How (and Why) to be a data driven startup - THub Rubrix

Transcript

1. How (and Why) to be a Data Driven Startup By Soham Mondal from Triveous 
 THub - RubriX
2. Presentation Agenda Agenda Introduction 
 Being data-driven: Why is it important? 
 Relevance to startups 1 Challenges 
 Perceived Challenges 
 Actual Problems 2 How to be a data driven startup? 
 Methodology 
 Tools 3
3. I’m Soham Mondal Founding Partner, Triveous 
 Lead Anchor Mentor @ Google For Startups Soham is the Founding Partner at Triveous and brings over 13 years of experience in building and servicing products across like finance, entertainment, education among others. https://www.linkedin.com/in/sohammondal/ 
 https://twitter.com/s0h4m Associations About
4. Triveous Technologies 
 https://triveous.com/ 2013 2016 2017 Khoslalabs Worked with Khoslalabs on a state-of-the-art micro ATM (any Kirana shop owner can act as an ATM teller using their mobile phone) and POS solutions for the underbanked sections of India. EnParadigm and Google Worked with Enparadigm on multiple offline first apps in the insurance and education space. Worked with Google on multiple initiatives in the User Experience and Android Application space. About
5. 2018 2022 FREND, Novopay and IDEO FREND is a non profit backed by Google and Tata Trusts. Worked on designing and developing an offline first application to generate livelihood for over 80,000 women in 300,000 villages across India. Worked with IDEO on a design framework for new internet users. Google AI, Creatorstack and Cutshort Worked with Novopay on multiple financial applications impacting millions of users across India. Worked on state of multiple state-of-the-art products in health, creator economy, recruitment and agri-tech.
6. Introduction What is a data-driven startup? Why should you care? 1
7. If you can’t measure it, you can’t improve it. Peter Drucker
8. Example: COVID - 19 Pandemic Metrics define strategy & progress No tracking = No management Number of cases vs Positivity Rate Government agencies, Healthcare workers Metrics define strategy PROBLEM STATEMENT Introduction
9. Forrester Research New type of startups/orgs are being created: Analysts at Forrester Research have identified a new type of organisation, the insights- driven business, which they claim are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021.
10. Harvard Business Review Data-driven companies enjoy increased revenue, improved customer service, best-in-class operating efficiencies, and improved profitability.
11. Startups Opportunity / Product Market Fit - How to define the problem statement 
 - How to find opportunities in market 
 - How to define product market fit 01. Product / Growth / Acquisition - How to prioritise new features? 
 - How to acquire new users? 
 - How to grow the organisation or product? 02. Monetisation - Choosing the right monetisation channels or strategy 
 - Revenue projections 03. Introduction
12. Challenges What are the challenges in being a data driven organisation? 2
13. Perceived Problem: Capturing Data
14. Feel overwhelmed making decisions at work 94% More data doesn’t mean better decision making From Oracle Netsuite
15. Real Challenges Important metrics What metrics should you capture? What metrics are important for your business? Data Driven Decision Making How do you make data driven decisions? Culture How to build an org wide culture of focusing on data and making data driven decisions? Challenges
16. Solution How to be a data driven startup or organisation? 3
17. Culture Make data driven decision making a part of the org culture Attitude Change your mindset about data Skilling Improve data literacy org- wide Tooling Provide people the right tools to be data driven
18. Don’t look at data as a separate part of the business to be used by analysts only Attitude
19. How do we make Data Driven Decision Making an Org-Wide phenomenon? Cultural Transformation
20. https://blog.weekdone.com/good-case-studies-implementing-okrs/
22. https://7geese.com/okr-objectives-and-key-results-faqs/
23. Analytics Framework Platform to securely capture and store data Access to Data, Data Literacy Easy access to data 
 Established process around data handling and access 
 Improve data literacy org-wide 
 Accessible OKRs Follow OKR or similar process 
 Make OKRs accessible to relevant people Product Research and Opportunity Analysis Use the “Jobs to be Done” Framework and other methodologies Tooling and Skilling Solution
24. Product Research Techniques Market Research - What Is the market? 
 - Who are your competitors? 
 - Who are the important stakeholders? 01. Qualitative Research - What do users need? 
 - What are their goals and aspirations? 
 - What are the challenges users face? 02. Quantitative Research - How to confirm or reject certain hypotheses? 
 - Statistical analysis of data 03. Solution
25. https://pdmethods.com/user-research/the-difference-between-qualitative-research-and-quantitative-research/
27. Jobs-to-be-Done Theory provides a framework for defining, categorising, capturing, and organising all your customers’ needs. JOBS TO BE DONE FRAMEWORK
28. https://hbr.org/2016/09/know-your-customers-jobs-to-be-done
29. https://jobs-to-be-done-book.com/
30. https://jobs-to-be-done-book.com/
31. https://www.intercom.com/blog/podcasts/podcast-tony-ulwick-on-jobs-to-be-done/
32. How (and Why) to be a Data Driven Startup? 01 Introduction How is data important? 
 Relevance to startups 02 Challenges Important Metrics 
 Data Driven Decision Making 
 Culture 03 Solution Attitude 
 Culture - OKRs 
 Skilling 
 Tooling - Jobs to be Done Recap
33. Thank You Email/Site soham@triveous.com 
 https://triveous.com/ 01. Email/Website https://www.linkedin.com/in/sohammondal/ 
 https://twitter.com/s0h4m 02. Slides https://speakerdeck.com/soham/how-and- why-to-be-a-data-driven-startup 03. Fin