Value Driven Data Science

Many data scientists begin their careers expecting to influence strategic decisions, only to find themselves trapped as "data order takers" - endlessly running reports and responding to requests without understanding their business impact. This reactive approach limits career growth and earning potential, keeping even experienced professionals from reaching their strategic potential.

In this episode, Kashif Zahoor joins Dr. Genevieve Hayes to share his journey from data order taker to strategic business partner, revealing a practical framework that any data professional can use to transform their role and accelerate their career growth.

You'll learn:

1. The three-step framework for evolving from order taker to strategic partner: amplify efficiency, deliver measurable value, and partner first, analyze second [06:21]
2. Why understanding your company's financial model is crucial for demonstrating real business impact [10:57]
3. The mindset shift from waiting for requests to proactively identifying and solving business problems [19:33]
4. How building trust through consistent delivery opens doors to bigger strategic conversations [17:04]

Guest Bio

Kashif Zahoor is the Vice President of Business Intelligence at Influence Mobile and has extensive experience in data leadership.

Links

• Connect with Kashif 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 compelling data presentation can fail if it runs headfirst into your stakeholders' cognitive blind spots. Decision makers who claim to be "data-driven" often unconsciously filter information through their existing beliefs, leaving brilliant insights ignored or dismissed.

In this Value Boost episode, Dr. Russell Walker joins Dr. Genevieve Hayes to reveal practical techniques for identifying and overcoming the cognitive biases that sabotage data-driven decision making.

This episode reveals:

1. How confirmation bias transforms data analysis into a "numerical Rorschach test" where stakeholders see only what confirms their existing beliefs [02:59]
2. The "verbal jujitsu" technique that acknowledges preconceptions without confrontation, allowing stakeholders to save face while guiding them toward data-driven conclusions [03:47]
3. Why recency bias makes yesterday's angry customer complaint outweigh months of systematic data analysis in executive decision making [05:24]
4. The pre-meeting strategy that helps you anticipate and prepare for stakeholder blind spots before they derail your presentation [07:00]

Guest Bio

Dr Russell Walker is the principal consultant at Walker Associates, which specialises in data science education and healthcare analytics, and previously served as a professor at DeVry University, where he co-founded the university’s business intelligence and analytics program. He holds a PhD in business administration with a specialty in computer science.

Links

• Russell's Website
• Connect with Russell 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 storytelling might make your findings memorable, but persuasion is what gets your recommendations implemented. 

Many data scientists have mastered communication and storytelling, yet still watch their brilliant insights gather dust because they haven't learned the crucial difference between informing stakeholders and persuading them to act.

In this episode, Dr. Russell Walker joins Dr. Genevieve Hayes to reveal how battle-tested frameworks from competitive debating can bridge this gap, transforming data scientists from skilled communicators into persuasive advocates who drive real organizational change.

This conversation reveals:

1. The fundamental difference between ethical persuasion and manipulation [03:13]
2. How to make dry statistics emotionally compelling by connecting data points to human experiences that resonate with decision-makers [08:11]
3. The four-part "stock issues" framework from policy debate that transforms any technical presentation into a persuasive business case [11:22]
4. The executive summary and headline strategies that ensure your persuasive message cuts through information overload [17:44]

Guest Bio

Dr Russell Walker is the principal consultant at Walker Associates, which specialises in data science education and healthcare analytics, and previously served as a professor at DeVry University, where he co-founded the university’s business intelligence and analytics program. He holds a PhD in business administration with a specialty in computer science.

Links

• Russell's Website
• Connect with Russell 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

Social media data drives countless business decisions, but up to 40% of social media engagement may be artificial or manipulated by bots. For data scientists accustomed to cleaning messy data, deliberately manipulated data presents an entirely different challenge that requires specialized detection techniques.

In this Value Boost episode, Tim O'Hearn joins Dr. Genevieve Hayes to reveal practical strategies for identifying and filtering out bot activity from social media datasets to extract trustworthy business insights.

This episode uncovers:

1. The telltale patterns in social media data that reveal bot activity [03:10]
2. How machine learning classifiers can identify bot accounts [05:20]
3. Why removing bot activity can increase marketing ROI by 10-20% [06:41]
4. The broader application of these techniques beyond social media for identifying "dodgy" data records in any dataset [07:25]

Guest Bio

Tim O’Hearn is a software engineer who spent years gaining millions of followers for clients by circumventing anti-botting measures on social networks. He is also the author of the new book, Framed: A Villain’s Perspective on Social Media.

Links

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

Social media algorithms silently shape what billions of people see and how they interact online. While most data scientists work to optimize business value within platform rules, there's valuable knowledge to be gained from understanding how these systems can be exploited - knowledge that can make ethical data scientists better at their jobs.

In this episode, Tim O'Hearn joins Dr. Genevieve Hayes to share insights from his experience manipulating social media platforms, revealing what ethical data scientists can learn from understanding the dark side of algorithmic systems.

This conversation reveals:

1. How social media platforms are essentially just sophisticated recommendation engines [08:16]
2. The "canary" technique for detecting when underlying systems have changed [11:36]
3. Why customer accounts often provide better testing data than artificial test accounts [13:56]
4. The importance of time series data collection for identifying suspicious patterns, effectiveness of campaigns, and understanding platform dynamics [18:04]

Guest Bio

Tim O’Hearn is a software engineer who spent years gaining millions of followers for clients by circumventing anti-botting measures on social networks. He is also the author of the new book, Framed: A Villain’s Perspective on Social Media.

Links

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

Most dashboards and reports get ignored despite all the technical expertise that goes into creating them. The reason isn't technical limitations or poor data quality - it's that they fail to deliver value to the people who are supposed to use them.

In this Value Boost episode, Nicholas Kelly joins Dr. Genevieve Hayes to reveal proven strategies for increasing dashboard adoption and showcasing your value as a data professional.

In this episode, you'll discover:

1. The number one reason why dashboards fail [01:15]
2. The three-bucket framework that transforms dashboard development [04:06]
3. How to salvage an already-built dashboard [07:12]
4. The simple wireframing technique that opens doors to meaningful user conversations [10:08]

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

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