Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

In the world of data analytics, there are few that have achieved as much as Bora Arslan, who joined us for this week’s podcast. Arslan has driven data transformation exercises across some of the largest organisations in the world. These organisations include Walmart and Ford in the US, and IAG here in Australia.

On the podcast, Arslan shares many insights from his time as a Chief Data Officer. From his strategies for getting organisational buy-in for transformation, to the ways in which he prefers to build and manage teams, Arslan provides us with a blueprint for how the modern data executive should look at the work that they do.

One of the key messages that Arslan shares is that data analytics executives need to get as close to the organisation as possible. If they report to the CIO and their team is nested within IT, they’ll be seen as a support function, rather than a strategic one. The closer the Chief Data Officer can get to other lines of business and the CEO, the better they can understand the needs of the business and develop strategic and transformative solutions in direct collaboration with the other key stakeholders. 

The challenge is that to be able to do this, the data team needs to learn how to speak the language of the other executives and lines of business. This has been one of the key reasons for Arslan’s ongoing success in his own roles. 

Tune in to hear more great insights from one of the real thought leaders in our space!

Thank you to our sponsor, Talent Insights Group! 

Connect with Bora: https://www.linkedin.com/in/bora-arslan/

Hear more from Bora and our awesome speaker faculty at Advancing AI Melbourne: https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

What we discussed

0:00  - Introduction

3:45 – Bora explains his background and what the last eight years in various executive roles has been like.

8:36 – How to define the role of a chief data officer in a large enterprise?

13:13 – What leaders can do to lead change management across the organisation and bring people on the transformation journey.

15:58 – How data analytics heads benefit from direct interaction with the CEO and executive team, rather than being a support function to the CIO.

18:46 – The most effective ways Chief Data Officers can influence C-level executives around them.

21:21 – On building teams: What are the most effective ways to structure data teams?

23:29 – The most effective ways to optimise project delivery, and the value of having a project management team within the organisation.

26:30 – Should the change management function sit within the data analytics team, or should it be more centralised within the business lines?

28:03 – A summary of the processes and methodologies key to driving successful analytical functions.

32:40 – Looking forward: The technologies to look forward to in the next year or two.

35:57 – Bora shares his career highlights to date.

This week in the Data Futurology podcast, we have a special presentation to share. Ben Taylor, the Assistant Commissioner for Data Insights at the ATO was one of the leading keynote speakers at our recent OpsWorld event in Sydney. There, he provided delegates with a deep dive into the data journey for the ATO in recent years. 

As you can probably guess, the ATO handles millions of lines of data every day, across data lakes that are petabytes in size. With a data team of around 800, there is often the sense that they’re racing against chaos to deliver. However, in recent years, the effort to transform and modernise the approach to data has been highly successful. The ATO was able to transition to cloud-driven data systems, and is now seen as a deep and strategic partner to the other lines of business within the organisation. 

In this presentation, Taylor shares some open and transparent examples of the challenges that the ATO faced, the steps that they took to embrace AI and automated analytics while maintaining human oversight and decision-making, and how the data team went about building trust to earn the support of the other lines of business. 

He also overviews the value of XOps – what that means from the ATO’s perspective – and why all data leaders should be looking at defining and adopting a XOps approach to their own data strategy. 

For deep insights into one of the largest data-driven organisations in Australia, Taylor’s presentation on the ATO’s experience with data is essential.

Connect with Ben Taylor:  https://www.linkedin.com/in/ben-taylor-962a2a60/?originalSubdomain=au

Joins us for our next event Advancing AI Melbourne https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community:https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

2:17: Introduction to Ben Taylor’s presentation.

7:06: Taylor introduces himself and provides the historical context for the ATO’s approach to analytics.

12:53: Taylor describes the state of the ATO’s data environment eight years ago, and overviews the transformation project to modernise it.

14:24: Taylor describes some of the challenges that the ATO found with centralising the data and analytics function.

16:42: XOps in the ATO – what challenges led to the ATO approaching data this way, and what impact did it have?

18:03: What, exactly, does “XOps” mean to the ATO? Ben shares his insights on the conversation. 

19:27: Taylor shares an example of what XOps looks like in action at the ATO.

23:45: How did the ATO avoid becoming too process heavy, as Government agencies can at times become?

27:13: How can teams handle the sense of “chaos” that comes from increasing demands from lines of business, while also managing the legacy tech debt?

29:13: Q & A with Taylor from the audience.

“At the ATO, we see data as the third note of a triad between business, technology, and data.

“What exactly is XOps? Honestly, we've spent a lot of time asking ourselves the same question. If you go out there and try to find someone who can tell you what XOps is, you won't find it… although I'm sure you'll find a few consultants that will sell you an answer for a few $100,000.”

This week in the Data Futurology podcast, we have a special presentation to share. Ben Taylor, the Assistant Commissioner for Data Insights at the ATO was one of the leading keynote speakers at our recent OpsWorld event in Sydney. There, he provided delegates with a deep dive into the data journey for the ATO in recent years. 

As you can probably guess, the ATO handles millions of lines of data every day, across data lakes that are petabytes in size. With a data team of around 800, there is often the sense that they’re racing against chaos to deliver. However, in recent years, the effort to transform and modernise the approach to data has been highly successful. The ATO was able to transition to cloud-driven data systems, and is now seen as a deep and strategic partner to the other lines of business within the organisation. 

In this presentation, Taylor shares some open and transparent examples of the challenges that the ATO faced, the steps that they took to embrace AI and automated analytics while maintaining human oversight and decision-making, and how the data team went about building trust to earn the support of the other lines of business. 

He also overviews the value of XOps – what that means from the ATO’s perspective – and why all data leaders should be looking at defining and adopting a XOps approach to their own data strategy. 

For deep insights into one of the largest data-driven organisations in Australia, Taylor’s presentation on the ATO’s experience with data is essential.

Connect with Ben Taylor:  https://www.linkedin.com/in/ben-taylor-962a2a60/?originalSubdomain=au

Joins us for our next event Advancing AI Melbourne https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

The future of AI is dynamic and multi-faceted. In this episode of the Data Futurology podcast, we are thrilled to welcome Nikita Atkins, the Artificial Intelligence Executive at NCS Australia. With NCS being one of the leading voices in AI, both in the APAC region and globally, Nikita has more than a few insights to share about the future of the technology and its most exciting use cases. 

We start by talking about low code/no code and how, by embracing that and enhancing it with AI, an organisation can shift their data science team away from “run-rate” models and tasks to instead focus on the highest value items. 

From there, we talk about data cleaning and pipelines, before moving on to some of the exciting innovations that are coming to the AI space – how will AI assist in rebuilding digital trust after so many high-profile cyber breaches have shaken the confidence of Australian consumers? How can AI play a role in enhancing the sustainability credentials of organisations? And what are new concepts like AI ops and Explainable AI, and how is NCS set up to be a pioneer in this space?

This is a far-reaching and in-depth interview, you’ll get a good sense of how organisations will be transforming their AI environments in the years ahead.

Don’t forget!  NCS will be at the Data Futurology Advancing AI conference in Melbourne in May. Be sure to come up and speak to Nikita and his team!

Connect with Nikita: https://www.linkedin.com/in/nikitaatkins/

Learn more about NCS: https://www.ncs.co

See NCS at Advancing AI Melbourne: https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

00:00 Introducing Nikita Atkins and the topics for the podcast.

1:04 Nikita’s background, his role at NCS, and a company overview.

4:16 On the topic of generative AI – what’s behind the interest and excitement in this area?

5:43 How generative AI tools can be effectively used in the enterprise.

9:46 On the subject of AI and low code/no code – how can organisations implement AI in a way that can enhance this area?

12:20 What should organisations be thinking about in terms of governance or deployment challenges with regard to low code/no code?

15:20 In terms of data cleansing, do we get better outcomes from better quality data and better structured model data?

18:36 Data pipelines are a critical need for any business working with data – what role does automation have to play?

23:15 The advantages of standardising data collection.

25:56 The emergence of and benefits behind AI ops.

29:36 NCS and sustainability – how can data be part of the solution?

35:17 Digital trust – in the wake of so many cyber breaches, what can enterprises do to earn the respect of customers back?

38:05 The concept of Explainable AI – what is it, and why is it a focus for NCS?

This week in the Data Futurology podcast, we have a special presentation to share. Ben Taylor, the Assistant Commissioner for Data Insights at the ATO was one of the leading keynote speakers at our recent OpsWorld event in Sydney. There, he provided delegates with a deep dive into the data journey for the ATO in recent years. 

As you can probably guess, the ATO handles millions of lines of data every day, across data lakes that are petabytes in size. With a data team of around 800, there is often the sense that they’re racing against chaos to deliver. However, in recent years, the effort to transform and modernise the approach to data has been highly successful. The ATO was able to transition to cloud-driven data systems, and is now seen as a deep and strategic partner to the other lines of business within the organisation. 

In this presentation, Taylor shares some open and transparent examples of the challenges that the ATO faced, the steps that they took to embrace AI and automated analytics while maintaining human oversight and decision-making, and how the data team went about building trust to earn the support of the other lines of business. 

He also overviews the value of XOps – what that means from the ATO’s perspective – and why all data leaders should be looking at defining and adopting a XOps approach to their own data strategy. 

For deep insights into one of the largest data-driven organisations in Australia, Taylor’s presentation on the ATO’s experience with data is essential.

Connect with Ben Taylor:  https://www.linkedin.com/in/ben-taylor-962a2a60/?originalSubdomain=au

Joins us for our next event Advancing AI Melbourne https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

2:17: Introduction to Ben Taylor’s presentation.

7:06: Taylor introduces himself and provides the historical context for the ATO’s approach to analytics.

12:53: Taylor describes the state of the ATO’s data environment eight years ago, and overviews the transformation project to modernise it.

14:24: Taylor describes some of the challenges that the ATO found with centralising the data and analytics function.

16:42: XOps in the ATO – what challenges led to the ATO approaching data this way, and what impact did it have?

18:03: What, exactly, does “XOps” mean to the ATO? Ben shares his insights on the conversation. 

19:27: Taylor shares an example of what XOps looks like in action at the ATO.

23:45: How did the ATO avoid becoming too process heavy, as Government agencies can at times become?

27:13: How can teams handle the sense of “chaos” that comes from increasing demands from lines of business, while also managing the legacy tech debt?

29:13: Q & A with Taylor from the audience.

This week’s guest is a true veteran of the data industry (and one of the first people we interviewed on the Data Futurology podcast!). Sandra Hogan has some of the deepest and most experienced views on how data teams can effectively engage with their organisations. Fifteen years ago, she was the Director of Customer Intelligence at Telstra, and in the years since she has seen data grow as a priority, and the status of data teams within those organisations that look to take a disruptive and leadership position in the market increase in-kind.

Sandra is now the Co-Founder and Data Analytics Lead of Amperfii, an organisation that provides analytics that helps data teams measure and articulate their value back to the organisation. In this podcast, she shares insights on how she has managed teams and encouraged their deeper participation in the organisation. 

Sandra also talks about how data teams can be motivated, where they should be focusing their energies within increasingly busy organisations. She discusses how critical it is for data teams to be involved as early into the process as possible.

“You need to pick the areas where you say ‘okay, these are the big strategic things, and these are the pieces of work that I actually think really make a difference to the business,’ and focus on them,” Sandra explained in the podcast. “Even if it's only 20, or 30 percent of what you do, it's going to actually be a lot more than what you're trying to show otherwise.”

To hear more from Sandra, we are privileged to have her speaking at our Advancing AI conference in Melbourne. Click here for more information and to register to attend what will be an insightful and thought-provoking event in Melbourne, from May 3-4.

Thank you to our sponsor Talent Insights Group!

Connect with Sandra: https://www.linkedin.com/in/sandra-hogan-9409421/

Learn more about Amperfii: https://www.amperfii.com/

Join Sandra at Advancing AI Melbourne: https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

0:00: Introduction

2:16 Reflecting on Sandra’s experience in the industry, including lessons learned in analytics and leadership.

09:51: What are the drivers and motivators that are behind the dynamics within analytics teams at the moment?

15:32: What are the main hurdles and challenges that data teams face when aiming to maximise their impact on the organisation?

25:33: How can data teams become more involved earlier in the process, and why is this important for outcomes and team motivation?

34:15: How can organisations prove and track the value of the analytics team?

40:21: Why a “conga line” is a great analogy for the role of data teams.

43:45: Why being able to capture and articulate the value of projects is so critical to data teams.

46:02: Conclusion and final thoughts.

For our milestone 200th Data Futurology podcast, we have the immense fortune of being able to host Gina Papush, the former Global Chief Data & Analytics Officer of wellness and insurance company, Cigna.

Papush has a long history in data science, having been involved in modelling and coding from before the time where “data scientist” was a defined role. In the years since, she has observed that enterprises have become siloed across computer science, data science, and other roles, and that the next stage of data science evolution now is to now break those silos down and find ways to bring cohesion across the organisation.

She has also seen the role of the CDO and their remit evolve, from one that focused on governance and controls, to being a value creator within the organisation. Being an effective agent for change has been important to that evolution, she says on the podcast, and data executives need to look to the “blind spots” that they might have. Many have the technical skills to excel in analytics, but building skills in influence and thought leadership, and to be a partner to the other stakeholders of the organisation, is the next critical step for the CDO.

Finally, Papush also shares her insights on how value is extracted from data. A “one size fits all” approach cannot work, she says, and organisations need to build their strategies based on the maturity of their own data practice, rather than the hype in the market.

Once the maturity is there, she says, data scientists can start looking at real life-changing innovation. “It’s (data) a huge part of how we move healthcare to be more preventive and more interactive,” she said. “Health is currently very event driven. But analytics and AI could make it much more seamless and unlock real-time care.”

Tune in to the full podcast for more of Papush’s thoughts on the history and future of data science.

Thank you to you our sponsor, Talent Insights Group!

Join us for one of our upcoming events: https://www.datafuturology.com/events

Join our Slack Community: https://hubs.li/Q01gKNBn0

This week on the Data Futurology podcast, we have a special guest, Eliud Polanco, to talk about an innovative approach to data management and access. This approach promises to make models and the management of data more reliable and secure.

Polanco, who is the president of Fluree, looks to a blockchain-driven future for data, where data blocks sit on the ledger, and the ability to access and modify them is based on a zero trust approach.

This unlocks innovation, Polanco says on the podcast, allowing organisations and individuals to take greater control over data, and do so in a more efficient manner. He points to GDPR regulations as a good example of where this approach can help. Currently, GDPR regulations require a lot of paperwork, but it’s inefficient and often ignored by both consumers and organisations. However, through a blockchain-based, decentralised approach to data management, a person’s right to control their data can be enhanced, but in such a way that the organisation can also manage the data more efficiently and effectively.

Polanco also provides an excellent potential use case in the financial services space. Financial services have strict regulatory requirements to monitor for money laundering and other illegal activities. However, that can be difficult to do based on data privacy and other regulations. In the example Polanco gives, it is difficult for a US financial services organisation to monitor transactions with Singapore, because US organisations can’t easily get access to Singaporean financial data.

However, this decentralised approach opens up the opportunity to have automation query data and return answers without the agent ever needing to see or touch the data. Suddenly it becomes possible to note a transaction without seeing the data of the transaction itself.

Enjoy this in-depth and nuanced discussion about one of the more exciting innovations on the data horizon.

Connect with Eliud Polanco: https://www.linkedin.com/in/eliud-polanco-977529131/

Contact Fluree: https://flur.ee/contact/

Read Fluree's Whitepaper on Data-Centric Architecture: https://flur.ee/wp-content/uploads/2023/01/Data-Centric-Technology-Architecture.pdf

Thank you to our podcast sponsor, Talent Insights Group!

Join us in Sydney for OpsWorld: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

This week’s guest on the Data Futurology podcast is a 30-year veteran of technology, across many different segments and roles. Nastaran Bisheban, now CTO of KFC in Canada, has previously held roles at Rakuten Kobo, Canadian Tire, and RIM. She additionally sits on the Board of Directors for the CIO Association of Canada.

One of the biggest changes that have occurred over the course of Nastaran’s career is the deeper integration of technology roles into the broader business. As she explains in the interview, Nastaran completed an MBA at Harvard Business School because her role has become an even 50/50 split between managing technology and interacting strategically with the rest of the C-suite and groups within the business. Having that broader understanding of business has been enormously valuable to her career.

Beyond that, Felipe and Nastaran discuss the role that AI and machine learning is playing in KFC Canada’s operation, how executives are encouraged to spend time “on the floor” in restaurants to learn the day-to-day challenges in operation, and how the company is looking to align its business strategy and data practice to drive growth across the operation.

Ultimately, as Nastaran stressed, technology is there to support the human element of the company. Technology that is used to help identify blind spots or notice trends that can be addressed, is an example of technology that has been deployed effectively. For instance, KFC Canada recently completed a significant transformation project to allow for all the delivery and ordering apps to integrate into its systems. It was Nastaran and her team’s human-centric approach to the application of that technology that allowed the project to succeed.

Enjoy this in-depth and insightful podcast!

Thank you to our sponsor, Talent Insights Group!

Connect with Nastaran Bisheban, Chief Technology Officer at KFC Canada: https://www.linkedin.com/in/nastaranb/

Join us in Sydney for OpsWorld: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

What we discussed:

00:00 Why you need to follow the problem (opening quote)

03:17 Nastaran shares her role and remit at KFC.

04:41 What is Nastaran’s vision for a data driven enterprise in her role as a CTO?

05:47 “Following the data” – what are the projects that KFC has undertaken with this mission in mind?

09:18 How data can be collected as an asset, but become a liability.

10:41 How AI and machine learning is being leveraged to unlock innovation at KFC Canada.

13:09 Is there a point in a technologist’s career where they make the transition to focusing more on the human side of technology?

16:55 How KFC Canada is looking to align the business strategy and data practice to drive growth through the organisation.

20:06 What makes a good CTO?

23:14 What should a technologist do to learn about the business, outside of the technology?

25:37 How organisations can prepare technical people for business roles.

28:13 How an organisation of the scale of KFC Canada looks to balance out the need for innovation with the need for stability.

31:27  Clearing technical debt is important, but how can a technology team determine what areas to focus on first?

32:49 How Nastaran and her team overcomes resistance and gets buy-in to their projects.

34:44 How KFC Canada built and managed its technical team culture.

In this latest episode, Felipe takes an in-depth look at the strategy and tactics behind AI and modelling, and looks at where organisations might be driving through the year.

One of the first things to understand is the difference between tactics and strategy. Strategy is the broad view – the understanding of where the organisation wants to be, while tactics form the pathway on how to get there. Too often organisations mix tactics and strategy up, and allow a narrow focus to dominate their approach to data, models and AI.

By looking at the big picture, 2023 will see an explosion in the number of models that are created, and the proliferation of AI and machine learning across the enterprise. Currently, the focus is on a small team of data scientists creating models of high value, but the future will see the number of models being created balloon out to thousands, driven by AI across the organisation.

There will also be an ongoing trend that more people across the organisation develop a basic understanding of models and AI, so they can deploy and monitor these models within their own teams. The question then becomes what does this mean to the data scientists? As we discuss, the role of data scientists will remain as critical as ever in creating those big-value, transformative models and managing the change management across the organisation. Indeed, as teams are increasingly able to create the smaller models for themselves, the role of the data science team as disruptive innovators is only going to become greater.

Tune into the podcast for these insights, and many more.

Thank you to our sponsor, Talent Insights Group!

Join us in Sydney for OpsWorld: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

What We Discussed:

00:00 Welcome to Data Futurology

02:34 The one-line summary of what a data analytics and AI strategy is.

05:19 Thoughts on the growth of data models. Currently, organisations have a small number of models in production, but the future will see organisations running with thousands of models in production.

7:51 The way that I like to apply automated machine learning solutions – as a first pass of models and a first benchmark before deploying something at scale.

9:26 The two “extreme” approaches to creating AI in organisations and kickstarting the journey towards deriving value from them.

 Quotes: