Tech for Non-Techies

Conferences are full of speakers saying that the latest tech will change the world, but that often leaves smart people even more confused. Knowing about trends is irrelevant if you don't know what to do about them. To learn how to cut through the tech hype, listen to this episode with Andrew Grill, the Actionable Futurist. Andrew began his career as an engineer, became a Global Managing Partner at IBM and today is a keynote speaker on tech & business trends. Learning notes from this episode: “To understand the technology, you need to play with it,” Andrew says. Using new software or devices at home makes you comfortable with trying new technologies. (e.g. try TikTok! you'll see what an engaging algorithm really feels like and you'll have a laugh) Innovation theatre is a problem if there is no clear understanding why a company has a digital strategy. This is usually a leadership issue, not a tech issue. The job title of Chief Digital Officer or Chief Data Officer is designed to be obsolete in the next few years. As all of our experiences are a mix of digital and analog, having a separate job title for digital will not make sense as companies become more fully integrated. Resources mentioned in this episode: The Pragmatist's Guide To Innovation   ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter.    (Photo provided by Andrew Grill)

To lead in the Digital Age, you need to become a Digital Collaborator. The best way to learn anything quickly is to put yourself in a situation where not doing it isn’t an option. Listen to this episode to learn what you can do to start collaborating with tech teams and take your career to the next level. Learning notes from this episode: If you work in a corporate, set up a weekly meeting with technologists and your team to discuss what they’re working on and how it impacts scale, efficiency, and customer satisfaction. This public commitment to collaboration removes your choice to delay. For example, if you work in marketing, set up regular meeting with the data science team and begin by outlining your goals for the year and where you see the biggest bottle necks. While the data science team might not have solutions right away, this will lay the foundations for future collaboration.  Another way to do become a Digital Collaborator is to volunteer with a tech start-up. You could join as an advisor to share your expertise and network, in exchange for sitting in on product meetings and learning.  If you’re not yet at the level where your expertise or network are coveted by a start-up, just volunteer your time. You can help manage their events, social media or help them with customer service. In exchange, say that you want to sit in on a product meeting, or have a 30 minute meeting per week with the head of product or the CTO to ask them questions.  Read Sophia's Harvard Business Review article: Coding Isn’t a Necessary Leadership Skill — But Digital Literacy Is Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.  ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter.  (Photo by LinkedIn Sales Solutions on Unsplash)

Some problems that annoy you daily could be solved by AI, but most business teams don't know that because they’ve never discussed them with a technologist. Listen to this episode with Dr Catherine Breslin, a machine learning scientist with a PhD from Cambridge, to learn how to make the most of the AI revolution. Dr Breslin was one of the first people to work on Amazon Alexa and today leaders Kingfisher Labs, a consulting company. Learning notes from this episode: For AI to have the biggest impact, data scientists need the input of domain experts, who are usually non-techies. To collaborate successfully with a data scientist, Dr Breslin suggests that non-technical teams bring their business wish list to a data scientist. Some of the items will probably be easily solved by technology, while others will not. Having regular discussions between tech teams and business teams will widen your scope of what’s possible. Buying data to build models is a significant cost, which needs to be built into estimates for a data science project. The three factors that influence how effective voice technology can be are language, subject, accent. Voice AI is effective for simple every-day tasks like “what’s the weather today?” in a language spoken by lots of people, but often struggles with specialist subject areas or smaller languages. Voice technology is most effective for the “big’ languages: English, Mandarin and Spanish. Resources mentioned in this episode: Dr Catherine Breslin on Twitter What data scientists do and how to work with them The Business of AI with Harvard Business School Prof Marco Iansiti AI, visual search & entrepreneurship with Jenny Griffiths MBE Book one of the 10 free coaching slots with Sophia here. This is only available in July 2022. ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter. 

To become SMART MONEY as an investor, founder or corporate innovator, you have to know what questions to ask about a product. This helps you spot signs of early success or early warning.  Listen to this episode to learn what questions to ask and how to link product innovation to business strategy.  Learning notes from this episode: The questions fall into three buckets: How do my best customers behave? What are the characteristics of my best customers? What has to happen for them to abandon the product? For bucket 1, you could ask: What features do my most active users use? What screens do they visit? How often do they open the app? What time of day do they open it and on which days? For bucket 2, you could ask: Where did these customers come from? What are their demographics? Are there any patterns? For bucket 3, you could ask: What screens tend to be the last screen that people get to before they shut down the app? What prices of other apps they use have? Resources mentioned in this episode: Tech for Non-Techies podcast: What on Earth is growth hacking? Book: How today’s fastest growing companies drive breakout success Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.  ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter. 

Even the smartest professionals who don’t have backgrounds in digital businesses make the same mistakes when it comes to tech start-ups. They often want vanity metrics, as opposed to what truly matters, and because they don’t know how a tech product gets made, they don’t know how to properly evaluate an opportunity.  In this episode you'll learn 3 core tech concepts and how they apply to early stage investing. Learning notes: There are fundamental differences between software products, that are especially important at the early stages. This is because, when a product is very new, it is still in development mode. This is why understanding product development is vital at the early stages. For example, evaluating Airbnb as a listed company focusses on typical investment metrics: revenues, costs, growth etc. These would have been unavailable when Airbnb first launched, so investors must look for other signs. Tech products are always evolving. For example, YouTube started as dating site. Its evolution was not an act of randomness, but a series of product and growth experiments.  Product metrics are not business metrics, and they change over time. Traditional investors are used to putting business metrics into Discounted Cashflow Statements. This system does not work in early stage tech start-ups.  Marketing is part of product development. Growth is part of the discovery process, and the growth hacker and product manager are often the same person in an early stage business. This means investors need to know how to include marketing spend in product development cost. Resources mentioned in this episode: How I got into deep tech investing (with Colin Beirne, Two Sigma Ventures) How to burn $2 billion To learn more, join the Introduction To Tech For Angel investors course You will learn: Core differences between tech & traditional businesses Which metrics are important at which stage Who does what on a product team How much different stages of development cost ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter. 

Listen to what happened when Apple forgot a key market and how to avoid the same mistake. When product teams consist of entirely white males, they make products for white males. When non-technical professionals learn to Speak Tech, you get better products, happier customers & better profits. Learning notes from this episode: While there are plenty of programs to get minorities into STEM, they will take years to have an effect. In the next few decades, most developers will continue to be white males. To prevent baking unconscious bias into products, the simplest, cheapest and fastest way is to teach non-technical teams how to work with the techies.  Bringing diverse voices into product development is not a moral issue; it is capitalist self-interest. E.g. if women are not involved in product innovation, companies can lose up to 50% market share.  To get Sophia's monthly business update, register here.    ----- Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.  ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter.   

"One of the most common types of advice we give at Y Combinator is to do things that don't scale," says Paul Graham, Y Combinator founder. Recruiting users manually and getting feedback is what lets you build a scalable product. Learning notes from this episode: "The most common unscalable thing founders have to do at the start is to recruit users manually. Nearly all startups have to. You can't wait for users to come to you. You have to go out and get them." - Paul Graham A product is always a solution to a problem someone is experiencing. The better you understand the problem and the users, the better the product will be. This often means 1:1 conversations with your customers. This advice doesn't only apply to early stage start-ups. If you are creating products, you are always looking for customer feedback to make them better. Brian Chesky still books Airbnbs so he can experience his product as a customer. Resources mentioned in this episode: Do things that don't scale - essay by Paul Graham Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.  ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter. 

“There are things that are much more important about investing in technology companies than technology,” says Colin Beirne, Founder of Two Sigma Ventures. TSV has invested in around 100 start-ups over the last 10 years, and funded 10 unicorns. They’re part of Two Sigma, a hedge fund with more than $60 billion under management. Colin is surrounded by data scientists and programmers, but doesn’t have a background in programming. Listen to this episode to hear how Colin went from a liberal arts college to becoming one of the world’s leading deep tech investors. Learning notes from this episode: “The winning company is not always the one with the best technology. Tech can be a differentiator, but usually it’s only temporary. The job of a venture capitalist is not to figure out which company has the best tech. It’s to figure out which company has the best business that can ultimately be the biggest impact,” says Colin. Data science and knowing how to analyse data to spot trends is domain agnostic. This is why you often see data scientists changing jobs from completely different fields, such as going from insurance to social media.  Companies across industries can and do use data analysis to make better decisions at scale. Media companies do this when serving us content and advertising, and investment firms do this to decide which companies to invest in. To decide whether joining a start-up is a good idea, evaluate the founders: do you think they have the ability to grow a successful business? Resources mentioned in this episode: Tech for Non-Techies podcast: Lessons from the Netflix C Suite  Tech for Non-Techies podcast: The Business of AI with Harvard Business School Prof Marco Iansiti Book: Competing in the Age of AI Strategy and Leadership When Algorithms and Networks Run the World  Book: How Generalists Triumph in a Specialized World   Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.  ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter. 

Real estate marketplace Zillow took $500 million in write downs and fired 25% of its workforce in late 2021, largely because a pricing algorithm made a mistake. Learn what went wrong and how to avoid it. Learning notes from this episode: Zillow started life as an online marketplace for real-estate in 2005, and monetised via advertising. The company decided to diversity and get into the business of flipping houses. Zillow used an algorithm to find properties it believed were undervalued and bought them.  When the housing market turned, Zillow was left with massive losses, but its competitors were not. Behind every algorithm is a set of assumptions made by humans. For example, factors like crime rates and commuting distances affect real estate prices and would go into a property pricing algorithm. Machine learning models often assume that the past equals the future, but that is generally not the case in the real world. When the economy changed, the Zillow algorithm did not adjust. Data scientist Prof Datta from Carnegie Mellon says that tools can be built to monitor whether an algorithm is accurate or not. In essence: create a tool to monitor another tool. Non-technical leaders can also participate: ask your tech colleagues how the model is being updated when circumstances change. Simply asking: "the economy is changing. Have we adjusted our pricing algorithm for these changes? How have we done it?" is a good start. Resources mentioned in this episode: Tech for Non-Techies podcast: Intro to Algorithms and Big Data Inside Big Data: The $500mm+ Debacle at Zillow Offers – What Went Wrong with the AI Models? Sign up for How To SPEAK TECH for Leaders (FREE class) ----- If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter. 

AI is a great tool to help you make decisions, but it's often not sophisticated enough to make good decisions by itself. This is why companies often rely on AI to do  most of the task, but leave the final decision to humans.  Most tech initiatives fit into one of these three buckets: Reach scale Increase efficiency Increase customer satisfaction Fashion retailer Stitch Fix uses a stylist algorithm to select outfits to send to customers, but the final selection is made by human stylists. The Netflix content team uses an algorithm to get suggestions on how much to pay for new shows, but ultimately the final decision rests with them (and isn't always the what the AI suggests). If you like learning about how tech products and profits get made, you'll like our newsletter. It's funny too. Sign up here. ----- There are 2 ways to apply this work to your goals: For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership. For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.  BOOK A CALL to discuss bespoke training & consulting. We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on info@techfornontechies.co   Say hi to Sophia on Twitter and follow her on LinkedIn. Following us on Facebook, Instagram and TikTok will make you smarter.