This document discusses strategies for cultivating the relationship between data and strategy in fundraising. It covers data acquisition strategy, including determining the minimum necessary data and costs of acquisition, maintenance, and errors. It then discusses using a scientific method and analytics to develop data-based fundraising strategies through observation, hypothesis, and testing. Finally, it addresses data safety strategy and risks to charities from data breaches, given the amount of sensitive donor information typically collected and relatively small IT budgets. The overall message is that properly acquiring, analyzing, and protecting data is crucial for effective fundraising strategies.
Business analytics in healthcare & life scienceSanjay Choubey
Business analytics for Healthcare, Life Science businesses. Trends, Issues, Challenges, process & steps, Business drivers, Market & compliance, Big data and approach to overcome
Business analytics in healthcare & life scienceSanjay Choubey
Business analytics for Healthcare, Life Science businesses. Trends, Issues, Challenges, process & steps, Business drivers, Market & compliance, Big data and approach to overcome
Data science for business leaders executive programmjitu309
Data Science for Business Leaders Executive Program
PPT For Project done by Jitendra Ratilal Mistry
For Educational purpose Only
The content given in the PPT does not belong to me, Content belong to it's original Creator, for Education purpose it has been used in PPT.
Foundational Strategies for Trust in Big Data Part 2: Understanding Your DataPrecisely
Teams working on new initiatives whether for customer engagement, advanced analytics, or regulatory and compliance requirements need a broad range of data sources for the highest quality and most trusted results. Yet the sheer volume of data delivered coupled with the range of data sources including those from external 3rd parties increasingly precludes trust, confidence, and even understanding of the data and how or whether it can be used to make effective data-driven business decisions.
The second part of our webcast series on Foundation Strategies for Trust in Big Data provides insight into how Trillium Discovery for Big Data with its natively distributed execution for data profiling supports a foundation of data quality by enabling business analysts to gain rapid insight into data delivered to the data lake without technical expertise.
IBM Healthcare Business Analytics solutions including Cognos, TM1 and SPSS. How healthcare challenges are met and costs are optimized through the use of Data Visualizations, Performance Management, and Predictive Analytics.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
The big-data explosion is driving a shift away from gut-based decision making. Marketing, in particular, is feeling the pressure to embrace new data-driven customer intelligence capabilities.
Marketers working 70-80 hours a week is not a great thing to hear.
But the requirement for them to have such a large amount of work time causes problems in the data selection and filtering.
Hence many marketers flunk the big data test
Slides used for a presentation to introduce the field of business analytics. Covers what BA is, how it is a part of business intelligence, and what areas make up BA.
What is Data Science and How to Succeed in itKhosrow Hassibi
The use of machine learning and data mining to create value from corporate or public data is nothing new. It is not the first time that these technologies are in the spotlight. Many remember the late ‘80s and the early ‘90s when machine learning techniques—in particular neural networks—had become very popular. Data mining was at a rise. There were talks everywhere about advanced analysis of data for decision making. Even the popular android character in “Star Trek: The Next Generation” had been named appropriately as “Data.” Data science has been the cornerstone of many data products and applications for more than two decades, e.g., in finance, Telco, and retail. Credit scores have been in use for decades to assess credit worthiness of people when applying for credit or loan. Sophisticated real-time fraud scores based on individual’s transaction spending patterns have been used since early ‘90s to protect credit card holders from a variety of fraud schemes. However, the popularity of web products from the likes of Google, Linked-in, Amazon, and Facebook has helped analytics become a household name. Every new technology comes with lots of hype and many new buzzwords. Often, fact and fiction get mixed-up making it impossible for outsiders to assess the technology’s true relevance. Due to the exponential growth of data, today there is an ever increasing need to process and analyze big data which has required a rethinking of every aspect of the data science life cycle, from data management, to data mining and analysis, to deployment. The purpose of this talk is first to describe what data science is and how it has evolved historically. Second, I share my own experiences as a data scientist across different industries and through time with the audience emphasizing the challenges and rewards.
Data and analytic strategies for developing ethical itHyoun Park
Suggested audience: CIO, Enterprise Architects, Data Managers, Analytics Managers, Data Scientists
IT is broken. Bad data assumptions, legacy technology, poor business decisions, and weak IT management have changed IT from a superstar to a second-rate department that struggles to maintain its seat at the CEO's table.
With AI, personal data, & business ethics all in ascendence, the need for ethical IT policies has never been greater. Otherwise, companies risk building services and products that fall short of the ethics and trust that they have been given by employees.
In this webinar, Amalgam Insights explores how current data, BI, analytics, and machine learning technologies threaten ethical IT and provides guidance based on other rules-based frameworks that derive business outcomes, such as the law and corporate legislation.
Project analytics in Project ManagementKetan Gandhi
Project managers can use this predictive information to make better decisions and keep projects on schedule and on budget. Analytics does more than simply enable project managers to capture data and mark the tasks done when completed.
Transform Unstructured Data Into Relevant Data with IBM StoredIQPerficient, Inc.
Recent studies indicate more than 90% of the world's data was created in the last 2 years, and organizational data is rising 20-50% year-over-year. As the amount of structured and unstructured data dramatically expands, the expense of maintaining data stores is outpacing the reduction in storage costs.
To help your organization address the issues associated with growing data capacity requirements, IBM offers StoredIQ, a leading unstructured data management and intelligent eDiscovery solution.
Learn about:
Data governance challenges
Information lifecycle governance implementation options
The benefits of early action when uncovering redundant, obsolete and trivial (ROT) content
Typical industry use cases
You'll also learn how to most effectively deploy IBM StoredIQ to be able to:
Analyze data sources in-place
Identify ROT content
Uncover personally identifiable information and sensitive data
Limit your compliance risks and reduce storage costs
Stuart Edwards, Principal Consultant of hut4 Data Science, shares his experiences of wrangling the broad range of data sources available to the collections industry.
Further information about this topic can be found in this article in the IMA Agent magazine:
http://www.imal.com.au/eAGENT/eagentv51i02/index.html
Data science for business leaders executive programmjitu309
Data Science for Business Leaders Executive Program
PPT For Project done by Jitendra Ratilal Mistry
For Educational purpose Only
The content given in the PPT does not belong to me, Content belong to it's original Creator, for Education purpose it has been used in PPT.
Foundational Strategies for Trust in Big Data Part 2: Understanding Your DataPrecisely
Teams working on new initiatives whether for customer engagement, advanced analytics, or regulatory and compliance requirements need a broad range of data sources for the highest quality and most trusted results. Yet the sheer volume of data delivered coupled with the range of data sources including those from external 3rd parties increasingly precludes trust, confidence, and even understanding of the data and how or whether it can be used to make effective data-driven business decisions.
The second part of our webcast series on Foundation Strategies for Trust in Big Data provides insight into how Trillium Discovery for Big Data with its natively distributed execution for data profiling supports a foundation of data quality by enabling business analysts to gain rapid insight into data delivered to the data lake without technical expertise.
IBM Healthcare Business Analytics solutions including Cognos, TM1 and SPSS. How healthcare challenges are met and costs are optimized through the use of Data Visualizations, Performance Management, and Predictive Analytics.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
The big-data explosion is driving a shift away from gut-based decision making. Marketing, in particular, is feeling the pressure to embrace new data-driven customer intelligence capabilities.
Marketers working 70-80 hours a week is not a great thing to hear.
But the requirement for them to have such a large amount of work time causes problems in the data selection and filtering.
Hence many marketers flunk the big data test
Slides used for a presentation to introduce the field of business analytics. Covers what BA is, how it is a part of business intelligence, and what areas make up BA.
What is Data Science and How to Succeed in itKhosrow Hassibi
The use of machine learning and data mining to create value from corporate or public data is nothing new. It is not the first time that these technologies are in the spotlight. Many remember the late ‘80s and the early ‘90s when machine learning techniques—in particular neural networks—had become very popular. Data mining was at a rise. There were talks everywhere about advanced analysis of data for decision making. Even the popular android character in “Star Trek: The Next Generation” had been named appropriately as “Data.” Data science has been the cornerstone of many data products and applications for more than two decades, e.g., in finance, Telco, and retail. Credit scores have been in use for decades to assess credit worthiness of people when applying for credit or loan. Sophisticated real-time fraud scores based on individual’s transaction spending patterns have been used since early ‘90s to protect credit card holders from a variety of fraud schemes. However, the popularity of web products from the likes of Google, Linked-in, Amazon, and Facebook has helped analytics become a household name. Every new technology comes with lots of hype and many new buzzwords. Often, fact and fiction get mixed-up making it impossible for outsiders to assess the technology’s true relevance. Due to the exponential growth of data, today there is an ever increasing need to process and analyze big data which has required a rethinking of every aspect of the data science life cycle, from data management, to data mining and analysis, to deployment. The purpose of this talk is first to describe what data science is and how it has evolved historically. Second, I share my own experiences as a data scientist across different industries and through time with the audience emphasizing the challenges and rewards.
Data and analytic strategies for developing ethical itHyoun Park
Suggested audience: CIO, Enterprise Architects, Data Managers, Analytics Managers, Data Scientists
IT is broken. Bad data assumptions, legacy technology, poor business decisions, and weak IT management have changed IT from a superstar to a second-rate department that struggles to maintain its seat at the CEO's table.
With AI, personal data, & business ethics all in ascendence, the need for ethical IT policies has never been greater. Otherwise, companies risk building services and products that fall short of the ethics and trust that they have been given by employees.
In this webinar, Amalgam Insights explores how current data, BI, analytics, and machine learning technologies threaten ethical IT and provides guidance based on other rules-based frameworks that derive business outcomes, such as the law and corporate legislation.
Project analytics in Project ManagementKetan Gandhi
Project managers can use this predictive information to make better decisions and keep projects on schedule and on budget. Analytics does more than simply enable project managers to capture data and mark the tasks done when completed.
Transform Unstructured Data Into Relevant Data with IBM StoredIQPerficient, Inc.
Recent studies indicate more than 90% of the world's data was created in the last 2 years, and organizational data is rising 20-50% year-over-year. As the amount of structured and unstructured data dramatically expands, the expense of maintaining data stores is outpacing the reduction in storage costs.
To help your organization address the issues associated with growing data capacity requirements, IBM offers StoredIQ, a leading unstructured data management and intelligent eDiscovery solution.
Learn about:
Data governance challenges
Information lifecycle governance implementation options
The benefits of early action when uncovering redundant, obsolete and trivial (ROT) content
Typical industry use cases
You'll also learn how to most effectively deploy IBM StoredIQ to be able to:
Analyze data sources in-place
Identify ROT content
Uncover personally identifiable information and sensitive data
Limit your compliance risks and reduce storage costs
Stuart Edwards, Principal Consultant of hut4 Data Science, shares his experiences of wrangling the broad range of data sources available to the collections industry.
Further information about this topic can be found in this article in the IMA Agent magazine:
http://www.imal.com.au/eAGENT/eagentv51i02/index.html
There are tensions in the data structure choices we make. These relate to the value of information over time, the access / capture trade off, preservation and archiving considerations, and the need to effectively embed process / practice layering to allow efficient application of knowledge to action.
Your AI and ML Projects Are Failing – Key Steps to Get Them Back on TrackPrecisely
With recent studies indicating that 80% of AI and machine learning projects are failing due to data quality related issues, it’s critical to think holistically about this fact. This is not a simple topic – issues in data quality can occur throughout from starting the project through to model implementation and usage.
View this webinar on-demand, where we start with four foundational data steps to get our AI and ML projects grounded and underway, specifically:
• Framing the business problem
• Identifying the “right” data to collect and work with
• Establishing baselines of data quality through data profiling and business rules
• Assessing fitness for purpose for training and evaluating the subsequent models and algorithms
From Asset to Impact - Presentation to ICS Data Protection Conference 2011Castlebridge Associates
This is a presentation I delivered to the Irish Computer Society Data Protection Conference in February 2011 and again on a webinar for dataqualitypro.com in March 2011.
It looks (for what I believe was the first time) at the relationship between Information Quality and Data Governance principles and practices and the objectives of Data Protection/Privacy compliance. it includes my first version of the mapping of the 8 Data Protection principles to the POSMAD Information Life Cycle referred to by McGilvray and others in the IQ/DQ fields.
This webinar discussed the purpose of data analytics and how it can be a light in the darkness for your organization to make better decisions for the future. The webinar covered the purpose of data analysis and its definition, the fundamental steps to take to perform data analysis to problem solve, and closed with next steps that attendees can take to further develop data analysis and business intelligence within their organizations.
During this webinar, attendees learned about the following:
- How data analytics functions to help your organization improve.
- The process for using data analytics to solve problems.
- Next steps to take to build data analysis within your organization.
DataEd Slides: Approaching Data Governance StrategicallyDATAVERSITY
At its core, Data Governance (DG) is: managing data with guidance. This immediately provokes the question: Would you tolerate your data managed without guidance? (In all likelihood, your organization has been managing data without adequate guidance and this accounts for its current, less-than-optimal state.) This program provides a practical guide to implementing DG or recharging your existing program. It provides your organization with an understanding of what Data Governance functions are required and how they fit with other Data Management disciplines. Understanding these aspects is a necessary prerequisite to eliminate the ambiguity that often surrounds initial discussions and implement effective Data Governance/Stewardship programs that manage data in support of organizational strategy. Program learning objectives include:
• Understanding why Data Governance can be tricky for organizations due to data’s confounding characteristics
• Strategy No. 1: Keeping DG practically focused
• Strategy No. 2: DG must exist at the same level as HR
• Strategy No. 3: Gradually add ingredients
• Data Governance in action: storytelling
Audit: Breaking Down Barriers to Increase the Use of Data AnalyticsCaseWare IDEA
Presenter: Lenny Block, Associate VP, Internal Audit, NASDAQ
While the majority of internal audit leaders and C-suite executives agree data analytics is important to strengthening audit coverage, only a small percentage of organizations are actively using data analytics regularly. Why is that? This webinar will explore challenges and barriers associated with starting, sustaining and expanding the use of data analytics to improve audit coverage.
SLIDESHARE: www.slideshare.net/CaseWare_Analytics
WEBSITE: www.casewareanalytics.com
BLOG: www.casewareanalytics.com/blog
TWITTER: www.twitter.com/CW_Analytic
Stop the madness - Never doubt the quality of BI again using Data GovernanceMary Levins, PMP
Does this sound familiar? "Are you sure those numbers are right?" "Why are your numbers different than theirs?"
We've all heard it and had that gut wrenching feeling of doubt that comes with uncertainty around the quality of the numbers.
Stop the madness! Presented in Dunwoody on April 18 by industry leading expert Mary Levins who discusseses what it takes to successfully take control of your data using the Data Governance Framework. This framework is proven to improve the quality of your BI solutions.
Mary is the founder of Sierra Creek Consulting
Transform Your Downstream Cloud Analytics with Data Quality Precisely
Untrustworthy results or inaccurate insights from ML, AI, and advanced analytics systems were due to a lack of quality in the data as reported by nearly half of respondents to Precisely’s Enterprise Data Quality survey. Are you ready to improve your trust in the data your organization is using in the cloud for business decision-making?
Register now to learn how to take the first steps to high-quality data in the cloud by better understanding your data through profiling.
During this on-demand webinar, we will explore key topics such as:
• The five key steps to effective data profiling
• How profiling informs your next steps to deliver quality data to the cloud
• How Precisely customers have elevated marketing and customer service results by focusing on data quality
The Merger is Happening, Now What Do We Do?DATUM LLC
This was presented on October 24, 2018 at the ASUG EIM Conference. One of the many challenges presented by an acquisition and divestiture event is unifying disparate data and integrating systems together. If you are leading an integration, you may have more questions than answers on how to approach this event. Learn how to best leverage the momentum and budgets that accompany these activities to jump start good governance practices up front, as well as how to measure the return on investment, ensuring data and EIM professionals' ongoing success.
Russian anarchist and anti-war movement in the third year of full-scale warAntti Rautiainen
Anarchist group ANA Regensburg hosted my online-presentation on 16th of May 2024, in which I discussed tactics of anti-war activism in Russia, and reasons why the anti-war movement has not been able to make an impact to change the course of events yet. Cases of anarchists repressed for anti-war activities are presented, as well as strategies of support for political prisoners, and modest successes in supporting their struggles.
Thumbnail picture is by MediaZona, you may read their report on anti-war arson attacks in Russia here: https://en.zona.media/article/2022/10/13/burn-map
Links:
Autonomous Action
http://Avtonom.org
Anarchist Black Cross Moscow
http://Avtonom.org/abc
Solidarity Zone
https://t.me/solidarity_zone
Memorial
https://memopzk.org/, https://t.me/pzk_memorial
OVD-Info
https://en.ovdinfo.org/antiwar-ovd-info-guide
RosUznik
https://rosuznik.org/
Uznik Online
http://uznikonline.tilda.ws/
Russian Reader
https://therussianreader.com/
ABC Irkutsk
https://abc38.noblogs.org/
Send mail to prisoners from abroad:
http://Prisonmail.online
YouTube: https://youtu.be/c5nSOdU48O8
Spotify: https://podcasters.spotify.com/pod/show/libertarianlifecoach/episodes/Russian-anarchist-and-anti-war-movement-in-the-third-year-of-full-scale-war-e2k8ai4
Up the Ratios Bylaws - a Comprehensive Process of Our Organizationuptheratios
Up the Ratios is a non-profit organization dedicated to bridging the gap in STEM education for underprivileged students by providing free, high-quality learning opportunities in robotics and other STEM fields. Our mission is to empower the next generation of innovators, thinkers, and problem-solvers by offering a range of educational programs that foster curiosity, creativity, and critical thinking.
At Up the Ratios, we believe that every student, regardless of their socio-economic background, should have access to the tools and knowledge needed to succeed in today's technology-driven world. To achieve this, we host a variety of free classes, workshops, summer camps, and live lectures tailored to students from underserved communities. Our programs are designed to be engaging and hands-on, allowing students to explore the exciting world of robotics and STEM through practical, real-world applications.
Our free classes cover fundamental concepts in robotics, coding, and engineering, providing students with a strong foundation in these critical areas. Through our interactive workshops, students can dive deeper into specific topics, working on projects that challenge them to apply what they've learned and think creatively. Our summer camps offer an immersive experience where students can collaborate on larger projects, develop their teamwork skills, and gain confidence in their abilities.
In addition to our local programs, Up the Ratios is committed to making a global impact. We take donations of new and gently used robotics parts, which we then distribute to students and educational institutions in other countries. These donations help ensure that young learners worldwide have the resources they need to explore and excel in STEM fields. By supporting education in this way, we aim to nurture a global community of future leaders and innovators.
Our live lectures feature guest speakers from various STEM disciplines, including engineers, scientists, and industry professionals who share their knowledge and experiences with our students. These lectures provide valuable insights into potential career paths and inspire students to pursue their passions in STEM.
Up the Ratios relies on the generosity of donors and volunteers to continue our work. Contributions of time, expertise, and financial support are crucial to sustaining our programs and expanding our reach. Whether you're an individual passionate about education, a professional in the STEM field, or a company looking to give back to the community, there are many ways to get involved and make a difference.
We are proud of the positive impact we've had on the lives of countless students, many of whom have gone on to pursue higher education and careers in STEM. By providing these young minds with the tools and opportunities they need to succeed, we are not only changing their futures but also contributing to the advancement of technology and innovation on a broader scale.
Presentation by Jared Jageler, David Adler, Noelia Duchovny, and Evan Herrnstadt, analysts in CBO’s Microeconomic Studies and Health Analysis Divisions, at the Association of Environmental and Resource Economists Summer Conference.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Understanding the Challenges of Street ChildrenSERUDS INDIA
By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
This session provides a comprehensive overview of the latest updates to the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (commonly known as the Uniform Guidance) outlined in the 2 CFR 200.
With a focus on the 2024 revisions issued by the Office of Management and Budget (OMB), participants will gain insight into the key changes affecting federal grant recipients. The session will delve into critical regulatory updates, providing attendees with the knowledge and tools necessary to navigate and comply with the evolving landscape of federal grant management.
Learning Objectives:
- Understand the rationale behind the 2024 updates to the Uniform Guidance outlined in 2 CFR 200, and their implications for federal grant recipients.
- Identify the key changes and revisions introduced by the Office of Management and Budget (OMB) in the 2024 edition of 2 CFR 200.
- Gain proficiency in applying the updated regulations to ensure compliance with federal grant requirements and avoid potential audit findings.
- Develop strategies for effectively implementing the new guidelines within the grant management processes of their respective organizations, fostering efficiency and accountability in federal grant administration.
What is the point of small housing associations.pptxPaul Smith
Given the small scale of housing associations and their relative high cost per home what is the point of them and how do we justify their continued existance
What is the point of small housing associations.pptx
Data and Strategy: Cultivating Their Relationship
1. Kirk Schmidt | Method Works Consulting
Data and Strategy:
Cultivating Their
Relationship
2. • 9 years in the charitable sector, 6 as a process and systems
consultant.
• IT background
• B.Math (Waterloo)
• Master Storyteller (when dice are involved)
Kirk Schmidt
3. • Data Acquisition Strategy
• Data-based Strategy in Fundraising
• Data Safety Strategy
• Questions/Comments/Tomato Dodgeball
Data and Strategy: Overview
5. • What is the absolute minimum you are willing to put in your
database?
• Is there value in keeping a single piece of information as a
record?
• Can it be used to analyse and model?
Minimum Data
6. • Financial Cost
• Time spent entering the
data
• Time spent researching the
data
• Wasted time on data that
will never be of use
The Cost of Acquisition
7. • What data might you need
verification for?
• Determine if it is worth
investing (time or money)
in verification of data
• What could go wrong?
• What data requires
constant maintenance in
our database?
• Determine if it is worth
investing (time or money)
in maintenance of the data
• Maintaining researched
information
Maintenance and Verification
8. • Difficult cost to measure and plan for
• This cost is weighted against verification and maintenance
(or even against acquiring data in the first place)
• What risk does stale data pose? How can you deal with it?
The Cost of Getting It Wrong
9. • Minimum Data Strategy
• Cost of Acquisition
• Cost of Maintenance and Verification
• Cost of Getting It Wrong
You have to TRUST your data before you can use it to build
data-based strategies in fundraising.
Review: Data Acquisition Strategy
10. “However beautiful the strategy, you should
occasionally look at the results.” -Churchill
Data-based
Strategy in
Fundraising
11. • Definition: “commercial or professional procedures that are
accepted or prescribed as being correct or most effective.”
• Charities are at the infancy of data-based strategy
• Requisite Penelope Burk reference
• How do we do our own?
Best Practices
18. • Once you have your questions, you can start hypothesising,
predicting, and testing.
• Change one variable at a time.
• Start small – observe your data and ask questions.
Review: Data-based Strategy
19. “The charitable sector is the easiest, and
most lucrative, target that has yet to really
see a major public breach.”
Data
Safety
Strategy
20. • The two cars
• You are a bigger target than your servers
Not Just IT
21. • Relatively accurate and comprehensive data
– Names, addresses, email, phone numbers, workplace
information, birth date and spousal information
– Donation history, sometimes including bank accounts and
partial credit card numbers
– Prospect research data (yachts!)
• Relatively small IT budgets and staff to deal with controls
and compliance
• No culture of awareness of the dangers
The Risk
22. • Exporting information out of the database into an excel file
and putting on external media.
• Printing out donor briefing documents and carrying them
around.
• Emailing information.
• Answering the telephone.
Potential Failures
23. • Carry as little sensitive information as possible, or protect it
(if you have the know-how to do so)
• Process for checking out and checking in documents
• Email as little as possible, or transfer information through
more secure means
• On the phone, put onus on the caller
• Think like a hacker
Protecting Yourself
24. • Basic overview today
• Know that you are the biggest risk to your data, not the IT
infrastructure
• Understand why charities are potentially a relatively easy
and lucrative target
• Protect yourself and have process where possible
Data Safety Strategy
26. • Data Acquisition Strategy
– Acquiring, Maintenance, Verification, Getting it Wrong,
Minimum Data
• Data-based Strategy in Fundraising
– Using analytics to observe, question, test, and change process
• Data Safety Strategy
– Everyone’s responsibility
Data and Strategy
Meet me at an event. Socially awkward, strange, not very talkative.
Meet me but prepped. You start talking geeky stuff. We’re good.
Meet me with 3 days prep – marginally better conversation, but LAW OF DIMINISHING RETURNS
3 day prep but some information is wrong.
END 6 MINUTES
What data to acquire so that you can TRUST IT
How to use data to support and enhance your fundraising strategy
Keeping the data safe
END 8 MINUTES
-Trust
-*Any* and *Every* Piece of information
WHAT DATA IS THE MINIMUM YOU FEEL YOU SHOULD HAVE
RE Minimum is Last Name. This isn’t particularly useful.
However, are there cases where a single piece of information is useful? Email? (Email interest -> donor -> major gift donor – may want to model that)
Your strategy needs to include what is a minimum amount that you will accept in your database
END 11 MINUTES
Data Entry
Cost of renting lists
Time spent researching data
Strategy – how are you going to use this data?
YACHTS
Like any other wealth research
What is the cost of this research?
How are you going to use this data?
Researcher at $36K, 1 month of research.
If we increase an ask by $5k because of this research and get it, we have a 67% ROI
What happens next year?
Yacht example – how much time is needed year over year to maintain?
Is it worth it?
16:30 to 18 MINUTES
Classic example of maintenance: National Change of Address.
15% move rate per year. 10,000 people on a list, that’s an expected loss of 1,500 accurate addresses.
At $1/mailing, you’ve lost $1,500 in simply returned mail.
A $500 investment in NCOA. Let’s say it fixes 50% of addresses (normally over 80%). Now you only lose $750 in lost mail, so you’re only really out $1,250 instead of $1,500.
Those 750 that were fixed might even donate. 2% response rate at $50 a pop would yield another $750 you otherwise would not have received.
So there is a strategy to maintenance.
There are also costs to verification, and may be worth investing
Deceased story
What Happens If
21 TO 23 MINUTES
What are the risks?
Cost of getting it wrong can be hard to measure.
Quick Tshirt example
Can you plan for the tshirt example? No. Can you build a culture that finds maintenance and verification of data to be important? Sure.
The real strategy here is – what is the cost of maintenance or verification vs getting it wrong? Our mailing example – cost of getting it wrong was $1,500 loss on mail. Is it worth the $500 NCOA? You bet.
27 to 28 MINUTES
-Target Story
-Burk: When donors were called by a board member within 48 hours of receiving the gift, those called gave an average of 39% more than those not called.
33 TO 35 MINUTE END
Best Practice do not come from people saying, “I think…” or, “I feel…”
They come from testing and data-centric models
This does not mean you shouldn’t do some things. But you should constantly question it.
36 TO 38 MINUTE END
We are going to look at some charts. Now these are analytics that we have performed for clients. This is all from live data, some of it random sampled, some of it the full dataset.
We are going to look at what the data is telling us right now, and then what questions we can pose.
This is a chart of something that should feel self-evident. Effectively, it is showing us that the percent of people who give a third gift is correlated with the number of months between their first and second gift.
How can we get more people to give earlier (what if we did a matching for second gift within 3 months) ex
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Next we have a bubble chart!
This is actually showing us the top 5 giving amounts, and how many gifts they represent over the year.
What if we changed ask ladders
Why is it like this?
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This shows the percent of people who are repeat donors year over year from initial gift
What type of question could you ask here?
What happens if we can increase the first year?
Can we use this to determine whether an acquisition strategy will make money?
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Here’s a fun one. This is a time series chart of the amount of gifts processed per day over the last fiscal year, spread over a 10 business day moving average.
Now this is far less about fundraising, but it is still about internal strategy.
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54 TO 56 MINUTE
Credit card replacement example
DEFCON example for answering the telephone.
55 TO 60 MINUTE
If time permits, KODAK example on think like a hacker.
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