This document compares web development and data science careers. It defines data science as using the data pipeline to ask questions, collect raw data, process it, explore it, and communicate results. Four common data scientist types are described: researchers with advanced degrees, AI specialists who code solutions from scratch, statisticians with math backgrounds, and super analysts who solve problems through code. Web development types include frontend developers using HTML/CSS/JavaScript, backend developers creating applications, and full stack developers who can do both. The document discusses indirect tech jobs and shows data science and web development have growing job markets. It provides suggestions for how to learn both fields through a free two-week trial program.
Summit Day 5: How to Use Data to Grow Your Membership in Just 1 Hour a MonthWild Apricot
With just one hour of your time and a few free tools, you could be increasing your membership every month. To learn how, join our free webinar on November 16th with Jason Jensen, data-driven marketing evangelist and nonprofit consultant. Jason will show you the tried-and-tested process that any nonprofit can use to increase membership and donations using data-driven marketing. Even if you’ve never measured a single campaign, you’ll be able to implement these strategies.
How Designers Can Make the World a Happier PlaceCentralis
Design is powerful – it can generate excitement, bring joy, provoke anger, or trigger anxiety, sometimes all in the same interaction. From the big decisions about a product’s purpose all the way down to the myriad pixel-level arguments lost and won, designers have a great responsibility to safeguard the happiness of the users we serve. But what do we really know about the nature of happiness? And how can we actually make everyone happy?
In this talk, Kathi Kaiser (Co-Founder & COO, Centralis) deconstructs the concept of “happiness” and offer designers a framework for considering the emotional impact of their work. She explores the meaning, dimensions, and pre-conditions of happiness while examining the wide range of satisfying outcomes and their implications for design. Drawing on recent research in psychology as well as real-world design examples, you’ll learn when and how to evoke joy, humor, reassurance, comfort, and other positive feelings through applying a set of guiding principles for the pursuit of happiness.
The document provides an agenda for a presentation on productivity. It discusses defining productivity, identifying the highest leverage activities to achieve strategic goals, automating tasks, getting help with projects, and improving business development skills. The presentation emphasizes focusing on key strategic objectives, tracking lead measures of progress, maintaining accountability, and closing sales opportunities.
How to think like a data scientist sandeepsandeep kumar
This document provides guidance on how to think like a data scientist. It outlines prioritizing the most important problems, decoding the key issues, and using a structured process for data science. This includes analyzing data, asking questions to arrive at conclusions, and making observations for accurate results. Learning by doing is emphasized as the best way to apply the knowledge, such as by immediately solving real problems with real data. The document also discusses how these principles are relevant for managers in India, including understanding models, deploying hypotheses, generating data, searching for mechanisms, and ensuring reproducibility and impact.
This document discusses metrics that matter for startups. It emphasizes that companies should measure customer value delivery, not just revenue. The key aspects are:
- Companies should have a North Star Metric that represents overall customer value delivered and endures over time.
- They should focus on 1-3 Key Drivers that directly impact the North Star Metric. This includes identifying the rate-limiting step.
- Nuance Metrics are also important to watch but not maximize.
- For pre-product-market fit startups, key drivers should focus on fast iterative learning and deepening fit with customers. Retention metrics need to identify the habituation threshold.
- The document provides examples and guides companies
The elements of the development plan
Elements of the quality plan
Development and quality plans for small and for internal projects
Software development risks a
This document compares web development and data science careers. It defines data science as using the data pipeline to ask questions, collect raw data, process it, explore it, and communicate results. Four common data scientist types are described: researchers with advanced degrees, AI specialists who code solutions from scratch, statisticians with math backgrounds, and super analysts who solve problems through code. Web development types include frontend developers using HTML/CSS/JavaScript, backend developers creating applications, and full stack developers who can do both. The document discusses indirect tech jobs and shows data science and web development have growing job markets. It provides suggestions for how to learn both fields through a free two-week trial program.
Summit Day 5: How to Use Data to Grow Your Membership in Just 1 Hour a MonthWild Apricot
With just one hour of your time and a few free tools, you could be increasing your membership every month. To learn how, join our free webinar on November 16th with Jason Jensen, data-driven marketing evangelist and nonprofit consultant. Jason will show you the tried-and-tested process that any nonprofit can use to increase membership and donations using data-driven marketing. Even if you’ve never measured a single campaign, you’ll be able to implement these strategies.
How Designers Can Make the World a Happier PlaceCentralis
Design is powerful – it can generate excitement, bring joy, provoke anger, or trigger anxiety, sometimes all in the same interaction. From the big decisions about a product’s purpose all the way down to the myriad pixel-level arguments lost and won, designers have a great responsibility to safeguard the happiness of the users we serve. But what do we really know about the nature of happiness? And how can we actually make everyone happy?
In this talk, Kathi Kaiser (Co-Founder & COO, Centralis) deconstructs the concept of “happiness” and offer designers a framework for considering the emotional impact of their work. She explores the meaning, dimensions, and pre-conditions of happiness while examining the wide range of satisfying outcomes and their implications for design. Drawing on recent research in psychology as well as real-world design examples, you’ll learn when and how to evoke joy, humor, reassurance, comfort, and other positive feelings through applying a set of guiding principles for the pursuit of happiness.
The document provides an agenda for a presentation on productivity. It discusses defining productivity, identifying the highest leverage activities to achieve strategic goals, automating tasks, getting help with projects, and improving business development skills. The presentation emphasizes focusing on key strategic objectives, tracking lead measures of progress, maintaining accountability, and closing sales opportunities.
How to think like a data scientist sandeepsandeep kumar
This document provides guidance on how to think like a data scientist. It outlines prioritizing the most important problems, decoding the key issues, and using a structured process for data science. This includes analyzing data, asking questions to arrive at conclusions, and making observations for accurate results. Learning by doing is emphasized as the best way to apply the knowledge, such as by immediately solving real problems with real data. The document also discusses how these principles are relevant for managers in India, including understanding models, deploying hypotheses, generating data, searching for mechanisms, and ensuring reproducibility and impact.
This document discusses metrics that matter for startups. It emphasizes that companies should measure customer value delivery, not just revenue. The key aspects are:
- Companies should have a North Star Metric that represents overall customer value delivered and endures over time.
- They should focus on 1-3 Key Drivers that directly impact the North Star Metric. This includes identifying the rate-limiting step.
- Nuance Metrics are also important to watch but not maximize.
- For pre-product-market fit startups, key drivers should focus on fast iterative learning and deepening fit with customers. Retention metrics need to identify the habituation threshold.
- The document provides examples and guides companies
The elements of the development plan
Elements of the quality plan
Development and quality plans for small and for internal projects
Software development risks a
The document discusses the importance of focusing on outcomes over outputs for team performance. It argues that teams perform best when they have a clear, measurable purpose and understand how their work impacts outcomes. This is illustrated through the example of NASA's mission to return Apollo 13's crew safely to Earth. The document advises defining an inspiring outcome-focused problem, establishing baseline metrics and success criteria, and breaking the problem down into sub-problems that each connect to and help achieve the overall outcome. Regularly measuring impacts on outcomes allows teams to prioritize, make data-driven decisions, and stay aligned on a shared vision and purpose.
The document outlines an idea workshop focused on determining strategic initiatives or "seeds" for an organization. It provides guidance on what makes a good seed, including being a multi-year goal that allows progress towards a larger objective. The document also covers brainstorming principles and a process for theme generation, grouping, voting and idea exercises to identify priority seeds.
This document outlines a strategic planning process for an organization called AIA. It includes sections on understanding needs, purpose, goals, categories of involvement, milestones, ideas, roadblocks, resources, and keeping the main priorities the top focus. The overall purpose is to move from vision to action by identifying wildly important goals.
Effectuation Overview by Insights IgnitedBeth Crooker
Insights Ignited (http://www.insightsignited.com) gives an overview of Effectuation - the mindset successful entrepreneurs use to build new ventures, as discovered by Dr. Saras Sarasvathy at UVA Darden's School of Business.
How to start thinking like a data scientistYogita Bansal
The document provides steps for starting to think like a data scientist without needing a technical background. It outlines a 6 step process: 1) Start with an interesting work-related question, 2) Identify relevant data sources, 3) Collect the data, 4) Modify your approach as needed, 5) Analyze the data to answer your original question, and 6) Repeat the process by posing new questions. The goal is to open your eyes to data opportunities and insights through an iterative learning process.
The document discusses quality control and creative thinking. It suggests that problems should be made smaller while small problems are quickly solved. It then discusses how brand strategists can deal with quality control and industrial engineering through applying 4 season country QA/QC paradigms in Indonesia. Creative feeling and thinking are presented as solutions to dealing with constant change, collective insecurity, and reinventing life through techniques like brainstorming, lateral thinking, and SCAMPER.
Why is that when we present facts alone, we can get met with resistance? Is there another way to influence? We discuss how storytelling in technical talks, when done right, can make your ideas more memorable and influential.
Manage Outcomes to Maximize Impact | Presented by Cole Costanzo, Senior Vice ...Melanie Barrett
How do you know if your organization is making a real difference? Master the art of managing and measuring outcomes and you will raise more money and achieve a greater impact. In this presentation, Cole Costanzo, Senior Vice President at Dickerson, Bakker & Associates, will cover the following outcomes:
1) Identify what you should be measuring, and how to establish impact-reporting systems,
2) Monitor progress toward goals, and use feedback loops to understand what's working and what's not, and
3) Incorporate best practices and emerging standards to build an outcomes-centered culture at your organization.
Scientific management and other leading techniques of a modern CPA firmEd Kless
This document discusses scientific management and efficiency in professional project management. It provides an overview of Frederick Taylor's principles of scientific management, which aim to maximize efficiency by breaking down jobs, timing tasks, eliminating unnecessary steps, and incentivizing workers to meet optimal times. The document also discusses how timesheets are critical as pricing, cost accounting, efficiency measurement, and project management tools. It provides examples of efficiency metrics like budget at completion, actual costs, planned value, earned value, cost variance, and performance indexes. Finally, it promotes the Leadership Education for Accounting Professionals program for continuing professional education.
Using Data Visibility to Drive Business PerformanceMicrosolve
A short presentation on the ’10 things you need to get right’ to use data visibility solutions to drive business performance. The author has many years of experience featuring success and failure in this space.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
Creating a data-driven organization requires developing a data-driven culture. Key aspects of a data-driven culture include having a strong testing culture that encourages hypothesis generation and experimentation, an open and sharing culture without data silos, a self-service culture where business units have necessary data access and analytical skills, and broad data literacy across all decision makers. Ultimately, an organization is data-driven when it uses data to drive impact and business results by pushing data through an analytics value chain from collection to analysis to decisions and actions. Maintaining a data-driven culture requires continuous effort as well as data leadership from a chief data or analytics officer.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Measuring the Business Impact of Learning Workshop. Royal Institution, London...Gareth Jones
These slides are from a workshop for senior learning and development leaders to explore how to measure the business impact of learning. Facilitated by LEO Learning, and supported by Towards Maturity and Watershed, it explored how to align training to business strategy, develop a measurement strategy and how to use a big data approach to track the impact on business performance. It was held in October 2017 at the Royal Institute in London
2 in 1 - Blending learning and km for business transformation and competitive...Alexandra Lederer
Presented at Work 2.0 Conference, Sydney - October 2016
• Competitive edge: repositioning the learning agenda around critical knowledge transfer to sustain competitive advantage
• Culture shift: transforming the business to a culture of peer to peer learning, practice sharing and collaboration
• Co-ownership: crafting sustainable, engaging and equitable learning solutions with business leaders
• Co-creation: upskilling and leveraging subject matter experts to create a continuous micro learning organization
The situational analysis is an important part of the strategic planning process where an organization analyzes its current internal and external situation. This analysis helps identify strengths, weaknesses, opportunities, and threats (SWOT analysis).
The situational analysis involves evaluating both internal factors such as resources, competencies, processes etc. and external factors such as market trends, competition, economic conditions, regulations etc. This comprehensive evaluation of the organization and its environment helps identify strategic issues and informs the development of objectives and strategies. A well-conducted situational analysis lays the foundation for effective strategic decision making.
7f. How Can a Company Gain Competitive Advantage?
There are several ways a company can gain competitive advantage including:
1
What are the characteristics of research?Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.The analysis is based on logical reasoning and involves both inductive and deductive methods.Real-time data and knowledge is derived from actual observations in natural settings.There is an in-depth analysis of all data collected so that there are no anomalies associated with it.It creates a path for generating new questions. Existing data helps create more research opportunities.It is analytical and uses all the available data so that there is no ambiguity in inference.Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.Create memorable experiences based on real-time data, insights and advanced analysis.
GreenBiz 17 Tutorial Slides: "Transformative Organizational Success through L...GreenBiz Group
Many sustainability programs struggle because they are developed or integrated in ways that miss important organizational dimensions. Participants will learn how to incorporate four key pillars of success for lasting, sustainable change: leadership, strategy, communication and global-context. This cross-functional team of expert practitioners and faculty will provide insights on how to:
Create and identify sustainability strategies that promote broad organizational success through an effective suite of actions.
Apply global sustainability principles to your specific organizational context by integrating your organization's own perspective through a lens of sustainability with a global-context.
Employ leadership competencies and behaviors that are critical to leading lasting, transformational change.
Communicate effectively about sustainability with key stakeholders and audiences.
The document provides an outline for a training on fundamentals of data analytics. It introduces the presenter, Daniel Meyer, who has over 20 years of experience in higher education, business process outsourcing, and financial services. The agenda covers topics such as descriptive, predictive, and prescriptive analytics, finding and using data, and driving decisions with data analytics. It also discusses challenges around big data and unstructured data, and the importance of business intelligence, data visualization, and data-driven decision making.
Business leaders everywhere are looking to data to inform their decision making. Accompanying this demand are misunderstandings of what it takes to transform data into something that can inform a decision. What is the data infrastructure required? In this talk, I'll dispel some of these misunderstandings and discuss what it takes to build good data infrastructure. I'll discuss the components of a good data infrastructure. The best practices and available tools for gathering data, processing it, storing it, analyzing it and communicating the results. The goal is for these components to create a data infrastructure which can evolve from simple reporting to sophisticated insights for decision making.
Presented at OpenWest 2018
Learning Analytics Primer: Getting Started with Learning and Performance Anal...Watershed
Navigating the scope of disruptive analytics solutions to deliver maximum impact. Learn more about the importance of scalable learning in organizations that want to embrace an environment of continuous improvement. Mike Rustici provides a workshop on the five steps to get started with learning and performance analytics. Ranging from gathering your data using methods like experience API, to setting metrics and evaluating impact of learning programs.
This document discusses the need to move beyond traditional advertising metrics and instead focus on measuring relevance and engagement with consumers. It advocates connecting how brand communications can meet consumer needs and interests at different moments in their lifecycle. A new measurement framework is proposed that profiles opportunity moments, the consumer context, and aligns brand and customer goals. Metrics would holistically assess attitudinal, behavioral and experiential factors. The goal is to facilitate customer-brand experiences that benefit both parties.
The document discusses the importance of focusing on outcomes over outputs for team performance. It argues that teams perform best when they have a clear, measurable purpose and understand how their work impacts outcomes. This is illustrated through the example of NASA's mission to return Apollo 13's crew safely to Earth. The document advises defining an inspiring outcome-focused problem, establishing baseline metrics and success criteria, and breaking the problem down into sub-problems that each connect to and help achieve the overall outcome. Regularly measuring impacts on outcomes allows teams to prioritize, make data-driven decisions, and stay aligned on a shared vision and purpose.
The document outlines an idea workshop focused on determining strategic initiatives or "seeds" for an organization. It provides guidance on what makes a good seed, including being a multi-year goal that allows progress towards a larger objective. The document also covers brainstorming principles and a process for theme generation, grouping, voting and idea exercises to identify priority seeds.
This document outlines a strategic planning process for an organization called AIA. It includes sections on understanding needs, purpose, goals, categories of involvement, milestones, ideas, roadblocks, resources, and keeping the main priorities the top focus. The overall purpose is to move from vision to action by identifying wildly important goals.
Effectuation Overview by Insights IgnitedBeth Crooker
Insights Ignited (http://www.insightsignited.com) gives an overview of Effectuation - the mindset successful entrepreneurs use to build new ventures, as discovered by Dr. Saras Sarasvathy at UVA Darden's School of Business.
How to start thinking like a data scientistYogita Bansal
The document provides steps for starting to think like a data scientist without needing a technical background. It outlines a 6 step process: 1) Start with an interesting work-related question, 2) Identify relevant data sources, 3) Collect the data, 4) Modify your approach as needed, 5) Analyze the data to answer your original question, and 6) Repeat the process by posing new questions. The goal is to open your eyes to data opportunities and insights through an iterative learning process.
The document discusses quality control and creative thinking. It suggests that problems should be made smaller while small problems are quickly solved. It then discusses how brand strategists can deal with quality control and industrial engineering through applying 4 season country QA/QC paradigms in Indonesia. Creative feeling and thinking are presented as solutions to dealing with constant change, collective insecurity, and reinventing life through techniques like brainstorming, lateral thinking, and SCAMPER.
Why is that when we present facts alone, we can get met with resistance? Is there another way to influence? We discuss how storytelling in technical talks, when done right, can make your ideas more memorable and influential.
Manage Outcomes to Maximize Impact | Presented by Cole Costanzo, Senior Vice ...Melanie Barrett
How do you know if your organization is making a real difference? Master the art of managing and measuring outcomes and you will raise more money and achieve a greater impact. In this presentation, Cole Costanzo, Senior Vice President at Dickerson, Bakker & Associates, will cover the following outcomes:
1) Identify what you should be measuring, and how to establish impact-reporting systems,
2) Monitor progress toward goals, and use feedback loops to understand what's working and what's not, and
3) Incorporate best practices and emerging standards to build an outcomes-centered culture at your organization.
Scientific management and other leading techniques of a modern CPA firmEd Kless
This document discusses scientific management and efficiency in professional project management. It provides an overview of Frederick Taylor's principles of scientific management, which aim to maximize efficiency by breaking down jobs, timing tasks, eliminating unnecessary steps, and incentivizing workers to meet optimal times. The document also discusses how timesheets are critical as pricing, cost accounting, efficiency measurement, and project management tools. It provides examples of efficiency metrics like budget at completion, actual costs, planned value, earned value, cost variance, and performance indexes. Finally, it promotes the Leadership Education for Accounting Professionals program for continuing professional education.
Using Data Visibility to Drive Business PerformanceMicrosolve
A short presentation on the ’10 things you need to get right’ to use data visibility solutions to drive business performance. The author has many years of experience featuring success and failure in this space.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
Creating a data-driven organization requires developing a data-driven culture. Key aspects of a data-driven culture include having a strong testing culture that encourages hypothesis generation and experimentation, an open and sharing culture without data silos, a self-service culture where business units have necessary data access and analytical skills, and broad data literacy across all decision makers. Ultimately, an organization is data-driven when it uses data to drive impact and business results by pushing data through an analytics value chain from collection to analysis to decisions and actions. Maintaining a data-driven culture requires continuous effort as well as data leadership from a chief data or analytics officer.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Measuring the Business Impact of Learning Workshop. Royal Institution, London...Gareth Jones
These slides are from a workshop for senior learning and development leaders to explore how to measure the business impact of learning. Facilitated by LEO Learning, and supported by Towards Maturity and Watershed, it explored how to align training to business strategy, develop a measurement strategy and how to use a big data approach to track the impact on business performance. It was held in October 2017 at the Royal Institute in London
2 in 1 - Blending learning and km for business transformation and competitive...Alexandra Lederer
Presented at Work 2.0 Conference, Sydney - October 2016
• Competitive edge: repositioning the learning agenda around critical knowledge transfer to sustain competitive advantage
• Culture shift: transforming the business to a culture of peer to peer learning, practice sharing and collaboration
• Co-ownership: crafting sustainable, engaging and equitable learning solutions with business leaders
• Co-creation: upskilling and leveraging subject matter experts to create a continuous micro learning organization
The situational analysis is an important part of the strategic planning process where an organization analyzes its current internal and external situation. This analysis helps identify strengths, weaknesses, opportunities, and threats (SWOT analysis).
The situational analysis involves evaluating both internal factors such as resources, competencies, processes etc. and external factors such as market trends, competition, economic conditions, regulations etc. This comprehensive evaluation of the organization and its environment helps identify strategic issues and informs the development of objectives and strategies. A well-conducted situational analysis lays the foundation for effective strategic decision making.
7f. How Can a Company Gain Competitive Advantage?
There are several ways a company can gain competitive advantage including:
1
What are the characteristics of research?Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.The analysis is based on logical reasoning and involves both inductive and deductive methods.Real-time data and knowledge is derived from actual observations in natural settings.There is an in-depth analysis of all data collected so that there are no anomalies associated with it.It creates a path for generating new questions. Existing data helps create more research opportunities.It is analytical and uses all the available data so that there is no ambiguity in inference.Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.Create memorable experiences based on real-time data, insights and advanced analysis.
GreenBiz 17 Tutorial Slides: "Transformative Organizational Success through L...GreenBiz Group
Many sustainability programs struggle because they are developed or integrated in ways that miss important organizational dimensions. Participants will learn how to incorporate four key pillars of success for lasting, sustainable change: leadership, strategy, communication and global-context. This cross-functional team of expert practitioners and faculty will provide insights on how to:
Create and identify sustainability strategies that promote broad organizational success through an effective suite of actions.
Apply global sustainability principles to your specific organizational context by integrating your organization's own perspective through a lens of sustainability with a global-context.
Employ leadership competencies and behaviors that are critical to leading lasting, transformational change.
Communicate effectively about sustainability with key stakeholders and audiences.
The document provides an outline for a training on fundamentals of data analytics. It introduces the presenter, Daniel Meyer, who has over 20 years of experience in higher education, business process outsourcing, and financial services. The agenda covers topics such as descriptive, predictive, and prescriptive analytics, finding and using data, and driving decisions with data analytics. It also discusses challenges around big data and unstructured data, and the importance of business intelligence, data visualization, and data-driven decision making.
Business leaders everywhere are looking to data to inform their decision making. Accompanying this demand are misunderstandings of what it takes to transform data into something that can inform a decision. What is the data infrastructure required? In this talk, I'll dispel some of these misunderstandings and discuss what it takes to build good data infrastructure. I'll discuss the components of a good data infrastructure. The best practices and available tools for gathering data, processing it, storing it, analyzing it and communicating the results. The goal is for these components to create a data infrastructure which can evolve from simple reporting to sophisticated insights for decision making.
Presented at OpenWest 2018
Learning Analytics Primer: Getting Started with Learning and Performance Anal...Watershed
Navigating the scope of disruptive analytics solutions to deliver maximum impact. Learn more about the importance of scalable learning in organizations that want to embrace an environment of continuous improvement. Mike Rustici provides a workshop on the five steps to get started with learning and performance analytics. Ranging from gathering your data using methods like experience API, to setting metrics and evaluating impact of learning programs.
This document discusses the need to move beyond traditional advertising metrics and instead focus on measuring relevance and engagement with consumers. It advocates connecting how brand communications can meet consumer needs and interests at different moments in their lifecycle. A new measurement framework is proposed that profiles opportunity moments, the consumer context, and aligns brand and customer goals. Metrics would holistically assess attitudinal, behavioral and experiential factors. The goal is to facilitate customer-brand experiences that benefit both parties.
Despite Learning measurement frameworks like Kirkpatrick and Philips ROI that have been around for so many years, defining meaningful measures still continues to be a big challenge for L&D. ‘E’ has become the most ignored in ADDIE.
We talk to an experienced panel about the unsatisfactory current state and what needs to be done to improve the importance, visibility and value of measuring Learning effectiveness in the real world. We focus on how to collect actionable insights about learning effectiveness: not only seeking to answer, did learning achieve the desired or intended result, but also why/why not.
This document provides an overview of measuring success and improvement. It discusses choosing the right measures, defining measures, collecting and analyzing data, and reviewing measures over time. Key points include focusing on outcome measures, using process measures to understand how outcomes are achieved, establishing clear definitions for each measure, and reviewing measures regularly to understand change over time and inform next steps. Visualizing data through charts and run charts is also discussed as an important part of analysis and presentation to tell the story behind the measures.
Keynote: Innovation, Leadership, and PsychologyIkhlaq Sidhu
This document discusses innovation leadership and psychology from the perspective of Ikhlaq Sidhu, Founding Director of the Sutardja Center for Entrepreneurship & Technology at UC Berkeley. The Center's approach brings executives and entrepreneurs into the classroom and labs to teach 1500 undergraduates and 100 graduate students. Their recipe focuses on mindset and behaviors rather than just business training. They have found that the key missing ingredient for innovation is behaviors and mindsets that allow people to utilize their core capabilities. The Center aims to provide depth in valued areas along with teaching entrepreneurial behaviors and mindsets.
This document provides an introduction and overview of the marketing research course. It outlines the teaching staff, course objectives, structure, assessments, and schedule. Key points:
- The course is taught by Dr. Steven Lu, who has a PhD in Marketing and experience publishing and consulting.
- The objectives are to introduce applied marketing research tools and teach the fundamentals of producing quality market research.
- Assessments include two exams, a term project conducted in stages involving a market research study, and class participation.
- The schedule provides an outline of the topics to be covered each week, including secondary research, qualitative research methods, surveys, sampling, and data analysis.
The document provides information on the importance of market research and information for schools. It discusses three sources of information - internal records, third party sources, and primary research. It highlights several issues with research including knowing when it will be useful, counting metrics properly, blind benchmarking, using data well, institutional biases, and undervaluing design. Sample research topics are presented like image and positioning studies, alumni surveys, and external market data sources. Tips are provided for better information gathering including having a multi-year research agenda and leveraging the process. Concerns with overreliance on web surveys are also discussed.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
6. Part 2
Stand in height order
Observations
Information = Usable
7. How could it be used
Observations
Knowledge = Valuable
Part 3
8. “Science is the study of the nature
and behaviour of natural things
and the knowledge that we obtain
about them.” collinsdictionary
“Scientist is someone who
systematically gathers and uses
research and evidence, making a
hypothesis and testing it, to gain
and share understanding and
knowledge.” sciencecouncil.org
Data Science
Why Data Science?
Data
• Raw Material
Science
• Latin ‘Scire’ to know
Scientist
• Knowledge Broker
9. 1
2
3
9
Recap
Data is just a raw material
Value derived when information is applied
Data Scientist are Knowledge Brokers
17. How to Guide
1. Understand strategic
context
2. Define value aligned to
goals
3. Ensure value delivery
18. Economic
EnviroSocial
S W
O T
1. Strategic Context
a. Internal Strengths &
Weaknesses
b. External Opportunities &
Threats
c. 4 categories initiating
Objectives
Survive
Continue
Combo
Grow
19. 2. Aligned to Goals
a. Identify goals that will
benefit
b. Define and quantify the
value
c. Prioritise by value