Leaders of Analytics

Do you really need a data-driven culture? Maybe not.

According to Bill Schmarzo, the CEO’s mandate is to become value-driven, not data-driven. For analytics teams that means one thing: no one cares about your data, they want results!

In this episode of Leaders of Analytics, Bill and I explore the economics of data & analytics and how to drive powerful decisions with data. Decisions that turn into business value.

Bill is the author of four text books and one comic book on generating value with analytics. He is a long-serving business executive, adjunct professor, university educator and global influencer in the sphere of big data, digital transformation and data & analytics leadership.

In this episode of Leaders of Analytics, we discuss:

• Why Bill has split his career between corporate leadership and education
• What value engineering is and how it pertains to data and analytics
• How to determine the economic value of data and analytics
• Why data management the single most important business discipline in the 21st century, and much more.

Bill's website: https://deanofbigdata.com/

Bill on LinkedIn: https://www.linkedin.com/in/schmarzo/

Bill on Twitter: https://twitter.com/schmarzo

Do you really need a data-driven culture? Maybe not.

According to Bill Schmarzo, the CEO’s mandate is to become value-driven, not data-driven. For analytics teams that means one thing: no one cares about your data, they want results!

In this episode of Leaders of Analytics, Bill and I explore the economics of data & analytics and how to drive powerful decisions with data. Decisions that turn into business value.

Bill is the author of four text books and one comic book on generating value with analytics. He is a long-serving business executive, adjunct professor, university educator and global influencer in the sphere of big data, digital transformation and data & analytics leadership.

In this episode of Leaders of Analytics, we discuss:

• Why Bill has split his career between corporate leadership and education
• What value engineering is and how it pertains to data and analytics
• How to determine the economic value of data and analytics
• Why data management the single most important business discipline in the 21st century, and much more.

Bill's website: https://deanofbigdata.com/

Bill on LinkedIn: https://www.linkedin.com/in/schmarzo/

Bill on Twitter: https://twitter.com/schmarzo

Great analytics teams understand that they are responsible for two things concurrently: production and consumption.

Most analytics teams master the production part well. After all, that’s why they exist, to produce analytics.

However, analytics only matter if someone consumes them and makes valuable decisions as a result. “Decision + value” is what we’re after.

To be able to make valuable decisions from analytics, consumers must be data and analytics literate, and that often comes down to education and culture creation.

So, how do you build analytics literacy in your organisation?

In this episode of Leaders of Analytics, Ben Jarvis, Head of Scaled Customer Services and Operations AUNZ at Google, answers this question and many more related to building a strong analytics culture.

Listen to learn:

• How Ben went from practicing law to becoming a senior analytics leader and operational GM
• How to coach and mentor technical and non-technical stakeholders on data and analytics literacy
• How do traditional businesses that aren’t born out of the internet era can transform into data-driven and analytics-literate organisations, and much more.

Connect with Ben on LinkedIn: https://www.linkedin.com/in/ben-stuart-jarvis/

Great analytics teams understand that they are responsible for two things concurrently: production and consumption.

Most analytics teams master the production part well. After all, that’s why they exist, to produce analytics.

However, analytics only matter if someone consumes them and makes valuable decisions as a result. “Decision + value” is what we’re after.

To be able to make valuable decisions from analytics, consumers must be data and analytics literate, and that often comes down to education and culture creation.

So, how do you build analytics literacy in your organisation?

In this episode of Leaders of Analytics, Ben Jarvis, Head of Scaled Customer Services and Operations AUNZ at Google, answers this question and many more related to building a strong analytics culture.

Listen to learn:

• How Ben went from practicing law to becoming a senior analytics leader and operational GM
• How to coach and mentor technical and non-technical stakeholders on data and analytics literacy
• How do traditional businesses that aren’t born out of the internet era can transform into data-driven and analytics-literate organisations, and much more.

Connect with Ben on LinkedIn: https://www.linkedin.com/in/ben-stuart-jarvis/

If you’re anything like me, you have a love/hate relationship with marketing. Marketing can be delightful, obnoxious or somewhere in-between, depending on content and context.

Most of us remember an ad from our youth that has given us a life-long emotional connection to a brand or product. Most of us also remember that obnoxious sales call or email campaign that made us swear never to buy from the offending company again.

In this episode of Leaders of Analytics, you will learn from Ikechi Okoronkwo why data-driven marketers have a leg-up when it comes to designing and executing impactful campaigns that hit the right audiences and create delight.

Ikechi is Executive Director, Managing Partner and Head of Business Intelligence & Analytics at Mindshare. Mindshare is a global media and marketing agency, and part of global marketing powerhouse GroupM.

Listen to this episode to learn:

• What Ikechi sees as the biggest opportunities in data-driven marketing
• What kinds of analytics to invest in to optimise the impact of your marketing efforts
• What kinds of data is needed to take advantage of these opportunities, and how to collect it
• How Ikechi and colleagues use data and analytics to distinguish between rational and emotional reactions to advertising
• How to drive a culture of experimentation and measurement among colleagues and stakeholders who are more creatively than analytically minded, and much more.

Ikechi on LinkedIn: https://www.linkedin.com/in/ikechi-okoronkwo-0318579/

If you’re anything like me, you have a love/hate relationship with marketing. Marketing can be delightful, obnoxious or somewhere in-between, depending on content and context.

Most of us remember an ad from our youth that has given us a life-long emotional connection to a brand or product. Most of us also remember that obnoxious sales call or email campaign that made us swear never to buy from the offending company again.

In this episode of Leaders of Analytics, you will learn from Ikechi Okoronkwo why data-driven marketers have a leg-up when it comes to designing and executing impactful campaigns that hit the right audiences and create delight.

Ikechi is Executive Director, Managing Partner and Head of Business Intelligence & Analytics at Mindshare. Mindshare is a global media and marketing agency, and part of global marketing powerhouse GroupM.

Listen to this episode to learn:

• What Ikechi sees as the biggest opportunities in data-driven marketing
• What kinds of analytics to invest in to optimise the impact of your marketing efforts
• What kinds of data is needed to take advantage of these opportunities, and how to collect it
• How Ikechi and colleagues use data and analytics to distinguish between rational and emotional reactions to advertising
• How to drive a culture of experimentation and measurement among colleagues and stakeholders who are more creatively than analytically minded, and much more.

Ikechi on LinkedIn: https://www.linkedin.com/in/ikechi-okoronkwo-0318579/

Business leaders are changing.

Today, it’s not enough to be a strategic thinker and good people leader to be successful in the corporate world. Why?

Modern business leaders are customer-centric and understand how to create a personalised customer experience using customer data.

Modern business leaders are data-driven and understand how to make decisions based on probabilistic outcomes, not just gut feel.

Modern business leaders understand what it takes to develop and deploy artificial intelligence in their organisation.

So, how do we educate our future business leaders to be analytics literate, technically capable and able design and use AI effectively and responsibly?

I recently spoke to Professor Hind Benbya to answer this question and many more relating to educating our future business leaders.

Hind is the Head of the Department of Information Systems & Business Analytics at Deakin University, where she leads the strategic direction of the department as well as academic aspects of teaching, research and industry engagement.

In this episode of Leaders of Analytics, you will learn:

• The critical must-learn skills for students wanting to shape the future of business with data and analytics
• The role of data, analytics and AI in business 10 years from now and how today’s business leaders must prepare
• How we bring today’s business leaders and executives up to speed with data and analytics
• How analytics leaders can drive their organisations to become truly data-driven, and much more.

Hind on LinkedIn: https://www.linkedin.com/in/hindbenbya/

Hind's research and publications: https://scholar.google.com/citations?user=KNAW0xsAAAAJ&hl=en

Deakin's Department of Information Systems & Business Analytics: https://www.deakin.edu.au/business/department-of-information-systems-and-business-analytics

Business leaders are changing.

Today, it’s not enough to be a strategic thinker and good people leader to be successful in the corporate world. Why?

Modern business leaders are customer-centric and understand how to create a personalised customer experience using customer data.

Modern business leaders are data-driven and understand how to make decisions based on probabilistic outcomes, not just gut feel.

Modern business leaders understand what it takes to develop and deploy artificial intelligence in their organisation.

So, how do we educate our future business leaders to be analytics literate, technically capable and able design and use AI effectively and responsibly?

I recently spoke to Professor Hind Benbya to answer this question and many more relating to educating our future business leaders.

Hind is the Head of the Department of Information Systems & Business Analytics at Deakin University, where she leads the strategic direction of the department as well as academic aspects of teaching, research and industry engagement.

In this episode of Leaders of Analytics, you will learn:

• The critical must-learn skills for students wanting to shape the future of business with data and analytics
• The role of data, analytics and AI in business 10 years from now and how today’s business leaders must prepare
• How we bring today’s business leaders and executives up to speed with data and analytics
• How analytics leaders can drive their organisations to become truly data-driven, and much more.

Hind on LinkedIn: https://www.linkedin.com/in/hindbenbya/

Hind's research and publications: https://scholar.google.com/citations?user=KNAW0xsAAAAJ&hl=en

Deakin's Department of Information Systems & Business Analytics: https://www.deakin.edu.au/business/department-of-information-systems-and-business-analytics

Most of us take for granted that food is always available to us when we need it. Our local supermarkets have shelves stacked with produce from all corners of the world. Rarely do we stop to think that the items in our shopping carts have been on a long journey involving months of work by many people.

How does all this food get produced in the first place, reliably, consistently and to a high standard? How do we combine and utilise scarce resources to feed billions of people around the world every day?

I recently caught up with Serg Masis to answer these questions and understand how data science is used to optimise food production around the world.

Serg is a Climate & Agronomic Data Scientist at global agriculture company Syngenta and author of the book ‘Interpretable Machine Learning with Python’.

In this episode of Leaders of Analytics, we discuss:

• The biggest challenges facing our global food system and how data science can help solve these
• How data science is used to help the environment
• Why Serg wrote the book ‘Interpretable Machine Learning with Python’ and why we should read it
• How to make models more interpretable, and much more.

Connect with Serg:

Serg's website: https://www.serg.ai/#about-me

Serg on LinkedIn: https://www.linkedin.com/in/smasis/

Serg's books from Packt: https://www.packtpub.com/authors/serg-masis

Most of us take for granted that food is always available to us when we need it. Our local supermarkets have shelves stacked with produce from all corners of the world. Rarely do we stop to think that the items in our shopping carts have been on a long journey involving months of work by many people.

How does all this food get produced in the first place, reliably, consistently and to a high standard? How do we combine and utilise scarce resources to feed billions of people around the world every day?

I recently caught up with Serg Masis to answer these questions and understand how data science is used to optimise food production around the world.

Serg is a Climate & Agronomic Data Scientist at global agriculture company Syngenta and author of the book ‘Interpretable Machine Learning with Python’.

In this episode of Leaders of Analytics, we discuss:

• The biggest challenges facing our global food system and how data science can help solve these
• How data science is used to help the environment
• Why Serg wrote the book ‘Interpretable Machine Learning with Python’ and why we should read it
• How to make models more interpretable, and much more.

Connect with Serg:

Serg's website: https://www.serg.ai/#about-me

Serg on LinkedIn: https://www.linkedin.com/in/smasis/

Serg's books from Packt: https://www.packtpub.com/authors/serg-masis