" solution that generated $30 million in new business from dead leads for one small client [21:19]

Guest Bio

Heidi Araya is the CEO and chief AI consultant of BrightLogic, an AI automation agency that specializes in delivering people-first solutions that unlock the potential of small to medium sized businesses. She is also a patented inventor, an international keynote speaker and the author of two upcoming books, one on process improvement for small businesses and the other on career and personal reinvention.

Links

• Connect with Heidi on LinkedIn
• BrightLogic website
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Would you believe that sharing a conversation in the lunch room could be more valuable to your data science career than spending countless hours behind a computer, perfecting algorithms and models? It's a radical idea, but it's exactly the kind of thinking that transforms good data scientists into exceptional ones.

In this Value Boost episode, AI strategist Gregory Lewandowski joins Dr Genevieve Hayes to explain his controversial 90-10 rule: that success in AI and data science is 90% about people and only 10% about technology - and shares a surprisingly simple way to put this principle into practice.

You'll learn:

1. Why focusing purely on technology creates a dangerous blind spot [01:53]
2. The critical success factor that most data science teams overlook [03:54]
3. The "toasted sandwich strategy" for building crucial relationships [05:54]

Guest Bio

Gregory Lewandowski is the Chief AI Strategist and Founder of GLEW, a consultancy focussing on the business side of AI ROI.

Links

• Connect with Gregory on LinkedIn
• GLEW Services website
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE