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    data sources

    Explore " data sources" with insightful episodes like "Ep. 496 - Duck Math and Adventures in Alaska", "Jordan Crawford on Making AI Work for Marketing", "Trading up to a new revenue management vision with Melissa Skluzacek, easyJet", "Dealing With The Different Dimensions Of Data" and "Data As A Single Source Of Truth" from podcasts like ""Ducks Unlimited Podcast", "The Marketer Show", "Airline Voice Radio", "The Power of Data" and "The Power of Data"" and more!

    Episodes (6)

    Ep. 496 - Duck Math and Adventures in Alaska

    Ep. 496 - Duck Math and Adventures in Alaska

    Maddie Lohman, a PhD student from University of Nevada-Reno and 2-time DU research fellow, joins host Mike Brasher to discuss her research on mallards, pintails, and blue-wings in the Prairie Pothole Region. She shares how an initial dislike of math turned into a fascination with quantitative ecology and how she hopes her research will inform conservation. The two also reminisce about their trip to Alaska with friends and colleagues to study black brant on the Yukon Delta National Wildlife Refuge.

     
    www.ducks.org/DUPodcast

    Jordan Crawford on Making AI Work for Marketing

    Jordan Crawford on Making AI Work for Marketing

    In this episode, Jordan Crawford joined to chat about:

    AI in Marketing and Sales

    - AI will significantly change how we think about marketing and sales
    - It is important to experiment with AI tools and find ways to work with them to expand capabilities
    - Both the cost and time to perform tasks with AI have gone to near zero
    - The challenge is asking AI questions that don't include nuance and can't be operationalized
    - To work effectively with AI, we need to break down work into smaller chunks that it can do well

    Using AI Effectively

    - The focus is on how to use GPT Four in processes without worrying about its hallucination problem
    - People who are not reinventing themselves are at risk of being replaced by someone using AI.
    - To use AI effectively, one needs to provide creative constraint and context. Andy Grove's framework of "if the board fired me today, what would my replacement come in and do?" can be useful for thinking about how to use AI.
    - AI is good for operationalizing, but one needs to work backwards and feed it the right inputs and training sets to make it work effectively.
    - The speaker's company uses AI for programmatic outbound campaigns, feeding it website context to determine the top ten data points for targeting customers.
    - Ideas generated by AI include employee turnover rates, gender diversity ratios, and presence of employee research groups.
    - The speaker believes that in order to define prompts, one needs to invert their thinking and break down the process into discrete steps.
    - By breaking down the process and having a clear understanding of the steps involved, the speaker is able to evaluate the AI's suggestions and identify which ideas are good or bad.
    - The speaker recommends dissecting one's process by writing it out on a whiteboard to gain clarity.
    - The speaker has campaigns using AI in a targeted way where they can trust the output.
    - The challenge in automating this is that a wrong result can have high stakes and the pain is too high if it gets it wrong.
    - The speaker is thinking about creatively constraining the automation to ensure that if it gets it wrong, it's a harmless mistake.

    Using Creative Constraints with AI

    - The speaker played around with an AI-generated sentence, which seemed like a human wrote it but was actually a lie, and warns against the weaponization of such technology.
    - Many people consider AI as a productivity hack, but the author thinks that the real opportunity is using it to do things that would have been impossible before.
    - The author has created a product that uses AI to identify the perfect moments for a company to sell their products and services.
    - The author uses AI to write effective sales emails quickly and efficiently, using creative constraints and contextual understanding.
    - This approach can be done at scale and can give companies a significant advantage over competitors who don't have sales teams of similar size.
    - The speaker doesn't trust AI to write a complete email or to act on their behalf. 
    - They believe that AI can't write a great email, except if it's trained on how to write five discrete sentences with specific steps and then summarize the email. 
    - They don't trust AI to handle anything that involves requiring truth. 
    - The speaker thinks the problem with AI is that people don't know how to use it or deploy it effectively, and there is a need to ask the right questions and to refine the process. 
    - The speaker recommends clay.com as a useful tool for refining data by having conversations with ChatGPT on a per-row basis.
    - The speaker has spent a lot of time tinkering with the tool to test its capabilities and come up with use cases.
    - The speaker advises others to play around with the tool and think about what perfect thing involving language they could accomplish with unlimited time, and then consider how AI could help them achieve it.
    - ChatGPT is a tool that can help you break down complex questions and tasks into smaller, discrete steps.
    - The best approach is to ask the tool to give you the smallest possible steps to accomplish a goal, even if someone without context on your business could understand.
    - By following these steps, you can audit them at every point and make sure they are correct.
    - The possibility with ChatGPT is not just to save time but to have a person work on a creative task with nearly unlimited time, energy, and focus.
    - The concept of constraint can help people go deeper and achieve higher output than they normally would.
    - The guest gave an example of a big process they have built using constraint.
    - The guest is asked if there are other examples of their process that have been automated and systematized due to constraint.
    - The speaker has operationalized AI for a specific process, but only for pieces of it so far.
    - They believe that the bar for successful AI implementation is high because it can begin "hallucinating" and making things up when given too much freedom.
    - An example of this is when AI was tasked to build SEO pages for 10,000 companies without creative constraint and started making things up.
    - The speaker believes that AI needs creative constraint and to be broken down into smaller processes to be successful.
    - They are aggressive about killing processes that don't meet their standards and advocate for breaking down tasks into smaller, explicit steps similar to talking to a fifth-grader.

    Trading up to a new revenue management vision with Melissa Skluzacek, easyJet

    Trading up to a new revenue management vision with Melissa Skluzacek, easyJet

    For this new season of Airline Voice Radio, we welcome two new hosts. Transformation pioneers and great storytellers Nancy Delgado and Tye Radcliffe take over the mic to explore the road to high-performance retailing by engaging with industry leaders. In this first episode, Tye talks to Melissa Skluzacek, easyJet’s Director of Trading and Revenue Management.

    Melissa has over 30 years of industry experience and has been with easyJet since January 2020. Her current position is Director of Trading and Revenue Management at the low-cost, UK-based airline. Trading is a British term that speaks to an amplified vision for revenue management. It was that aspect that attracted Melissa to the role. 

    For a more holistic and collaborative approach to revenue optimization, easyJet's trading team implements the pricing and revenue management strategy. Then the team works with other departments to ensure the revenue needle is moving in the right direction. In Melissa's view:

    “Revenue management, digital, merchandising, and distribution are all going to morph into a much more of a combined function."

    With easyJet operating in nearly 1,000 routes, its revenue management department works with an enormous amount of information. Using data models is the only way to handle this sheer volume. Melissa’s advice is that before implementing a data model, the airline should decide what the model needs to accomplish and what it can and cannot do. Most importantly, a data model’s output needs to answer a specific business question. Will data models replace revenue analysts? Not according to Melissa. She advises against basing decisions solely on the model's output. Instead, analysts should view the output as a recommendation that they can approve, reject, or influence.

    In this episode, Melissa and Tye discuss if:

    • Combining search data with competitive fare prices and event data will give revenue analysts a more comprehensive market view.
    • Dynamic pricing has huge revenue implications for airlines as it allows them to reach the customer at a more personal level.
    • Revenue management is a niche field with many nuances and requires specific skills that few vendors have.

    Tune in for more Airline Voice Radio episodes coming soon with insightful airline leaders. Airline Voice Radio is available on your favorite podcast player, such as Spotify, Apple Podcasts, and Google Podcasts.

    Emerging Data Sources – Get a Handle on eDiscovery for Collaboration Tools

    Emerging Data Sources – Get a Handle on eDiscovery for Collaboration Tools

    In the first episode of season four, co-hosts Bill Mariano and Rob Hellewell, introduce themselves and welcome listeners back for a fourth season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution.

    To kick things off, Bill and Rob begin with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this first episode, they dive into a recent story around COVID-19 and the reformation of legal culture

    The guest speaker segment for episode one highlights Ellen Blanchard of T-Mobile. Ellen, Bill, and Rob discuss the growth in emerging data sources, especially with the introduction of more remote work due to COVID-19. They cover tips on how to manage, collect, process, and review collaboration data for ediscovery purposes via the following questions:

    • What has changed over the last couple of years and even in the last few months with COVID-19?
    • How do you get a handle on these data sources?
    • How do you weigh that balance between risks and what teams need to use to be productive?
    • What are some key tips to keep in mind when managing ediscovery around collaboration tools?

    At the end of the episode, Bill recaps key takeaways and thanks Ellen for joining. If you enjoyed the show, join in the conversation on Twitter and discover more about our speakers and the show here.

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    About Law & Candor

    Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here.