This talk covers the PM framework needed to lead AI incubations. Product school webinar video at https://www.linkedin.com/video/live/urn:li:ugcPost:6690684172895322113/
This document discusses best practices for software product development. It covers:
1. Motivation for focusing on best practices due to trends like globalization, industrialization, and consumerization.
2. The state-of-the-art in science and practice, examining concepts from research areas like information systems, product management, and usability methods, as well as practices from industries like automotive and Apple.
3. Six key best practices are distilled from science and practice: having a clear product vision and leadership, using focused interdisciplinary empowered teams, maintaining a clear product scope, employing an artifact-centric development approach, integrating stakeholders continuously, and taking an incremental milestone-based approach.
1. The document discusses agile modeling and implementation strategies at different organizational levels. It provides details on how agile modeling practices like active stakeholder participation, iterative development, and simplicity can increase productivity and reduce defects.
2. Implementing agile requires changes to operating models and organizational structures to allow for more flexible development at scale. The core of agile modeling involves principles like simplicity, feedback, and maximizing stakeholder investment.
3. Effective documentation in agile focuses on clear communication, minimalism, and ensuring documents have value beyond the development process. Models and documents should be "just barely enough."
Second in a series of innovation webinars from Paul May & Brendan Dunphy of 'How to Farm Lightning: sustainable innovation' in partnership with Frost & Sullivan Ltd
How to Master Product Management Case Studies by fmr Groupon PMProduct School
Main takeaways
- How does one proceed in an interview when given a product case study to solve
- What are some of the most common case questions to practice
- What hiring managers are looking for when asking candidates to solve a product case
- The importance of a good hypothesis
- Best frameworks that can come in handy
The Strategic Role of Product Management
The Strategic Role of Product Management explains why product management is a critical, strategic role in a technology company. One which guides products to be created based on a market need, not because someone thinks it is a good idea.company. One which guides products to be created based on a market need, not because someone thinks it is a good idea.
India's first Annual Product Management and Marketing Benchmar launched at NA...Pinkesh Shah
The document summarizes the key findings from India's first annual Product Management survey conducted by Adaptive Marketing. The survey received 182 responses from product professionals in India. It found that most product managers in India have an engineering background and are 32 years old with 3.4 years of experience as a PM. They spend most of their time on requirements management and product planning. On average, PMs earn 18 lakhs annually with variable pay. Most PMs aspire to be entrepreneurs or work for large tech companies like Google.
The document summarizes a business case for a new connected digital picture frame product called DigiPix. It outlines the opportunity, market potential, product concept, development plan, and go-to-market strategy. Key points include strong growth in the digital photo frame market, customer interest in DigiPix's connectivity features, a first-mover advantage over competitors, and financial projections showing potential for $30M in revenue by year 4 with an initial $5M investment and positive NPV. The summary recommends moving forward with a $50K investment to further validate the market opportunity.
This document discusses best practices for software product development. It covers:
1. Motivation for focusing on best practices due to trends like globalization, industrialization, and consumerization.
2. The state-of-the-art in science and practice, examining concepts from research areas like information systems, product management, and usability methods, as well as practices from industries like automotive and Apple.
3. Six key best practices are distilled from science and practice: having a clear product vision and leadership, using focused interdisciplinary empowered teams, maintaining a clear product scope, employing an artifact-centric development approach, integrating stakeholders continuously, and taking an incremental milestone-based approach.
1. The document discusses agile modeling and implementation strategies at different organizational levels. It provides details on how agile modeling practices like active stakeholder participation, iterative development, and simplicity can increase productivity and reduce defects.
2. Implementing agile requires changes to operating models and organizational structures to allow for more flexible development at scale. The core of agile modeling involves principles like simplicity, feedback, and maximizing stakeholder investment.
3. Effective documentation in agile focuses on clear communication, minimalism, and ensuring documents have value beyond the development process. Models and documents should be "just barely enough."
Second in a series of innovation webinars from Paul May & Brendan Dunphy of 'How to Farm Lightning: sustainable innovation' in partnership with Frost & Sullivan Ltd
How to Master Product Management Case Studies by fmr Groupon PMProduct School
Main takeaways
- How does one proceed in an interview when given a product case study to solve
- What are some of the most common case questions to practice
- What hiring managers are looking for when asking candidates to solve a product case
- The importance of a good hypothesis
- Best frameworks that can come in handy
The Strategic Role of Product Management
The Strategic Role of Product Management explains why product management is a critical, strategic role in a technology company. One which guides products to be created based on a market need, not because someone thinks it is a good idea.company. One which guides products to be created based on a market need, not because someone thinks it is a good idea.
India's first Annual Product Management and Marketing Benchmar launched at NA...Pinkesh Shah
The document summarizes the key findings from India's first annual Product Management survey conducted by Adaptive Marketing. The survey received 182 responses from product professionals in India. It found that most product managers in India have an engineering background and are 32 years old with 3.4 years of experience as a PM. They spend most of their time on requirements management and product planning. On average, PMs earn 18 lakhs annually with variable pay. Most PMs aspire to be entrepreneurs or work for large tech companies like Google.
The document summarizes a business case for a new connected digital picture frame product called DigiPix. It outlines the opportunity, market potential, product concept, development plan, and go-to-market strategy. Key points include strong growth in the digital photo frame market, customer interest in DigiPix's connectivity features, a first-mover advantage over competitors, and financial projections showing potential for $30M in revenue by year 4 with an initial $5M investment and positive NPV. The summary recommends moving forward with a $50K investment to further validate the market opportunity.
Designing Successful International Go-To-Market StrategiesHans Bech
This white paper describes some of the challenges associated with international market penetration for software companies with long value chains. Further, it gives two real life examples of how companies have overcome these challenges using very different approaches.
Company XYZ changed from a channel-based approach to internationalization through acquisitions. Company ABC chose an international joint venture strategy to compensate for lack of staff and funds.
Modeling and Simulation in Business Process ManagementDenis Gagné
1) The document discusses using modeling and simulation in business process management to provide value during business transformations.
2) It explores how simulation could be used for communication, training, analysis, and validation and gives examples of visual, scenario, and numeric simulations.
3) The document outlines some best practices for business process modeling simulations including aligning the simulation and business goals and using the right expertise.
Product management boils down to owning the vision, design, and execution for your product. This presentation walks you through the roles and responsibilities of product managers and attributes of the most successful product folks.
Enjoyed this presentation? Subscribe to my weekly essays at http://www.sachinrekhi.com
Usability & Interface Design for HiTech ProductsPinkesh Shah
Slides from the Product Professionals Networking event hosted by AIPMM and Adaptive Makreting in Hyderabad, India on Feb 3rd.
Usability & Interface Design
www.adaptivemarketing.in
This Brainmates presentation seeks to answer the question "What is product management?"
This presentation investigates this important strategic role and illustrates its responsibilities and functional applications.
A useful reference for people working in product management or who are interested in a career in this field.
** About Brainmates:
Brainmates is an Australian based business that has is championing the important role that Product Managers perform in delivering a product's that are loved by their customers and deliver a return on investment to the businesses that provide them.
Brainmates trains coaches and supported Product Management Professionals in all kinds of industries and business sizes. Contact the team on +61 1800 272 466 to see if we can help your products and business.
** Connect with Brainmates online:
Visit the Brainmates WEBSITE: http://bit.ly/1lQ51mE
Like Brainmates on FACEBOOK: http://bit.ly/2c0RVaO
Follow Brainmates on TWITTER: http://bit.ly/2bNhKft
Brainmates - Product Management Training and Expertise
I. Define product management.
II. Discuss the constituents of a product.
i.Examine the significance product elements.
III. Evaluate the role of product packaging in consumers’ buying decisions.
IV. Evaluate four product-growth decisions.
V. Use techniques for product management.
The document provides an overview of product management for startups. It discusses what product management is, understanding customer needs, and prioritizing features to maximize return on engineering resources. The key aspects covered include translating business objectives and customer needs into product requirements, defining and tracking metrics, and identifying and planning high-impact product ideas. Understanding customer problems and priorities is emphasized as critical for developing successful products.
Software Product Management – Optimizing WHAT to Develop Ernani Ferrari
Software companies, as well as development teams in IT departments within companies of other industries have, for years, struggled to find better tools, methodologies and training process for software development. Yet, most medium and small organizations, as well as some large ones, still struggle with the processes that define WHAT the software to be developed should be and how it will evolve over time. Proper processes are not established and most times organizations cope with conflicting roles and stressing day-to-day decisions. Product management for software requires a company-wide understanding of goals, opportunities and required discipline related to product management and is fundamental to maximize all development and ongoing maintenance efforts. This session will address why product management is crucial to maximize revenues and reduce costs in the short, medium and long terms; what the role of a product manager is; how to unfold company strategies into product strategies; what the several business aspects to be considered at product planning are; how to define productization artifacts; and how to orchestrate product releases across a software company to improve corporate communication and overall financial results.
Main Message:
Software organizations have improved HOW they develop and support their products – they have also to improve how to, on an ongoing basis, optimize WHAT those products should be.
10 Best Practices Of Software Product ManagementSVPMA
Yossi Zohar is a senior director at Amdocs with over 22 years of experience in IT and software. He discusses 10 rules for effective product management. The rules include maintaining direct customer interactions; thoroughly prioritizing requirements; being ready to make quick de-scoping decisions; and justifying release scope through conflicting pressures. He also provides 3 bonus rules around being persistent, defining ROI-driven products, and focusing on business performance metrics. Yossi encourages questions and shares his contact information to continue the discussion.
Sjaak Brinkkemper: Visual Business Modeling Techniques for the Software IndustryCBOD ANR project U-PSUD
Visual Business Modeling Techniques for the Software Industry
Sjaak Brinkkemper, Utrecht University
at the conference
DATA, DIGITAL BUSINESS MODELS, CLOUD COMPUTING AND ORGANIZATIONAL DESIGN
24-25 November 2014
University Paris –Sud
Software Product Management in Web 2.0Suhas Kelkar
This document outlines the course objectives and content for a 12-hour course on software product management. The course will introduce students to key concepts like requirements gathering, writing business cases, product pricing, branding, and innovation. It will also cover frameworks for managing and marketing technology products. The course is divided into four 3-hour sessions that will address topics such as pricing models, prioritizing features, creating product roadmaps, and product management in agile and web 2.0 environments.
Practical Product Management for new Product ManagersAmarpreet Kalkat
This presentation provides tips and tools for a professional who is new to Product Management function (in software).
It does not cover the full lifecycle of a product and primarily focuses on the product development/product building phase. As such, it is more usable for professionals working on existing products than for those in the process of building new products from scratch.
The document summarizes the history and goals of the Business Process Simulation Working Group (BPSWG). It established in 2011 to develop standards for parameterizing and interchanging process analysis data to allow structural and capacity analysis of business processes. The BPSWG aims to define a specification that encourages wider adoption of simulation and provides an open interchange format for simulation scenario data. The standard complements existing process modeling standards like BPMN and XPDL.
The document summarizes the strategic role of product management. It argues that product management is needed to make companies market-driven by understanding customer needs and problems in order to build products people want to buy. It distinguishes product management from marketing, which it defines as creating customer-focused products rather than promotional activities. It also differentiates product management from sales by noting product managers focus on future products while sales focuses on current offerings.
The document discusses the strategic role of product management. It argues that product management is needed for companies to become truly market-driven by identifying customer problems and communicating these to other departments to build products that people want to buy. It distinguishes product management from marketing, which it defines as understanding customer needs rather than promotional activities. It also differentiates product management from sales by describing how product management ensures the company focuses on solving customer problems rather than just selling existing products.
The document outlines the problem solving process for developing computer programs. It discusses the steps as: 1) defining and analyzing the problem, 2) designing the program using techniques like algorithms and flowcharts, 3) coding the program, 4) compiling the code, 5) debugging and testing for errors, 6) documenting the program, and 7) implementing the program and maintaining it for users. The overall process transforms a problem description into a solution by applying appropriate problem-solving strategies, techniques and tools.
Peter Boersma's presentation "UX Beyond UCD" from UX Camp Europe 2012. Shows deliverables that influence the user experience that are not part of the standard User Centered Design set. Includes deliverables from business, strategy, (project) management, and process design.
Building Scalable ML Products by TripAdvisor PM & Data ScientistProduct School
Main takeaways:
- How to build Product Roadmap together with Data Science
- How to Prioritize Machine Learning features
- Measuring success on Machine Learning models
Designing Successful International Go-To-Market StrategiesHans Bech
This white paper describes some of the challenges associated with international market penetration for software companies with long value chains. Further, it gives two real life examples of how companies have overcome these challenges using very different approaches.
Company XYZ changed from a channel-based approach to internationalization through acquisitions. Company ABC chose an international joint venture strategy to compensate for lack of staff and funds.
Modeling and Simulation in Business Process ManagementDenis Gagné
1) The document discusses using modeling and simulation in business process management to provide value during business transformations.
2) It explores how simulation could be used for communication, training, analysis, and validation and gives examples of visual, scenario, and numeric simulations.
3) The document outlines some best practices for business process modeling simulations including aligning the simulation and business goals and using the right expertise.
Product management boils down to owning the vision, design, and execution for your product. This presentation walks you through the roles and responsibilities of product managers and attributes of the most successful product folks.
Enjoyed this presentation? Subscribe to my weekly essays at http://www.sachinrekhi.com
Usability & Interface Design for HiTech ProductsPinkesh Shah
Slides from the Product Professionals Networking event hosted by AIPMM and Adaptive Makreting in Hyderabad, India on Feb 3rd.
Usability & Interface Design
www.adaptivemarketing.in
This Brainmates presentation seeks to answer the question "What is product management?"
This presentation investigates this important strategic role and illustrates its responsibilities and functional applications.
A useful reference for people working in product management or who are interested in a career in this field.
** About Brainmates:
Brainmates is an Australian based business that has is championing the important role that Product Managers perform in delivering a product's that are loved by their customers and deliver a return on investment to the businesses that provide them.
Brainmates trains coaches and supported Product Management Professionals in all kinds of industries and business sizes. Contact the team on +61 1800 272 466 to see if we can help your products and business.
** Connect with Brainmates online:
Visit the Brainmates WEBSITE: http://bit.ly/1lQ51mE
Like Brainmates on FACEBOOK: http://bit.ly/2c0RVaO
Follow Brainmates on TWITTER: http://bit.ly/2bNhKft
Brainmates - Product Management Training and Expertise
I. Define product management.
II. Discuss the constituents of a product.
i.Examine the significance product elements.
III. Evaluate the role of product packaging in consumers’ buying decisions.
IV. Evaluate four product-growth decisions.
V. Use techniques for product management.
The document provides an overview of product management for startups. It discusses what product management is, understanding customer needs, and prioritizing features to maximize return on engineering resources. The key aspects covered include translating business objectives and customer needs into product requirements, defining and tracking metrics, and identifying and planning high-impact product ideas. Understanding customer problems and priorities is emphasized as critical for developing successful products.
Software Product Management – Optimizing WHAT to Develop Ernani Ferrari
Software companies, as well as development teams in IT departments within companies of other industries have, for years, struggled to find better tools, methodologies and training process for software development. Yet, most medium and small organizations, as well as some large ones, still struggle with the processes that define WHAT the software to be developed should be and how it will evolve over time. Proper processes are not established and most times organizations cope with conflicting roles and stressing day-to-day decisions. Product management for software requires a company-wide understanding of goals, opportunities and required discipline related to product management and is fundamental to maximize all development and ongoing maintenance efforts. This session will address why product management is crucial to maximize revenues and reduce costs in the short, medium and long terms; what the role of a product manager is; how to unfold company strategies into product strategies; what the several business aspects to be considered at product planning are; how to define productization artifacts; and how to orchestrate product releases across a software company to improve corporate communication and overall financial results.
Main Message:
Software organizations have improved HOW they develop and support their products – they have also to improve how to, on an ongoing basis, optimize WHAT those products should be.
10 Best Practices Of Software Product ManagementSVPMA
Yossi Zohar is a senior director at Amdocs with over 22 years of experience in IT and software. He discusses 10 rules for effective product management. The rules include maintaining direct customer interactions; thoroughly prioritizing requirements; being ready to make quick de-scoping decisions; and justifying release scope through conflicting pressures. He also provides 3 bonus rules around being persistent, defining ROI-driven products, and focusing on business performance metrics. Yossi encourages questions and shares his contact information to continue the discussion.
Sjaak Brinkkemper: Visual Business Modeling Techniques for the Software IndustryCBOD ANR project U-PSUD
Visual Business Modeling Techniques for the Software Industry
Sjaak Brinkkemper, Utrecht University
at the conference
DATA, DIGITAL BUSINESS MODELS, CLOUD COMPUTING AND ORGANIZATIONAL DESIGN
24-25 November 2014
University Paris –Sud
Software Product Management in Web 2.0Suhas Kelkar
This document outlines the course objectives and content for a 12-hour course on software product management. The course will introduce students to key concepts like requirements gathering, writing business cases, product pricing, branding, and innovation. It will also cover frameworks for managing and marketing technology products. The course is divided into four 3-hour sessions that will address topics such as pricing models, prioritizing features, creating product roadmaps, and product management in agile and web 2.0 environments.
Practical Product Management for new Product ManagersAmarpreet Kalkat
This presentation provides tips and tools for a professional who is new to Product Management function (in software).
It does not cover the full lifecycle of a product and primarily focuses on the product development/product building phase. As such, it is more usable for professionals working on existing products than for those in the process of building new products from scratch.
The document summarizes the history and goals of the Business Process Simulation Working Group (BPSWG). It established in 2011 to develop standards for parameterizing and interchanging process analysis data to allow structural and capacity analysis of business processes. The BPSWG aims to define a specification that encourages wider adoption of simulation and provides an open interchange format for simulation scenario data. The standard complements existing process modeling standards like BPMN and XPDL.
The document summarizes the strategic role of product management. It argues that product management is needed to make companies market-driven by understanding customer needs and problems in order to build products people want to buy. It distinguishes product management from marketing, which it defines as creating customer-focused products rather than promotional activities. It also differentiates product management from sales by noting product managers focus on future products while sales focuses on current offerings.
The document discusses the strategic role of product management. It argues that product management is needed for companies to become truly market-driven by identifying customer problems and communicating these to other departments to build products that people want to buy. It distinguishes product management from marketing, which it defines as understanding customer needs rather than promotional activities. It also differentiates product management from sales by describing how product management ensures the company focuses on solving customer problems rather than just selling existing products.
The document outlines the problem solving process for developing computer programs. It discusses the steps as: 1) defining and analyzing the problem, 2) designing the program using techniques like algorithms and flowcharts, 3) coding the program, 4) compiling the code, 5) debugging and testing for errors, 6) documenting the program, and 7) implementing the program and maintaining it for users. The overall process transforms a problem description into a solution by applying appropriate problem-solving strategies, techniques and tools.
Peter Boersma's presentation "UX Beyond UCD" from UX Camp Europe 2012. Shows deliverables that influence the user experience that are not part of the standard User Centered Design set. Includes deliverables from business, strategy, (project) management, and process design.
Building Scalable ML Products by TripAdvisor PM & Data ScientistProduct School
Main takeaways:
- How to build Product Roadmap together with Data Science
- How to Prioritize Machine Learning features
- Measuring success on Machine Learning models
Customer segmentation for business success with knimeKnoldus Inc.
Customer segmentation has undoubtedly been one of the most implemented applications in data analytics since the birth of customer intelligence and CRM. Data scientists and modern business analysts work closely together to achieve and automize a comprehensive description of the company’s group of customers.
However, they usually came across these two challenges:
~ Need to implement a customer segmentation frame that can accommodate a self-adjusting procedure.
~ Need an interactive way to inject their knowledge into the customer segmentation frame without ever opening the underlying data processing workflow.
Learn how to generate different customer groups using clustering and how to provide insights into the performance of sales activities.
The document outlines Neo4j's customer journey framework and services to help customers successfully implement graph database projects. It introduces Neo4j services like innovation labs, modeling sessions, references, bootcamps, proofs of concept, and expert services that guide customers through evaluation, implementation, and adoption. Example graph projects in master data management, knowledge graphs, and network management are also summarized.
Choose the Right Problems to Solve with ML by Spotify PMProduct School
Main takeaways:
-What problems are best solved with ML and what problems are NOT
-What you need to understand and how technical you need to get as a PM of an ML product
A practical guide for startups to drive growth and innovation.
Denver Startup Week Product Track presentation by Argie Angeleas, Taylor Names, Matt Reynolds
The Product Management Journey by Adobe & PayPal PMsProduct School
Speakers from Adobe and PayPal, have spent a good number of years as Product Managers in their respective companies. Their stories give you an idea of how the role of a Product Manager evolves with time.
Debapriya Basu is a Principal Product Manager at Zillow who specializes in AI products and technology. The presentation covers designing user experiences for AI-infused systems, including principles of design such as embracing customer needs and building trust. Guidelines are provided for user interaction stages like before first interaction, during interaction, and when things go wrong. A framework is outlined for the design process, including determining how AI can help, identifying user needs, collecting and analyzing data, designing prototypes, and incorporating feedback.
This document discusses demystifying data science. It begins by introducing the speaker and their background in data science. It then discusses common misconceptions about data science, noting that it is more than just statistics, machine learning, big data, or business analytics. The document outlines the full data science process from exploratory analysis to modeling to testing and evaluation. It emphasizes the importance of a scientific approach and focusing on solving business problems. Finally, it discusses best practices for developing data products and the ideal skillset of a data science team.
Machine Learning has become a must to improve insight, quality and time to market. But it's also been called the 'high interest credit card of technical debt' with challenges in managing both how it's applied and how its results are consumed.
How to be a Digital Products Ninja by ServiceNow Sr. PMProduct School
Main takeaways:
- Learn how to be an expert product Ninja in the continuously changing digital world
- Learn about top 7 productivity hacks for Product Managers
- Best practices and framework for the product manager’s toolbox
GraphTour 2020 - Customer Journey with Neo4j ServicesNeo4j
1) The document discusses Jan Aertsen's background and various services offerings from Neo4j to help customers implement graph database solutions. It covers services like innovation labs, modeling sessions, bootcamps, proofs of concept, and full implementation support.
2) Examples of graph database projects discussed include a master data management solution, knowledge graphs, and network management. For each, the document outlines the business problem, how Neo4j can help, and the services Neo4j provides.
3) Neo4j's services aim to accelerate customers' innovation through graph thinking at all stages of the customer journey from problem awareness to solution adoption and advocacy.
Machine learning models are difficult to operationalize at scale due to infrastructure challenges like supporting different frameworks and languages, managing models through versioning and reproducibility, and deploying models at large scale. Most organizations struggle with successfully moving projects from proof-of-concept to production as lack of process, incentives, skills, champions, and appropriate technology impede operationalization. Adopting practices like integrating engineering and data science teams, defining clear production criteria, and choosing infrastructure-agnostic platforms can help organizations realize value from machine learning by addressing these barriers to operationalization.
Give the People What They Want: An Approach to Thoughtful KM TechnologyEnterprise Knowledge
This document provides an overview of a presentation by Todd Fahlberg and Madison Jaronski on taking a thoughtful approach to KM technology. It discusses assessing the current people, processes, culture and technologies that make up a KM ecosystem. It emphasizes understanding business drivers, putting KM in terms of results, using an iterative approach, and active communication. It outlines a 4 phase approach to selecting KM technology: 1) Gathering requirements and defining personas, 2) Leveraging data driven evaluations like demonstrations and proofs of concept, 3) Combining quantitative and qualitative data for decisions, 4) Crafting an implementation strategy for success and adoption. Key aspects discussed include change management, communications, training, and governance.
Machine learning projects may seem similar to any software engineering endeavor, the reality is machine learning projects are onerous, demand high quality work from every person involved, and are sensitive to any tiny mistake.
It seems that we cannot go five years without having some massive technology shift that becomes an essential part of our day-to-day lives. So, we will start with a proper definition of machine learning and how it is changing the way businesses analyze information. We will then continue by discussing proper ways to begin machine learning projects, including weighing the feasibility of a project, planning timelines, and the stages of the machine learning workflow once you start your project.
After exploring the stages of the machine learning workflow, we will end the webinar with an example of a completed machine learning project. We will demonstrate how to create a similar project and give you the tools to create your own.
What you'll learn:
A deeper understanding of the end-to-end machine learning workflow.
The tools needed to effectively create, design, and manage machine learning projects.
The skills to define your goal, foresee issues, release models, and measure outcomes during the ML project lifecycle.
Demo: Skyl Platform for End-End machine learning workflow.
This is the slide deck for this webinar:
https://skyl.ai/webinars/guide-end-to-end-machine-learning-projects
How to Be a Data Driven PM by TORA Chief Marketing OfficerProduct School
Key Takeaways:
- How to make data-driven decisions;
- The importance of making data-driven decisions;
- Where and how to gather and use data effectively with real-life examples;
- How important data training is for product managers.
Using Data Science to Build an End-to-End Recommendation SystemVMware Tanzu
This document summarizes the key steps and outcomes of a project to build an end-to-end recommendation system for a power utility company. The system was designed to integrate machine learning models with mobile and call center systems to recommend ancillary products to customers. The project involved exploring customer data, developing machine learning models through an iterative process, and operationalizing the models by building APIs and automated workflows. The new system provided recommendations via microservices and represented an improvement over the utility's previous manual, less rigorous approach to data science and modeling.
Cloud Machine Learning can help make sense of unstructured data, which accounts for 90% of enterprise data. It provides a fully managed machine learning service to train models using TensorFlow and automatically maximize predictive accuracy with hyperparameter tuning. Key benefits include scalable training and prediction infrastructure, integrated tools like Cloud Datalab for exploring data and developing models, and pay-as-you-go pricing.
How to Increase Your Product Sense by ServiceNow Senior PMProduct School
Main takeaways:
- Framework of learning and improving your product sense
- Learn how to do your skill gap analysis and ideas to level up
- How to build it as a muscle and create successful products
Design decisions in job architectures and competency modeling June 2020Steven Forth
This document provides guidance on designing a skill and competency management program. It discusses key design decisions around job architecture, competency modeling, and integration with other systems. The document recommends: beginning with 1-3 use cases; deciding on one or multiple competency models, a top-down or bottom-up approach, and a big bang or successive rollout strategy; designing job architecture with common and specialized components; and identifying integration points across HR systems. It also offers best practices for adoption such as seeding profiles and reporting on trends. The goal is to build capabilities for adaptation, efficiency, and resilience through an effective skill management program.
Similar to Lead AI incubations as a Product manager (20)
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
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Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
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Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
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Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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* Step-by-step implementation guide
* Live demos with code snippets
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#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Dr. Sean Tan, Head of Data Science, Changi Airport Group
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Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
2. HELLO!
I am Debapriya Basu
I am here to share my learnings and experiences
on how to drive AI incubations.
You can find me at
https://www.linkedin.com/in/debapriyabasu/
Current: PM@Zillow Group
Former: PM@Microsoft
2
3. WHAT I WILL
COVER
Journey of an AI(ML) PM, using real life examples to
illustrate
◎ When to use AI(ML) to solve customer problems
◎ What is a generic PM framework for an AI (ML)
incubation
◎ What skills help PMs to succeed in AI (ML)
incubations
3
6. IDENTIFY
CUSTOMER
PROBLEM
◎ What is the problem
◎ How can the problem be solved
without AI(ML)
◎ How can AI(ML) add value
◎ Identifies complex patterns to predict
outcomes
◎ Adapts outcome to inputs in real time
◎ Scales on vast datasets fast
◎ Enables personalization
◎ Adapts to post launch improvements on
model through feedback flywheel generated
by user’s interaction with UX + AI
6
ZESTIMATE
7. AI(ML) IN ACTION
2 PREDICTION
RECOMMENDATION
CLASSIFICATION
ANOMALY DETECTION
NATURAL LANGUAGE PROCESSING
CONVERSATIONAL AI ETC
13. ◎ Predictions
◎ Recommendations
◎ Classification
◎ Natural Language Processing
◎ Anomaly Detection
◎ Conversational AI
◎ etc
USE AI (ML)
TECH FOR
13
GOOGLE
15. BUSINESS
OUTCOMES
◎ AI(ML) solutions provide such
enhanced productivity for
end-users that it ends up changing
their Human Computer Interaction
and becomes table stakes for
businesses
Search
15
16. BUSINESS
OUTCOMES
◎ Customized User Experiences leads to
engaged and retained users
◎ Recommendations
◎ Custom Personalization
◎ Conversational AI
Netflix artwork is personalized to
Individuals
16NETFLIX
17. BUSINESS
OUTCOMES
◎ Identification of insights using
AI(ML) help optimize for business
goals (like saving costs or deciding
more effectively where to invest)
17
GOOGLE
Google used DeepMind’s ML to reduce
energy to cool its data centers by 40%
18. BUSINESS
OUTCOMES
◎ Strategy helps expand to new
surfaces and customers
quicker
Google cloud search is Google search for
enterprise content and is available in Gmail,
Drive, Docs, Sheets, Slides, Calendar here
18
GOOGLE
21. IDEATE ALIGN
Align stakeholders to a
common definition of
the problem
OBJECTIVE FUNCTION
Is it Prediction, Classification
or something else
MODEL QUALITY
METRICS
Classification Metrics like
Precision, Recall etc
Rank Aware Metrics like
NDCG, MRR etc
Trade-offs
21
EXPERIENCES
Identify hero
experience with
implicit and explicit
user feedback
mechanism to ideate
SUCCESS
DEFINITION
Define success in terms
of online metrics
22. IDEATE
22
GOAL:
How popular will a listing be?
OBJECTIVE FUNCTION:
Predict the likelihood of a listing to drive a
contact request tomorrow, given
● the listing content features (price,
size, location etc) and
● historical engagement (the number
of views, saves and contacts a listing
has received on the previous days)
OFFLINE METRIC:
AUC and NDCG
ONLINE METRIC:
#contacts, #views
Ref
23. IDENTIFY
DATA
AND AI
TECHNOLOGY
DATA
◎ 1st Party vs 3rd Party
◎ Privacy and Security
◎ Fresh
◎ Unbiased
◎ Representative
◎ Relevant
◎ Missing data
◎ Noisy data
◎ Inconsistent
23
AI TECH
◎ Machine learned
◎ Supervised
◎ Unsupervised
◎ Reinforced
◎ Modeling Techniques
◎ Deep learning
◎ NLP
◎ Ensemble Learning
◎ Pre-trained Models
25. PROTOTYPE
25
Validate
● If supervised
learning, validate
offline metrics
against ground
truth
● If clustering,
determine how well
situated a point is in
a cluster or how
distant clusters are
Build
● Simplify objective
function
● Select most relevant
features
● Test multiple algos if
needed
Iterate till
acceptance
criteria reached
● Define behavior in
edge cases
● Define fallback if
model does not
work as needed
Not often time-bound
and maynot yield best
results in get go
Don’t forget to eyeball
Are you improving
performance on existing
non-AI orAI solution
Analyze
● Analyze every
important attribute
of dataset
● Identify
relationships
between attributes
in the dataset
● Analyze in context of
time, user etc
● Visualize
26. GET
SPONSORSHIP
26
ROI
In terms of monetary gain,
users acquired, retained, cost
saving, gain or save on
company OKRs
Resourcing
How many
What type
Value for the business
Align with overall strategy
Competing / Differentiator
Value for the customer
Productivity, Engagement etc
SELL
PRODUCT/TECH
VISION
27. BUILD TEAM Immediate
Skills
◎ Applied Science
◎ Data Science
◎ Data Pipeline Engineering
◎ E2E and online Product Engineering
◎ Machine Learning Engineering
27
V-Team
◎ Annotators
◎ Experience Teams
◎ Architecture Teams
◎ Data Engineering Teams
◎ Experimentation Platform
Teams
◎ Legal, Privacy, Security
Attitude
● Comfort with ambiguity
● Willingness and ability to shape the problem
● Ability to look at the problem from different
angles and dimensions
● Ability to think laterally
● Success comes in iterations
28. 28
UX FOR AI -> TRANSPARENT + EXPLAINABLE AI
MODEL CONFIDENCE
EXPLICIT FEEDBACK
LIKE/DISLIKE
DATA SOURCES
MODEL
FEATURES
Ref
IMPLICIT FEEDBACK IS CRITICAL
29. AI
ARCHITECTURE
29
Ref Offline Modeling pipeline
E2E Architecture
3 levels
◎ Offline model training pipeline
◎ Online serving infrastructure
◎ E2E architecture
◎ UX
◎ Online serving infra
◎ Offline Batch processing
◎ Other dependent systems
PM considerations
- Mechanism of Data collection
(batched/streamed)
- Frequency of Data Collection
- Dependency systems
- How are predictions processed
(real-time/offline)
30. SHIP A MODEL Refine prototype or build new model
◎ DataAnalysis
◎ Algorithm selection
◎ Objective function selection
◎ Training and test set selection
◎ Feature selection
◎ Expand data coverage
◎ Check for outliers
◎ Retrain, retest your model
◎ Scale to new markets and languages
30
Operationalize
◎ Validate via online Experiments
◎ Ship in production
◎ Learn from causal uplift analysis
◎ Scale data collection
◎ Scale models to new markets and
languages
◎ Incorporate feedback either in
real time or offline
◎ Reduce friction to deploy models
◎ Version control models
Success => Online metric improvements,
Offline metric improvement
31. SUSTAINED
SUCCESS
CRITERIA
AI Models powering
Individual Product or Feature
Established Relation between
online metric and offline metric
31
AI Models for understanding
a class of entities
Adoption
User UnderstandingAI is
a class of models that
helps understand
customer’s state, segment
and journey
32. ETHICAL AI Privacy
AI models should be built within
guardrails to ensure users cannot be
identified or their details inferred
from model output
Researchers were able to identify Netflix
users by correlating anonymized test data
provided in the Netflix Prize competition with
publicly available IMDB movie review
database.
32
Fairness
AI/ML models used for making decisions or
predictions should not be biased with respect
to protected attributes (latent bias) such as
race, gender and sexuality. It should be aware
and counter impacts of interaction and
selection bias also.
A MIT study Project Gender Shades uncovered
the bias that facial analysis technologies have
a heavy bias towards white males.
JoyAdowaa Buolamwini foundedAlgorithmic
Justice League, an organisation that looks to
challenge bias in decision making software
34. SKILLS
34
Clarify
Clarify goals, assumptions
Understand what the data says
Simplify problem, process,
solution
Be resilient
Learn from failures, course
correct, reshape problem,
remodel, reengineer
Success is a process, not an
end goal
Focus
Keep an eye on customer problem at
all times
Refine optimization function and
online metric until crisp, offline
metrics until relation between online
and offline metric is identified
Zoom in-out
(+) Guide product direction and
discussion as needed
(-)Align product to broader
business strategy
35. WHAT’S NEXT
AFTER A
SUCCESSFUL
INCUBATION
35
Life post incubation (launch)
◎ Analyze user feedback data, both implicit and explicit
◎ Understand user pain-points with the product and work to mitigate it
As a PM, this is the moment
where you decide to take the
shipped technology to next
phase or move to shape a new
idea to solve a customer
problem
◎ Continue to iterate model with fresh data and feedback
◎ Build a strategy for improved model quality, by training on sophisticated
frameworks, more data etc
◎ Understand and analyze industry and expert sentiments on the product
◎ Build a strategy of the shipped product/technology ROI
◎ Should it be expanded to new surfaces, new markets
◎ Does the engagement and feedback funnel provide enough data to
retrain models
◎ Should UX be updated to ensure better quality feedback
USER
IMPACT
MODEL
QUALITY
PRODUCT-
TECH
STRATEGY
36. HOW IS
LEADING
AN AI (ML)
INCUBATION
DIFFERENT
FROM LEADING
OTHER
PROJECTS
AS A PM
36
What’s same, what’s different
- Understand customer problem,
- Define strategy
- Define vision and success criteria of product
- Drive alignment and collaboration
- Execute
- UnderstandAI technology, process and needs of building models
- Define optimization goal of the model, success KPIs
- Understand Datasets, learn relationship between online and offline metric
- Design UX that works for the non-deterministic aspect ofAI
- Understand Privacy and Legal impact onAI models and how they affect customers
Core PM
skills
AI PM
skills
- Shape a problem from ambiguity
- Find, stitch data, identify insights from data
- Envision and convince others of the vision
- Collaborate, collaborate, collaborate
- Think laterally and think iteratively, reshape, re-pivot as needed
- Be resilient (failures form the way to ultimate success)
AI incubation
PM skills
37. SPECIAL
THANKS
◎ Amit Mondal, Google
◎ Kieran Mcdonald, Microsoft
◎ Ondrej Linda, Zillow
◎ Sangdi Lin, Zillow
37
Slide template
38. WHAT I
COVERED
Takeaways and food for thought
◎ When do you use AI (ML) to solve customer
problems
◎ What are the stages you as a PM go through in an
AI (ML) incubation
◎ What skills and mindset will help you to succeed
in AI (ML) incubations
Please reach out with your comments and thoughts at
tutulpriya@gmail.com
38