The document discusses what it means to be data-driven and the traits of data-driven organizations and managers. It defines being data-driven as making decisions compelled by data rather than intuition. Data-driven organizations build tools and culture to act on data, make decisions at all levels using diverse data, develop understanding through data, deal with uncertainty, and continuously learn from mistakes. The document emphasizes the importance of high-quality data for reducing uncertainty and enabling others to follow logic and align with decisions. It concludes that being data-driven drastically improves company performance by investing in quality data.
Traits of the Data-Driven
The data-driven:
● Make decisions at the lowest possible level
● Bring as much diverse data to any situation as they possibly can
● Use data to develop a deeper understanding of their worlds
● Develop an appreciation for variation
● Deal reasonably well with uncertainty
● Integrate their ability to understand data and its implications with their intuitions
● Recognize the importance of high-quality data and invest to make improvements
● Conduct good experiments and research
● Recognize that decision criteria can vary with circumstances
● Realize that making a decision is only the first step
● Work hard to learn new skills and bring new data and new data technologies (big data, predictive analytics, metadata management, etc.) into their organizations
● Learn from their mistakes
Traits of the Data-Driven
The data-driven:
● Make decisions at the lowest possible level
● Bring as much diverse data to any situation as they possibly can
● Use data to develop a deeper understanding of their worlds
● Develop an appreciation for variation
● Deal reasonably well with uncertainty
● Integrate their ability to understand data and its implications with their intuitions
● Recognize the importance of high-quality data and invest to make improvements
● Conduct good experiments and research
● Recognize that decision criteria can vary with circumstances
● Realize that making a decision is only the first step
● Work hard to learn new skills and bring new data and new data technologies (big data, predictive analytics, metadata management, etc.) into their organizations
● Learn from their mistakes
Generating Business Value thro’ Integrating Data Analysis into planning and...NareshChawla
Data analysis is the lifeline of any business. No business can survive without analyzing available data. Whether one wants to arrive at some marketing decisions or fine-tune new product launch strategy or compute process capability or predicate future trends or breakdown a big issue into smaller but manageable issues; data analysis is the key to all the problems.
[9Lenses + CSC] – Transforming the Way you Discover Organizational Insights9Lenses
Incite Discovery through scaled insight discovery. This is the presentation Edwin Miller, CEO, 9Lenses made along with Jerry Overton, Head of Advanced Analytics Research in CSC’s ResearchNetwork and founder of CSC’s FutureTense competency. This presentation was made on December 2nd, 2014 at the Innovation Enterprise’s Chief Innovation Officer Summit, in New York City.
Edwin advocated for the automation of the middle-management layer of a business so that machine learning can more rapidly connect all the complexities of a business.
Jerry Overton spoke about how Data Science + Human Data allows companies to simulate new business models.
What makes an effective executive?
The measure of the executive, Peter F. Drucker reminds us, is the ability to "get the right things done." This usually involves doing what other people have overlooked as well as avoiding what is unproductive. Intelligence, imagination, and knowledge may all be wasted in an executive job without the acquired habits of mind that mold them into results.
Drucker identifies five practices essential to business effectiveness that can, and must, be learned: Managing time Choosing what to contribute to the organization Knowing where and how to mobilize strength for best effect Setting the right priorities Knitting all of them together with effective decision-making
Ranging widely through the annals of business and government, Peter F. Drucker demonstrates the distinctive skill of the executive and offers fresh insights into old and seemingly obvious business situations.
Data analytics with managerial application ass 3Nishant Kumar
In this presentation , we discussed about important insight from “ what do we do with all these big data “ by Susan Etlinger , finally data are not always correct, but we can make useful deduction to search other possibilities in order to innovate by changing our frame of reference
In this presentation we explore ideas related to improving the usefulness of project Stakeholder Analysis by augmenting it with the neuroscience based SCARF model. http://www.proficiencysystems.com/
Insights from neuroscience to motivate business stakeholdersKay Fudala
Organizations are struggling with unparalleled challenges created by the uncertainty and ambiguity of transformational changes. Social neuroscience provides the framework to identify domains that activate reward or threat circuitry in the human brain. So, how can IT professionals leverage established research from Neuroscience to design interactions with stakeholders to promote rapid acceptance and adoption? What are the key behaviors that can improve collaboration and engagement to deliver the greatest business value? This session answers those questions and many more!
Key Takeaways
• Learn about the anatomy of the brain
• Discuss how the brain responds to change
• Learn practical ways to utilize this information to engage people
Generating Business Value thro’ Integrating Data Analysis into planning and...NareshChawla
Data analysis is the lifeline of any business. No business can survive without analyzing available data. Whether one wants to arrive at some marketing decisions or fine-tune new product launch strategy or compute process capability or predicate future trends or breakdown a big issue into smaller but manageable issues; data analysis is the key to all the problems.
[9Lenses + CSC] – Transforming the Way you Discover Organizational Insights9Lenses
Incite Discovery through scaled insight discovery. This is the presentation Edwin Miller, CEO, 9Lenses made along with Jerry Overton, Head of Advanced Analytics Research in CSC’s ResearchNetwork and founder of CSC’s FutureTense competency. This presentation was made on December 2nd, 2014 at the Innovation Enterprise’s Chief Innovation Officer Summit, in New York City.
Edwin advocated for the automation of the middle-management layer of a business so that machine learning can more rapidly connect all the complexities of a business.
Jerry Overton spoke about how Data Science + Human Data allows companies to simulate new business models.
What makes an effective executive?
The measure of the executive, Peter F. Drucker reminds us, is the ability to "get the right things done." This usually involves doing what other people have overlooked as well as avoiding what is unproductive. Intelligence, imagination, and knowledge may all be wasted in an executive job without the acquired habits of mind that mold them into results.
Drucker identifies five practices essential to business effectiveness that can, and must, be learned: Managing time Choosing what to contribute to the organization Knowing where and how to mobilize strength for best effect Setting the right priorities Knitting all of them together with effective decision-making
Ranging widely through the annals of business and government, Peter F. Drucker demonstrates the distinctive skill of the executive and offers fresh insights into old and seemingly obvious business situations.
Data analytics with managerial application ass 3Nishant Kumar
In this presentation , we discussed about important insight from “ what do we do with all these big data “ by Susan Etlinger , finally data are not always correct, but we can make useful deduction to search other possibilities in order to innovate by changing our frame of reference
In this presentation we explore ideas related to improving the usefulness of project Stakeholder Analysis by augmenting it with the neuroscience based SCARF model. http://www.proficiencysystems.com/
Insights from neuroscience to motivate business stakeholdersKay Fudala
Organizations are struggling with unparalleled challenges created by the uncertainty and ambiguity of transformational changes. Social neuroscience provides the framework to identify domains that activate reward or threat circuitry in the human brain. So, how can IT professionals leverage established research from Neuroscience to design interactions with stakeholders to promote rapid acceptance and adoption? What are the key behaviors that can improve collaboration and engagement to deliver the greatest business value? This session answers those questions and many more!
Key Takeaways
• Learn about the anatomy of the brain
• Discuss how the brain responds to change
• Learn practical ways to utilize this information to engage people
1. Sepa exactamente de donde provienen sus datos.
2. Asegure que todos en la organización comparten los mismos datos, con un acceso fácil y libre de complejidades.
3. Gobernabilidad de la información: mantenga a su equipo capacitado en procesos simples y transparentes.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl 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.
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.
Slide share Hyper-Decision Making - Short VersionDr. Ted Marra
The new imperative for organisational success will be 'hyper-decision making'. Gain insights into executive research around decision making; the concept of 'optimal' decision; the costs of lost opportunity associated with decision making; the factors that determine your organisation's 'decision intelligence quotient'; the drivers of 'risk'; what a systematic, integrated and comprehensive decision making process looks like; and more! Enjoy!
NTEN Your Analytics doesn't have to be dramatic to be usefulAndrew Patricio
My presentation at the 2024 NTEN conference in Portland, OR. I talk about practical approaches and benefits to deploying your analytics and reporting systems. Three high level themes:
1. Focus on people not the system, in particular make sure you start with hiring someone who understands your data before building your system. Data analytics augments human intuition not replaces it.
2. Make sure you start with your organizational vision to define your business outcomes to define your metrics and analytics to define your data. In other words make sure you are tracking relevant data
3. It is more about evolution not revolution. Data science is incremental not sudden.
Get the fundamentals of a good data culture ideas..pdfJose thomas
A better supply chain, better customer relationship management, and lower IT costs are all benefits of using Axolon ERP solutions UAE. Customers are more satisfied as a result of the quicker responses to their inquiries. https://axolonerp.com/
Data-driven decision-making is an incredible process that helps data science professionals boost their businesses. Explore DDDM in detail and learn how you can master it in 2024
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
2. What do you mean by being data driven?
The adjective data-driven means that progress in an
activity is compelled by data, rather than by intuition or by
personal experience.
Data-drivenness is about building tools, abilities, and, most
crucially, a culture that acts on data.
The essence of “data-driven” is making better decisions up
and down the organization chart.
3.
4.
5. Traits of the Data-Driven
The data-driven:
• Make decisions at the lowest possible level
• Bring as much diverse data to any situation as they
possibly can
• Use data to develop a deeper understanding of their
worlds
• Develop an appreciation for variation
• Deal reasonably well with uncertainty
• Integrate their ability to understand data and its
implications with their intuitions
6. • Recognize the importance of high-quality data and
invest to make improvements
• Conduct good experiments and research
• Recognize that decision criteria can vary with
circumstances
• Realize that making a decision is only the first step
• Work hard to learn new skills and bring new data and
new data technologies (big data, predictive analytics,
metadata management, etc.) into their organizations
• Learn from their mistakes
8. The data-driven are constantly re-evaluating and
refining their decisions along the way.
They are quicker than others to pull the plug when the
evidence suggests that a decision is wrong.
That doesn’t mean they “turn on a dime”; they know
that is not sustainable.
Rather, they learn as they go.
9. MANAGERIAL ASPECT
Data-driven managers have an innate sense that variation
dominates. Even the simplest process, human response, or
most-controlled situation varies. While they may not use a
graph or control chart, they know that they have to
recognize that variation if they are going to understand
what is going on.
10.
11.
12. While each person and organization is different, every
manager should start by pushing decision making down the
organization. It may be tough and counterintuitive,
especially for managers who want to feel in control, but it’s
worth the effort.
Frankly, you simply cannot be data-driven without a high
level of trust in your data and data sources. You’re reduced
to your intuition alone, the antithesis of the goal here.
Quality data is a necessity. Engage your management team
in doing exactly the same thing for your organization.
13.
14. CONCLUSION
Being data driven improves a companies performance
drastically.
Invest in quality data. High-quality data makes it easier
to understand variation and reduces uncertainty.
Success is measured in execution, and high-quality data
makes it easier for others to follow the decision-makers
logic and align to the decision.
