Lean Startups: A Success Blueprint for Early-Stage Entrepreneurs

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The document discusses the lean startup methodology for early-stage entrepreneurs. It emphasizes that most startups fail because they build products that do not solve real problems or meet customer needs, rather than due to technical problems. The lean startup approach advocates validating ideas with customers early through minimum viable products and iterative customer feedback, rather than fully developing products without customer input. It provides tips for entrepreneurs such as finding problems worth solving, deeply understanding customers, launching when a product provides value, and continuously learning and adapting plans based on measuring real-world usage and feedback.

Technologie Business Économie & finance

Lean Startups

A Success Blueprint for Early-Stage Entrepreneurs

Abby Fichtner

@HackerChick
Harvard Innovation Lab

“Considering the incredible amount of human energy, passion,
and creativity that we invest in creating new products & services…

@HackerChick

@EricRies

… it’s a terrible waste that so many of them fail.”

@HackerChick

@EricRies

9 out of 10
new products

fail

@HackerChick

“Most technology start-ups fail not because the
technology doesn’t work, but because they’re making
something that there is not a real market for”

@HackerChick

@EricRies

Single Biggest Predictor of Failure?

@HackerChick

Don Sull, "The Upside of Turbulence”

Single Biggest Predictor of Failure?

Sticking to Initial Business Plan

@HackerChick

Don Sull, "The Upside of Turbulence”

Promise of the Lean Startup
Instead of building our startups according to myths
We can guide them with facts & knowledge

@HackerChick

@EricRies

Startups are NOT small versions
of large organizations

@HackerChick

@HackerChick

Andrew Mason, CEO of Groupon (NY Tech Meetup)

you‘re way too

dumb

to figure out whether your

idea

@HackerChick

is

good

Andrew Mason, CEO of Groupon (NY Tech Meetup)

Thinking ‘Bout Your Startup

• Can I Make Money From It?
• Can I Get People to Know About It?
• Can I Build It?

@HackerChick

Thinking ‘Bout Your Startup

• Can I Build It?
• Can I Get People to Know About It?
• Can I Make Money From It?

@HackerChick

IDEAS

Learn

Build

Measure

Get Through The Whole Loop as
FAST as POSSIBLE
@HackerChick

Guesses

Learn

DO

Measure

Get Through The Whole Loop as
FAST as POSSIBLE
@HackerChick

The unit of progress for entrepreneurs…

learning
not

execution

@HackerChick

Idea to Launch
•

Find a problem worth solving

•

Know your customer

•

Find a solution that resonates

•

Launch when you have a quantum of utility

@HackerChick

Step #1
Find a

problem
worth solving

@HackerChick

We had an idea for a new product.
We went off & built it, put it on our website.

not a single person clicked thru

What did we learn
from that?
@HackerChick

We had an idea for a new product.
We went off & built it, put it on our website.

not a single person clicked thru

Was there a faster
way to learn that?
@HackerChick

How do you get

people

to your

@HackerChick

site

?

Step #2
know your

customer

@HackerChick

It’s just as important to develop our
customers as our product

@HackerChick

Lean Startup
Product

Customers

Agile Development

Customer Development

@HackerChick

Customer Discovery

What is the problem?
Who has the problem?
@HackerChick

@SGBlank

Customer Discovery

How important is the problem’s solution to the customer?
How valuable is the problem’s solution to the customer?
@SGBlank
@HackerChick

What are you doing to solve
this problem today?

@HackerChick

Step #3
Find a

solution
that resonates

@HackerChick

(MVP)

Minimum Viable Product

@HackerChick

Concierge Service
(AKA Wizard of Oz)

Boston Startup School - @HackerChick
@HackerChick

Product/Market Fit
“In a great market – a market with lots of real
potential customers – the market pulls product
out of the startup.”
- Marc Andreessen

@HackerChick

Step #4

launch!
when you have a

quantum of utility
@HackerChick

@paulg, Y Combinator

Guesses to Validate
• Can I Make Money From It?
• Can I Get People to Know About It?
• Can I Build It?

@HackerChick

•

Find a problem worth solving

•

Know your customer

•

Find a solution that resonates

•

Launch when you have a quantum of utility

@HackerChick

Learn More
Eric Ries
@EricRies
http://startuplessonslearned.com/

Steve Blank
@sgblank
http://steveblank.com/

Ash Maurya
@ashmaurya
http://ashmaurya.com/

Abby Fichtner

@HackerChick
http://HackerChick.com

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

Artificial Intelligence: Facts and Myths

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Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia

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Sara Mae O’Brien Scott and Tatiana Baquero Cakici, Senior Consultants at Enterprise Knowledge (EK), presented “AI Fast Track to Search-Focused AI Solutions” at the Information Architecture Conference (IAC24) that took place on April 11, 2024 in Seattle, WA. In their presentation, O’Brien-Scott and Cakici focused on what Enterprise AI is, why it is important, and what it takes to empower organizations to get started on a search-based AI journey and stay on track. The presentation explored the complexities of enterprise search challenges and how IA principles can be leveraged to provide AI solutions through the use of a semantic layer. O’Brien-Scott and Cakici showcased a case study where a taxonomy, an ontology, and a knowledge graph were used to structure content at a healthcare workforce solutions organization, providing personalized content recommendations and increasing content findability. In this session, participants gained insights about the following: Most common types of AI categories and use cases; Recommended steps to design and implement taxonomies and ontologies, ensuring they evolve effectively and support the organization’s search objectives; Taxonomy and ontology design considerations and best practices; Real-world AI applications that illustrated the value of taxonomies, ontologies, and knowledge graphs; and Tools, roles, and skills to design and implement AI-powered search solutions.

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Explore 'The Codex of Business: Writing Software for Real-World Solutions,' a compelling SlideShare presentation that delves into digital transformation in healthcare. Discover through a detailed case study how Agile methodologies empower healthcare providers to develop, iterate, and refine digital solutions that address real-world challenges. Learn how strategic planning, user feedback, and continuous improvement drive success in deploying technologies that enhance patient care and operational efficiency. Ideal for healthcare professionals, IT specialists, and digital transformation advocates seeking actionable insights and practical examples of technology making a real difference.

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Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

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Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Safe Software

Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

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Lean Startups: A Success Blueprint for Early-Stage Entrepreneurs

1. Lean Startups A Success Blueprint for Early-Stage Entrepreneurs Abby Fichtner @HackerChick Harvard Innovation Lab

2. @HackerChick

3. What’s your idea @HackerChick ?

4. “Considering the incredible amount of human energy, passion, and creativity that we invest in creating new products & services… @HackerChick @EricRies

5. … it’s a terrible waste that so many of them fail.” @HackerChick @EricRies

6. 9 out of 10 new products fail @HackerChick

7. “Most technology start-ups fail not because the technology doesn’t work, but because they’re making something that there is not a real market for” @HackerChick @EricRies

8. Single Biggest Predictor of Failure? @HackerChick Don Sull, "The Upside of Turbulence”

9. Single Biggest Predictor of Failure? Sticking to Initial Business Plan @HackerChick Don Sull, "The Upside of Turbulence”

10. @HackerChick

11. Promise of the Lean Startup Instead of building our startups according to myths We can guide them with facts & knowledge @HackerChick @EricRies

12. @HackerChick

13. Startups are NOT small versions of large organizations @HackerChick

14. @HackerChick

15. validate before building @HackerChick

16. VISION @HackerChick BUILD

17. VISION @HackerChick BUILD

18. VISION @HackerChick BUILD

19. VISION @HackerChick BUILD

20. VISION @HackerChick REALITY

21. @HackerChick

22. @HackerChick

23. @HackerChick Andrew Mason, CEO of Groupon (NY Tech Meetup)

24. you‘re way too dumb to figure out whether your idea @HackerChick is good Andrew Mason, CEO of Groupon (NY Tech Meetup)

25. Thinking ‘Bout Your Startup • Can I Make Money From It? • Can I Get People to Know About It? • Can I Build It? @HackerChick

26. Thinking ‘Bout Your Startup • Can I Build It? • Can I Get People to Know About It? • Can I Make Money From It? @HackerChick

27. @HackerChick

28. @HackerChick

29. @HackerChick

30. IDEAS Learn Build Measure Get Through The Whole Loop as FAST as POSSIBLE @HackerChick

31. Guesses Learn DO Measure Get Through The Whole Loop as FAST as POSSIBLE @HackerChick

32. The unit of progress for entrepreneurs… learning not execution @HackerChick

33. Idea to Launch • Find a problem worth solving • Know your customer • Find a solution that resonates • Launch when you have a quantum of utility @HackerChick

34. @HackerChick

35. COOL? @HackerChick

36. Step #1 Find a problem worth solving @HackerChick

37. We had an idea for a new product. We went off & built it, put it on our website. not a single person clicked thru What did we learn from that? @HackerChick

38. We had an idea for a new product. We went off & built it, put it on our website. not a single person clicked thru Was there a faster way to learn that? @HackerChick

45. How do you get people to your @HackerChick site ?

46. Step #2 know your customer @HackerChick

47. It’s just as important to develop our customers as our product @HackerChick

48. Lean Startup Product Customers Agile Development Customer Development @HackerChick

49. Lean Startup Product Customers Agile Development Customer Development @HackerChick

50. @HackerChick

51. Customer Discovery What is the problem? Who has the problem? @HackerChick @SGBlank

52. Customer Discovery How important is the problem’s solution to the customer? How valuable is the problem’s solution to the customer? @SGBlank @HackerChick

53. @HackerChick

54. What are you doing to solve this problem today? @HackerChick

55. Step #3 Find a solution that resonates @HackerChick

56. (MVP) Minimum Viable Product @HackerChick

57. Concierge Service (AKA Wizard of Oz) Boston Startup School - @HackerChick @HackerChick

58. @HackerChick

59. @HackerChick

60. Product/Market Fit “In a great market – a market with lots of real potential customers – the market pulls product out of the startup.” - Marc Andreessen @HackerChick

61. Step #4 launch! when you have a quantum of utility @HackerChick @paulg, Y Combinator

62. Guesses to Validate • Can I Make Money From It? • Can I Get People to Know About It? • Can I Build It? @HackerChick

63. • Find a problem worth solving • Know your customer • Find a solution that resonates • Launch when you have a quantum of utility @HackerChick

64. Learn More Eric Ries @EricRies http://startuplessonslearned.com/ Steve Blank @sgblank http://steveblank.com/ Ash Maurya @ashmaurya http://ashmaurya.com/ Abby Fichtner @HackerChick http://HackerChick.com

Lean Startups: A Success Blueprint for Early-Stage Entrepreneurs

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