Data Natives 2015: Predictive Applications are Going to Steal Your Job: this ...Lars Trieloff
Fears of robots taking away blue collar jobs have been coming and going over the last decade. But this time it’s different: a new breed of predictive applications, or white-collar robots are going after knowledge-worker and managerial jobs. Using automated data-driven decisions, they speed up and improve critical business processes and leave employers and employee’s scratching their heads what is coming next. Lars Trieloff, who is building predictive applications for a living at Blue Yonder explains what happens, why it happens and what it means for you (and your boss).
Big Data Berlin – Automating Decisions is the Next Frontier for Big DataLars Trieloff
Just collecting, storing and analyzing data is not enough. In order to benefit from it, you have to overcome organizational and human inertia and establish automated processes that use insights gained from your data.
This presentation has been presented at http://dataconomy.com/28-august-2014-big-data-berlin/
Big data is data that is too large to process with traditional software. As computers get smaller, cheaper, and more powerful, more computing resources can be applied to big data through cloud computing. Machine learning algorithms can analyze big data to build predictive applications that forecast outcomes and optimize decisions. However, enterprises have doubts and concerns about adopting predictive applications due to issues around data availability, predictability, understandability, and ensuring the results can be executed on.
Smartcon 2015 – Automated Decisions in the Supply ChainLars Trieloff
This document discusses the process of automating decisions using predictive applications and machine learning models. It begins by outlining how predictive applications work by collecting and storing data, analyzing correlations, building decision models, and deciding and testing outcomes. The document then discusses challenges like predicting demand and order quantities. It provides an example of using sales forecasts and probability distributions to determine optimal order amounts while minimizing stock-out risks. Finally, it discusses how enterprises adopt predictive applications, addressing concerns around data availability, predictability, understandability, and executability, and outlines the potential financial impacts.
Automated decision making with predictive applications – Big Data BrusselsLars Trieloff
This document discusses automated decision making with big data and predictive applications. It begins by looking at how decisions are currently made, which is often based on qualitative factors rather than data-driven insights. It then examines how predictive applications work by collecting and analyzing data to build models that can make decisions and be tested and optimized. The document argues that predictive applications can help reduce risk and costs while increasing revenue by enabling trends to be estimated, classifications to be made, and events to be predicted to optimize returns. It presents the idea of having a common platform for building, running, and monitoring predictive applications using both internal and external data.
Automated Decision making with Predictive Applications – Big Data HamburgLars Trieloff
Most businesses are making most decisions the way Lizards do: based on very simple reflex-response patterns and let cognitive biases taint their decision making. Instead of letting gut feel and biases take over, predictive applications make decisions fast, cheap and fact-based.
Automated decision making using Predictive Applications – Big Data ParisLars Trieloff
Predictive Applications enable automated data-driven decisions using big data, machine learning, artificial intelligence and optimization algorithms. With this, they are able to scale decision making, improve the quality of decisions and circumvent cognitive biases that cloud human decision making.
Data Natives 2015: Predictive Applications are Going to Steal Your Job: this ...Lars Trieloff
Fears of robots taking away blue collar jobs have been coming and going over the last decade. But this time it’s different: a new breed of predictive applications, or white-collar robots are going after knowledge-worker and managerial jobs. Using automated data-driven decisions, they speed up and improve critical business processes and leave employers and employee’s scratching their heads what is coming next. Lars Trieloff, who is building predictive applications for a living at Blue Yonder explains what happens, why it happens and what it means for you (and your boss).
Big Data Berlin – Automating Decisions is the Next Frontier for Big DataLars Trieloff
Just collecting, storing and analyzing data is not enough. In order to benefit from it, you have to overcome organizational and human inertia and establish automated processes that use insights gained from your data.
This presentation has been presented at http://dataconomy.com/28-august-2014-big-data-berlin/
Big data is data that is too large to process with traditional software. As computers get smaller, cheaper, and more powerful, more computing resources can be applied to big data through cloud computing. Machine learning algorithms can analyze big data to build predictive applications that forecast outcomes and optimize decisions. However, enterprises have doubts and concerns about adopting predictive applications due to issues around data availability, predictability, understandability, and ensuring the results can be executed on.
Smartcon 2015 – Automated Decisions in the Supply ChainLars Trieloff
This document discusses the process of automating decisions using predictive applications and machine learning models. It begins by outlining how predictive applications work by collecting and storing data, analyzing correlations, building decision models, and deciding and testing outcomes. The document then discusses challenges like predicting demand and order quantities. It provides an example of using sales forecasts and probability distributions to determine optimal order amounts while minimizing stock-out risks. Finally, it discusses how enterprises adopt predictive applications, addressing concerns around data availability, predictability, understandability, and executability, and outlines the potential financial impacts.
Automated decision making with predictive applications – Big Data BrusselsLars Trieloff
This document discusses automated decision making with big data and predictive applications. It begins by looking at how decisions are currently made, which is often based on qualitative factors rather than data-driven insights. It then examines how predictive applications work by collecting and analyzing data to build models that can make decisions and be tested and optimized. The document argues that predictive applications can help reduce risk and costs while increasing revenue by enabling trends to be estimated, classifications to be made, and events to be predicted to optimize returns. It presents the idea of having a common platform for building, running, and monitoring predictive applications using both internal and external data.
Automated Decision making with Predictive Applications – Big Data HamburgLars Trieloff
Most businesses are making most decisions the way Lizards do: based on very simple reflex-response patterns and let cognitive biases taint their decision making. Instead of letting gut feel and biases take over, predictive applications make decisions fast, cheap and fact-based.
Automated decision making using Predictive Applications – Big Data ParisLars Trieloff
Predictive Applications enable automated data-driven decisions using big data, machine learning, artificial intelligence and optimization algorithms. With this, they are able to scale decision making, improve the quality of decisions and circumvent cognitive biases that cloud human decision making.
Automated Decision Making with Predictive Applications – Big Data DüsseldorfLars Trieloff
Another installment and iteration of my talk on predictive applications, automated decision making and why cognitive biases prevent us from making the best decisions at scale
Invisible Boxes - Why Parts of Your Web Design are Not Seen Neo Insight
Lisa Fast presented examples of Invisible Boxes in a webinar with Gerry McGovern and at UXCamp Ottawa in November 2014. Invisible boxes are boxes and images in your web page design that simply are seen when people use the site to perform tasks. Lisa explains the digital psychology underpinnings of why the boxes aren't seen (Gestalt principles, Inattentional blindness, priming by ads). Understanding these principles can help you avoid invisible boxes in your web designs.
Become an Exponential Organization, Change the World FasterGary A. Bolles
A talk to the NetHope annual summit, an amazing group of 50+ non-profit organizations from around the world. As I told the attendees, I should have titled this, "Become an Exponential Organization, Help the World Change the World Faster" - how you can help affected populations to help themselves.
Brain Hacking: Using behavioural economics and consumer psychology to improve...David Greenwood
Security is a feeling, based not solely on probabilities and mathematical calculations, but on your psychological reactions to both risks and countermeasures. You might feel that you're at high risk of burglary, medium risk of murder, and low risk of identity theft. And your neighbour, in the exact same situation, might feel that he's at high risk of identity theft, medium risk of burglary, and low risk of murder.
You can be secure even though you don't feel secure. And you can feel secure even though you're not. Learn why we’re predictably irrational, and how you use this new found knowledge to nudge consumers to make better cybersecurity decisions.
Presented at BSides Belfast, 7th September 2017.
https://www.youtube.com/watch?v=uHpXt-PItdk&feature=youtu.be&t=1s
David Turnbull, cofounder and CCO Snapshot, at Travel Tech Conference Russia 2017 (http://traveltechcon.ru/eng).
"As the debate surrounding the dominance of OTA's and who truly "owns" the customer intensifies, David takes an amusing but critical look at the current state of data management within the hospitality sector and why this is preventing the significant leaps in customer experience achieved by other industries".
Subscribe to TTCR news: http://eepurl.com/cnhNvH
Is it enough to design for a great patient experience, improved health outcomes, and overall cost reductions in health care? While incentives may soon change, the idea of data-driven solutions to improve health care is not a new one. Yet why have technological solutions so frequently fail on all three of the triple aims? We need to be able to ask deeper questions, and experiment with more humanistic approaches.
Looking at specific interaction examples from incumbents and startups in health tech, I will contrast the current approaches for data-driven solution development, and how they fall short at the moment of interaction. Incumbents deploy top down approaches that comply with regulation, and meet the needs of payers and providers, but famously fail to deliver engaging patient and practitioner experiences. New entrants want to disrupt the entire system, but often struggle to understand deep unmet patient needs, and how to demonstrate evidence-based outcomes.
For each solution born onto the health tech scene, can we ask: Are patient’s lives enhanced by the addition of data? Do doctors become more wise? Do nurses feel more empowered? Do spouses know how to effectively intervene? Do adult children of aging parents get more time in their overly stretched days? And do these collective interactions actually result in improved population health?
This talk will outline an approach to design for a higher aim and enhance the lives of everyone who seeks care from the health care system.
"The Unintended Consequences of Beating Users with Carrot Sticks: Radical Thoughts on Security Reform" Presentation by
Benjamin Tomhave at OWASP 2010 AppSec DC Cofnerence. Uploading here for non-mac users. (http://www.owasp.org/index.php/The_Unintended_Consequences_of_Beating_Users_with_Carrot_Sticks:_Radical_Thoughts_on_Security_Reform)
The document discusses the concept of a "Just Culture" which balances accountability for human errors, at-risk behaviors, and reckless behaviors. It recognizes that humans can and will make mistakes through human error or lapses. A Just Culture deals with behaviors and categorizes them based on whether they were due to human error, at-risk behaviors where risks weren't recognized, or reckless behaviors where risks were recognized.
Black Swan Risk Management - Aditya YadavAditya Yadav
This document discusses managing risks from "black swan" events, which are rare events with severe consequences that are often rationalized with hindsight. The author argues that a probabilistic or statistical approach is inappropriate for black swan risk management. Instead, organizations should use scenario-based modeling to simulate assumption failures, identify model sanity checks, and prepare reactive measures. The key is having a general consensus on risk themes and practices for different categories of model breakdowns, rather than rigid procedures, so people understand risks mentally.
Behavioral Economics At Work Nunnally, Steadman, Baxter Las Vegas Finalksteadman
The document summarizes a presentation on behavioral economics and judgment risk given by Tyler Nunnally, the founder and CEO of Upside Risk. The presentation discusses concepts from behavioral economics like heuristics and biases that can lead to judgment errors, and examines how risk appetite can impact decision making and business performance. Best practices for managing judgment risk and reducing biases are also covered.
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...Protectionandmanagement
Want to change people's behaviour just ask (and nudge, hug, shove and smack) - Joseph Williams (Carbon Trust) - Energy & Environment Expo, 18 June 2014
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityEric Garland
In this presentation for the Intelligence Collaborative, I explore cognitive bias - social, decision, probability, and memory - and its effect distortion clear thinking about strategy and decision making. This is part of of my executive training course "Executive Mind Traps.
Accelerated finance and tech leadershipTapp Commerce
We’re super excited being part of the accelerated agenda of intersection economies. Technology is the enabler, self-learning systems constantly enhance the lives of individuals and optimise merchant locations extending reach across suburbs, amplifying impact on cash society.
Tapp platform contributes to well-being of millions of consumers, narrows inequality and pushes cash economy to further impact the stability of emerging countries.
Please find a collection of technologies, AI, forecasting, game changer opportunities and conclusions of how the world stands. We’re pulling economies towards stability while providing people the opportunity to choose for themselves.
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...Eric Garland
A presentation on how our current situation of global economic transition requires a new approach to organizational learning and decision making. We are ending the era of authoritarian intelligence and moving toward more of a peer-to-peer approach toward decoding changes in the world.
For more check out https://www.competitivefutures.com/ and http://www.ericgarland.co/keynote-speaker-executive-educator/
The document discusses how the workplace is changing and becoming more social in nature. It argues that while bureaucracy and silos served purposes in the past, organizations must now master complexity, deal with shifting boundaries, and remove friction. Acknowledging the social nature of business is key to adapting to changes in society and the convergence of technologies that are blurring traditional boundaries.
This document summarizes a presentation about fostering a DevOps culture. It discusses how technology can provide trust through automation, but culture and people are difficult to change. It suggests using behavioral economics and creating diverse teams to encourage different perspectives. Other suggestions to accelerate organizations include using incentives, empowering change, and addressing issues like fear, anger and suffering that some may feel about changes. While equilibrium sounds good, technology organizations can get stuck in "bad equilibrium" and need to break out of inefficient, undesirable states to improve.
Finding out what could go wrong before it does – Modelling Risk and UncertaintyBruce Edmonds
The document discusses challenges with using models to predict outcomes for complex systems and situations. It describes how classic policy modeling approaches often make simplifying assumptions that may not accurately capture real-world complexity. Specifically, statistical models assume fixed relationships that don't account for heterogeneity; microsimulations and CGE models only model simple systems and make strong assumptions; and system dynamics and simulation models have limitations due to unknown parameters and structural changes. The document advocates approaches that rapidly sense and react to complex, uncertain systems instead of trying to predict them, as predicting complex, unpredictable situations can provide false confidence and lead to unforeseen consequences.
Vlerick HRday 2013: Men versus machine, who wins? - Prof. Marc BuelensVlerick Business School
This document discusses the increasing use of big data and analytics in human resources. It provides examples of how data can be used to predict job performance, sales performance, and who may not be suitable for customer support roles. The document also discusses research comparing human judgment to statistical models in making predictions. While statistical models often outperform experts, combining multiple predictions from humans and models tends to provide the most accurate forecasts. Intuition alone is unlikely to be valid without direct experience and the ability to learn from mistakes. In conclusion, the document advocates applying what is already known about improving predictions by using simple models, multiple independent predictions, and combining human and machine judgments.
Automated decision making with predictive applications – Big Data AmsterdamLars Trieloff
My slides from tonight's talk at Impact HUB in Amsterdam on big data, machine learning, cognitive biases and how to overcome them with predictive applications.
The document discusses the Lean Startup methodology. It introduces key Lean Startup principles like entrepreneurs are everywhere, entrepreneurship is management, validated learning, build-measure-learn, and innovation accounting. It emphasizes the importance of the minimum viable product to test ideas quickly and learn through customer feedback, continuous deployment to learn from customers rapidly, and using metrics like split testing to validate hypotheses. The overall goal is to minimize the time and resources spent on products that do not meet customer needs.
Automated Decision Making with Predictive Applications – Big Data DüsseldorfLars Trieloff
Another installment and iteration of my talk on predictive applications, automated decision making and why cognitive biases prevent us from making the best decisions at scale
Invisible Boxes - Why Parts of Your Web Design are Not Seen Neo Insight
Lisa Fast presented examples of Invisible Boxes in a webinar with Gerry McGovern and at UXCamp Ottawa in November 2014. Invisible boxes are boxes and images in your web page design that simply are seen when people use the site to perform tasks. Lisa explains the digital psychology underpinnings of why the boxes aren't seen (Gestalt principles, Inattentional blindness, priming by ads). Understanding these principles can help you avoid invisible boxes in your web designs.
Become an Exponential Organization, Change the World FasterGary A. Bolles
A talk to the NetHope annual summit, an amazing group of 50+ non-profit organizations from around the world. As I told the attendees, I should have titled this, "Become an Exponential Organization, Help the World Change the World Faster" - how you can help affected populations to help themselves.
Brain Hacking: Using behavioural economics and consumer psychology to improve...David Greenwood
Security is a feeling, based not solely on probabilities and mathematical calculations, but on your psychological reactions to both risks and countermeasures. You might feel that you're at high risk of burglary, medium risk of murder, and low risk of identity theft. And your neighbour, in the exact same situation, might feel that he's at high risk of identity theft, medium risk of burglary, and low risk of murder.
You can be secure even though you don't feel secure. And you can feel secure even though you're not. Learn why we’re predictably irrational, and how you use this new found knowledge to nudge consumers to make better cybersecurity decisions.
Presented at BSides Belfast, 7th September 2017.
https://www.youtube.com/watch?v=uHpXt-PItdk&feature=youtu.be&t=1s
David Turnbull, cofounder and CCO Snapshot, at Travel Tech Conference Russia 2017 (http://traveltechcon.ru/eng).
"As the debate surrounding the dominance of OTA's and who truly "owns" the customer intensifies, David takes an amusing but critical look at the current state of data management within the hospitality sector and why this is preventing the significant leaps in customer experience achieved by other industries".
Subscribe to TTCR news: http://eepurl.com/cnhNvH
Is it enough to design for a great patient experience, improved health outcomes, and overall cost reductions in health care? While incentives may soon change, the idea of data-driven solutions to improve health care is not a new one. Yet why have technological solutions so frequently fail on all three of the triple aims? We need to be able to ask deeper questions, and experiment with more humanistic approaches.
Looking at specific interaction examples from incumbents and startups in health tech, I will contrast the current approaches for data-driven solution development, and how they fall short at the moment of interaction. Incumbents deploy top down approaches that comply with regulation, and meet the needs of payers and providers, but famously fail to deliver engaging patient and practitioner experiences. New entrants want to disrupt the entire system, but often struggle to understand deep unmet patient needs, and how to demonstrate evidence-based outcomes.
For each solution born onto the health tech scene, can we ask: Are patient’s lives enhanced by the addition of data? Do doctors become more wise? Do nurses feel more empowered? Do spouses know how to effectively intervene? Do adult children of aging parents get more time in their overly stretched days? And do these collective interactions actually result in improved population health?
This talk will outline an approach to design for a higher aim and enhance the lives of everyone who seeks care from the health care system.
"The Unintended Consequences of Beating Users with Carrot Sticks: Radical Thoughts on Security Reform" Presentation by
Benjamin Tomhave at OWASP 2010 AppSec DC Cofnerence. Uploading here for non-mac users. (http://www.owasp.org/index.php/The_Unintended_Consequences_of_Beating_Users_with_Carrot_Sticks:_Radical_Thoughts_on_Security_Reform)
The document discusses the concept of a "Just Culture" which balances accountability for human errors, at-risk behaviors, and reckless behaviors. It recognizes that humans can and will make mistakes through human error or lapses. A Just Culture deals with behaviors and categorizes them based on whether they were due to human error, at-risk behaviors where risks weren't recognized, or reckless behaviors where risks were recognized.
Black Swan Risk Management - Aditya YadavAditya Yadav
This document discusses managing risks from "black swan" events, which are rare events with severe consequences that are often rationalized with hindsight. The author argues that a probabilistic or statistical approach is inappropriate for black swan risk management. Instead, organizations should use scenario-based modeling to simulate assumption failures, identify model sanity checks, and prepare reactive measures. The key is having a general consensus on risk themes and practices for different categories of model breakdowns, rather than rigid procedures, so people understand risks mentally.
Behavioral Economics At Work Nunnally, Steadman, Baxter Las Vegas Finalksteadman
The document summarizes a presentation on behavioral economics and judgment risk given by Tyler Nunnally, the founder and CEO of Upside Risk. The presentation discusses concepts from behavioral economics like heuristics and biases that can lead to judgment errors, and examines how risk appetite can impact decision making and business performance. Best practices for managing judgment risk and reducing biases are also covered.
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...Protectionandmanagement
Want to change people's behaviour just ask (and nudge, hug, shove and smack) - Joseph Williams (Carbon Trust) - Energy & Environment Expo, 18 June 2014
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityEric Garland
In this presentation for the Intelligence Collaborative, I explore cognitive bias - social, decision, probability, and memory - and its effect distortion clear thinking about strategy and decision making. This is part of of my executive training course "Executive Mind Traps.
Accelerated finance and tech leadershipTapp Commerce
We’re super excited being part of the accelerated agenda of intersection economies. Technology is the enabler, self-learning systems constantly enhance the lives of individuals and optimise merchant locations extending reach across suburbs, amplifying impact on cash society.
Tapp platform contributes to well-being of millions of consumers, narrows inequality and pushes cash economy to further impact the stability of emerging countries.
Please find a collection of technologies, AI, forecasting, game changer opportunities and conclusions of how the world stands. We’re pulling economies towards stability while providing people the opportunity to choose for themselves.
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...Eric Garland
A presentation on how our current situation of global economic transition requires a new approach to organizational learning and decision making. We are ending the era of authoritarian intelligence and moving toward more of a peer-to-peer approach toward decoding changes in the world.
For more check out https://www.competitivefutures.com/ and http://www.ericgarland.co/keynote-speaker-executive-educator/
The document discusses how the workplace is changing and becoming more social in nature. It argues that while bureaucracy and silos served purposes in the past, organizations must now master complexity, deal with shifting boundaries, and remove friction. Acknowledging the social nature of business is key to adapting to changes in society and the convergence of technologies that are blurring traditional boundaries.
This document summarizes a presentation about fostering a DevOps culture. It discusses how technology can provide trust through automation, but culture and people are difficult to change. It suggests using behavioral economics and creating diverse teams to encourage different perspectives. Other suggestions to accelerate organizations include using incentives, empowering change, and addressing issues like fear, anger and suffering that some may feel about changes. While equilibrium sounds good, technology organizations can get stuck in "bad equilibrium" and need to break out of inefficient, undesirable states to improve.
Finding out what could go wrong before it does – Modelling Risk and UncertaintyBruce Edmonds
The document discusses challenges with using models to predict outcomes for complex systems and situations. It describes how classic policy modeling approaches often make simplifying assumptions that may not accurately capture real-world complexity. Specifically, statistical models assume fixed relationships that don't account for heterogeneity; microsimulations and CGE models only model simple systems and make strong assumptions; and system dynamics and simulation models have limitations due to unknown parameters and structural changes. The document advocates approaches that rapidly sense and react to complex, uncertain systems instead of trying to predict them, as predicting complex, unpredictable situations can provide false confidence and lead to unforeseen consequences.
Vlerick HRday 2013: Men versus machine, who wins? - Prof. Marc BuelensVlerick Business School
This document discusses the increasing use of big data and analytics in human resources. It provides examples of how data can be used to predict job performance, sales performance, and who may not be suitable for customer support roles. The document also discusses research comparing human judgment to statistical models in making predictions. While statistical models often outperform experts, combining multiple predictions from humans and models tends to provide the most accurate forecasts. Intuition alone is unlikely to be valid without direct experience and the ability to learn from mistakes. In conclusion, the document advocates applying what is already known about improving predictions by using simple models, multiple independent predictions, and combining human and machine judgments.
Automated decision making with predictive applications – Big Data AmsterdamLars Trieloff
My slides from tonight's talk at Impact HUB in Amsterdam on big data, machine learning, cognitive biases and how to overcome them with predictive applications.
The document discusses the Lean Startup methodology. It introduces key Lean Startup principles like entrepreneurs are everywhere, entrepreneurship is management, validated learning, build-measure-learn, and innovation accounting. It emphasizes the importance of the minimum viable product to test ideas quickly and learn through customer feedback, continuous deployment to learn from customers rapidly, and using metrics like split testing to validate hypotheses. The overall goal is to minimize the time and resources spent on products that do not meet customer needs.
Better Living Through Analytics - Strategies for Data DecisionsProduct School
Data is king! Get ready to understand how a successful analytics team can empower managers from product, marketing, and other areas to make effective, data-driven decisions.
Louis Cialdella, a data scientist at ZipRecruiter, shared some case studies and successful strategies that he has used at ZipRecruiter as well as previous experiences. The purpose of this data talk was to enlighten people on how to make sure that analysts can successfully partner with other departments and get them the information they need to do great things.
The Best & Worst Uses of AI in Software TestingEficode
Ingo Philipp
Distinguished Evangelist – Tricentis
Ingo Philipp champions the methodologies and technologies at the core of the company’s continuous testing solution. In his previous position as a senior product manager, he orchestrated product development and product marketing.
Machine learning is all around us. It is driving familiar B2C brands like Amazon and Google. And it is now driving our Quote-to-Cash process. Learn how to streamline and run a global sales operations organization leveraging machine learning to increase sales efficiency and to increase margins and revenue.
Data capabilities and competitive advantageNUS-ISS
This document discusses data capabilities and competitive advantage, drawing from lessons from consulting and research. It provides several examples and case studies to illustrate key points. The examples show how differentiating between drivers, levers, and causes is important to avoid making incorrect assumptions. They also demonstrate how the direction of causality and errors in arithmetic can pose problems. The document advocates using multiple metrics and perspectives, such as through the balanced scorecard framework, to measure performance and link data capabilities to organizational objectives. It also discusses different views on the impacts and transformative nature of technological changes and digitalization.
2010 10 19 the lean startup workshop for i_gap irelandEric Ries
The document discusses the Lean Startup methodology for building startups under conditions of extreme uncertainty. It advocates for an experimental, customer-focused approach where the minimum viable product is used to test hypotheses and gather customer feedback through rapid iteration. Key techniques include continuous deployment, rapid A/B testing, and using the five whys method to identify the root causes of problems. The goal is to minimize the time to validate learning about customers through frequent releases and measurement.
Information Security - Back to Basics - Own Your VulnerabilitiesJack Nichelson
When a security program isn't as good as it should be it can be tempting to conclude that it needs more resources and solutions. Jack Nichelson decided to take a different approach: simplification. By focusing on fewer problems with bigger returns, he was able to reduce malware by 60 percent and improve the results of his annual pen report. He’ll share a back-to-the-basics case study for removing complexity and running a simple, effective, start-up worthy security program.
This Talk is for - Security Managers looking to better focus on the real vulnerabilities and more effectively communicate your progress
The Goals of this talk – Find the real problems, create a formal plan, build support for the plan, and report the progress
The document discusses the Lean Startup methodology for building startups under conditions of extreme uncertainty. It advocates for building a minimum viable product and continuously validating hypotheses through customer experiments rather than fully planning products. Key techniques include rapid A/B testing, continuous deployment of code, and using metrics to guide product decisions rather than visions of predicted success. The goal is to maximize learning from customers with minimum resources to improve odds of achieving product-market fit.
Automated decision making with big data – Big Data ViennaLars Trieloff
This document discusses automated decision making using big data. It describes how companies in different industries like marketing and finance are using big data today, with three main approaches - using more data, faster data, or better decisions. The challenges of communication breakdowns between data collection/analysis and actual decision making are explored. Predictive applications aim to make better decisions by collecting and analyzing data to predict outcomes and optimize decisions. The example of optimizing ground beef orders is provided, showing how small changes in demand prediction can have large cost savings impacts.
Big data refers to the large amounts of structured and unstructured data that businesses receive daily. While the volume of data is large, it is what organizations do with the data that matters by analyzing it for insights to improve decisions and strategies. The amount of global data continues to grow exponentially, increasing the potential to glean key insights, yet only a small percentage of data is currently analyzed. Businesses should focus on better utilizing the information they receive every day to reduce costs, improve efficiency, develop new products and services, and make smarter decisions through big data analytics. However, data must be carefully interpreted and can be misused, so context from fields like the humanities and social sciences is important for critical thinking.
This document discusses breaking through the "analysis barrier" in web analytics. It describes the difference between reporting and analysis, with analysis involving deeper study of problems and recommendations for change. The document outlines a 5-stage model of web analytics maturity and provides examples of real customer analyses, showing how they identified issues and made recommendations. It introduces Semphonic as a consultancy that helps clients overcome the analysis barrier through an analytic roadmap and ongoing deep-dive analysis projects.
Using data analytics midlands think tank 2013Paddy Moore
The document discusses how data analytics can provide business clarity and better decisions through access to current, relevant, and actionable information, highlighting that businesses see a €10.66 return for every €1 spent on analytics and can gain a 67% competitive advantage; it also examines how the evolution of technology over time has made analytics solutions cheaper, more powerful, and easier to use than in the past.
2010 04 28 The Lean Startup webinar for the Lean Enterprise InstituteEric Ries
The document discusses myths and truths about Lean Startups. It dispels four common myths: that Lean means cheap, that it only applies to web/internet companies, that Lean Startups are small, and that they replace vision with data. It then provides an overview of Lean Startup principles like building a Minimum Viable Product, conducting rapid split tests, and achieving continuous deployment through small, frequent code releases.
2011 10 12 eric ries lean startup web 2.0 expo ny keynoteEric Ries
The document discusses principles of the Lean Startup methodology. It emphasizes validating ideas with customers through minimum viable products and rapid experimentation (build-measure-learn loop), using metrics to determine when to pivot an idea that is not working or persevere with one that shows promise. The goal is to minimize the time and money spent on ideas that are not viable so entrepreneurs can focus on their most promising opportunities.
The document discusses the principles of the Lean Startup methodology. It defines a startup as an experiment to deliver a new product or service under conditions of uncertainty. Rather than following a traditional product development process, the Lean Startup approach advocates for building a minimum viable product and using continuous deployment and A/B testing to rapidly validate hypotheses and learn from customers. Key principles include minimizing the time to validate learning through the build-measure-learn loop and using metrics that are actionable, accessible and auditable.
Eric Ries - The Lean Startup - Google Tech TalkEric Ries
This document discusses Lean Startup principles including validated learning, building-measuring-learning quickly through iterations, and innovation accounting. It emphasizes that entrepreneurship is management, startups are experiments, and most successful startups pivot their vision based on customer feedback. The Lean Startup methodology advocates for developing minimum viable products and continuously deploying, measuring and improving through techniques like A/B testing to rapidly learn what customers want.
Strategies to make anyone use your Product | Product that CountCastle
This document discusses strategies for getting people to use products. It covers understanding the user's needs or "job" that the product helps with, making it easy for the user to switch to the product, and demonstrating the product's value. It also discusses the journey users go through from not knowing about a product to trying it to becoming regular users. Product hooks that trigger behaviors like notifications or autoplaying videos are mentioned. The key is understanding the user, constantly delivering value throughout the experience, and crafting a story and triggers that drive user behavior.
Putting the F in FaaS: Functional Compositional Patterns in a Serverless WorldLars Trieloff
Presented at #ServerlessConf 2017 in New York City. Don't go looking for serverless patterns in strange places, take existing functional programming patterns instead.
Big Data Munich – Decision Automation and Big DataLars Trieloff
My presentation from Big Data Munich: How decision automation based on big data and machine learning can help you run a better business and avoid common cognitive biases.
10 Things I Learned About Pricing – Product Camp Berlin 2014Lars Trieloff
The document discusses 10 key lessons about pricing:
1. Always price based on the perceived value to the customer, not just costs.
2. "Freemium" is not really a pricing strategy on its own.
3. Price lists should be backed up by salespeople who can explain the value to customers.
4. Start with lower introductory prices to get new customers.
5. It is better to be a high-quality premium product than a cheap add-on product given away for free.
6. Good pricing requires analyzing historical sales data.
Digital marketing rapidly introduces new channels, concepts and context into marketing. This can lead to confusion and cognitive dissonance between traditional right-brain marketers and digital left-brain marketers. By going beyond the surface of what is visible in terms of vendors and products and concentrating on the fundamental building blocks of marketing, "The DNA of Marketing" offers a new look at marketing and a way to make sense of digital marketing innovation.
Combine Social Media with Social Communities in CQ5 to open additional channels for your marketing campaigns and increase targeting accuracy, maximize conversion and drive profitability.
Mastering the customer engagement ecosystem with CQ5Lars Trieloff
This document discusses how companies can master the customer engagement ecosystem by speaking with one voice across channels using a content management system. It notes that in the past companies used single or multi-channel approaches but now must engage customers through various micro-channels like websites, blogs, social media, mobile apps, stores, catalogs, email and more. The document recommends that companies identify their customers, build experiences for them, and speak with one voice by centralizing their marketing technology, content creation and delivery to better engage customers as they move across channels.
A short look on Day's Advanced Collaboration for Communiqué 4 and an outlook what Social Collab for Communiqué 5 will offer. Held by Lars Trieloff at Day's Tech Summit 2008 in Basel.
The document discusses how to avoid "bullshit architecture" when building web applications. It notes that architectural failure can result in expensive implementation and operation costs. Such failures often happen due to making technology choices based on hype, personal preference, or inertia rather than actual requirements. The presentation advocates using a modular architecture with well-defined interfaces between components to provide flexibility and avoid expensive rework later.
This document discusses REST (Representational State Transfer) and how it can be used with AJAX. It provides definitions of core REST concepts like resources, representations, URIs and HTTP verbs. It describes how web browsers can make HTTP requests but have limitations. AJAX allows getting alternate representations of resources like JSON and making asynchronous HTTP requests to overcome browser limitations. Frameworks help build RESTful AJAX applications by defining the domain model, resources and representations.
Presentation held at Web Montag Stockholm, March 2008. Introduction of JCR, Sling and the µjax AJAX-based access layer to a content repository. The presentation includes the demo of the µjax Dojo integration.
The document discusses JCR (Java Content Repository), which defines a standard API for accessing content in a content repository. It introduces μjax, which is an AJAX implementation that uses a JCR-compliant content repository in the backend. μjax allows for simple reading and writing of content to the repository via JavaScript. The document provides examples of using μjax to read, write, add and list content and encourages developers to try it out using Adobe CRX.
Living in a multiligual world: Internationalization for Web 2.0 ApplicationsLars Trieloff
The document discusses internationalization challenges for Web 2.0 applications and proposes solutions. It notes that Web 2.0 applications use various technologies like JavaScript, Flash, and desktop applications that each have their own internationalization frameworks. It recommends consolidating internationalization by keeping all translation data in a common format and database, and allowing applications to access translations from this single source. The document also addresses challenges of translating user-generated content and graphical text, and suggests structuring content and generating graphics dynamically on the server to improve translatability.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
In the Adani-Hindenburg case, what is SEBI investigating.pptxAdani case
Adani SEBI investigation revealed that the latter had sought information from five foreign jurisdictions concerning the holdings of the firm’s foreign portfolio investors (FPIs) in relation to the alleged violations of the MPS Regulations. Nevertheless, the economic interest of the twelve FPIs based in tax haven jurisdictions still needs to be determined. The Adani Group firms classed these FPIs as public shareholders. According to Hindenburg, FPIs were used to get around regulatory standards.
Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
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An introduction to the cryptocurrency investment platform Binance Savings.Any kyc Account
Learn how to use Binance Savings to expand your bitcoin holdings. Discover how to maximize your earnings on one of the most reliable cryptocurrency exchange platforms, as well as how to earn interest on your cryptocurrency holdings and the various savings choices available.
Industrial Tech SW: Category Renewal and CreationChristian Dahlen
Every industrial revolution has created a new set of categories and a new set of players.
Multiple new technologies have emerged, but Samsara and C3.ai are only two companies which have gone public so far.
Manufacturing startups constitute the largest pipeline share of unicorns and IPO candidates in the SF Bay Area, and software startups dominate in Germany.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
FIA officials brutally tortured innocent and snatched 200 Bitcoins of worth 4...jamalseoexpert1978
Farman Ayaz Khattak and Ehtesham Matloob are government officials in CTW Counter terrorism wing Islamabad, in Federal Investigation Agency FIA Headquarters. CTW and FIA kidnapped crypto currency owner from Islamabad and snatched 200 Bitcoins those worth of 4 billion rupees in Pakistan currency. There is not Cryptocurrency Regulations in Pakistan & CTW is official dacoit and stealing digital assets from the innocent crypto holders and making fake cases of terrorism to keep them silent.
19. • Drill-down analysis … misunderstood or
distorted
• Metrics dashboards … contradictory and
confusing
• Monthly reports … ignored after two
iterations
• In-house analyst teams … overworked
and powerless
How Data-Driven Decisions
REALLY work
CO M M U N I C AT I O N
B R E A K D O W N
20. How Decisions REALLY should
work
Computer
Collects
Computer
Stores
Computer
Analyzes
Computer
Predicts
CO M P U T E R
D E C I D E S
21. — Everyone at Blue Yonder, all the time
99.9% of all business decisions
can be automated
29. • Business rules are like programs – written by
non-programmers
• Business rules can be contradictory,
incomplete, and complex beyond
comprehension
• Business rules have no built-in feedback
mechanism:“It is the rule, because it is the rule”
Business rules are Programs,
just not very good ones.
42. — Daniel Kahneman
“All of us would be better
investors if we just made fewer
decisions.”
43.
44. How we are making decisions
(Like the big apes we are)
Anchoring effect
IKEA effect
Confirmation bias
Bandwagon effect
Substitution
Availability heuristic
Texas Sharpshooter Fallacy
Rhyme as reason effect
Over-justification effect
Zero-risk bias
Framing effect
Illusory correlation
Sunk cost fallacy
Overconfidence
Outcome bias
Inattentional Blindness
Benjamin Franklin effect
Hindsight bias
Gambler’s fallacy
Anecdotal evidence
Negativity bias
Loss aversion
Backfire effect
45.
46. K-Means Clustering
Naive Bayes
Support Vector Machines
Affinity Propagation
Least Angle Regression
Nearest Neighbors
Decision Trees
Markov Chain Monte Carlo
Spectral clustering
Restricted Bolzmann Machines
Logistic Regression
Computers making decisions
(cold, fast, cheap, rational)
47. • A machine learning algorithm is a system that
derives a set of rules based on a set of data
• It is based on systematic observation, double-
checking and cross-validation
• There is no magic, just data – and without data
there is no magic either
Machine Learning means
Programs that write Programs
71. If you ordered 8,5 cases, you
would waste a lot of meat,
the ideal order amount is 8
cases.
72. Predictive Apps in a Nutshell
Batch and streaming data ingestion, batch
and streaming delivery (with real-time option)
Reduce risk and cost » increase revenue and profit
Trend Estimation Classification Event Prediction
Optimize Returns
Collect Data Predict Results Drive Decisions
73. — John Maynard Keynes
“When my information
changes, I alter my conclusions.
What do you do, sir?”
74. One Common Platform for
Predictive Applications
Multi-Tenant Runtime Environment
Link Store Build Run View
Link your own and
third-party data, easily
integrated via API
Store your data in
high-performance
database as a service
Build machine
learning and
application code
Automatically run
and scale ML models
and applications
Monitor and inspect
resource usage and
model quality
Secure Micro Cloud Infrastructure
Domain Model Predictive Model Application Code
75. — Kevin Kelly
“The business plans of the next
10,000 startups are easy to
forecast: Take X and add AI”
76. How Enterprises adopt
Predictive Applications
Learn about
ADDD
Define Target
Process
Build
Predictive App
Go Live
Make Lots of
Money
78. How Enterprises REALLY adopt
Predictive Applications
Learn about
ADDD
Define Target
Process
Build
Predictive App
Make Lots of
Money
D O U BT S
CO N C E R N S
O B J E C T I O N S