William Edwards Deming (October 14, 1900 – December 20, 1993) was an American statistician, professor, author, lecturer and consultant. He is perhaps best known for the "Plan-Do-Check-Act" cycle popularly named after him. In Japan, from 1950 onwards, he taught top management how to improve design (and thus service), product quality, testing, and sales (the last through global markets) through various methods, including the application of statistical methods.
Deming made a significant contribution to Japan's later reputation for innovative high-quality products and its economic power. He is regarded as having had more impact upon Japanese manufacturing and business than any other individual not of Japanese heritage. Despite being considered something of a hero in Japan, he was only just beginning to win widespread recognition in the U.S. at the time of his death.President Reagan awarded the National Medal of Technology to Deming in 1987. He received in 1988 the Distinguished Career in Science award from the National Academy of Sciences.
Deming's teachings and philosophy are best illustrated by examining the results they produced after they were adopted by Japanese industry, as the following example shows: Ford Motor Company was simultaneously manufacturing a car model with transmissions made in Japan and the United States. Soon after the car model was on the market, Ford customers were requesting the model with Japanese transmission over the US-made transmission, and they were willing to wait for the Japanese model. As both transmissions were made to the same specifications, Ford engineers could not understand the customer preference for the model with Japanese transmission. Finally, Ford engineers decided to take apart the two different transmissions. The American-made car parts were all within specified tolerance levels. On the other hand, the Japanese car parts were virtually identical to each other, and much closer to the nominal values for the parts – e.g., if a part was supposed to be one foot long, plus or minus 1/8 of an inch – then the Japanese parts were all within 1/16 of an inch. This made the Japanese cars run more smoothly and customers experienced fewer problems.
Data is transforming the social sector. At Do Good Data 2013 you will hear from leading thinkers from nonprofits, academia, and government talk about how data is transforming their work and organizations.
(It's been around for a while, like all disruptive tech trends - it sometimes takes years to ramp up and then fade into being part of life."
Myth 2: Big Data Is Objective
Need to have information literacy skills - know the context of your data - it may be skewed. This is why you can't be "data-driven" and have to be "data-informed"
Myth 3: Big Data Doesn't Discriminate
It isn't color blind or gender blind. When people create data sets, those become fallible human tools. Data is something we create but also something we imagine.
Myth 4: Big Data Makes Cities Smart
It is only as good as the people using it. Devices are proxies for public needs.
Myth 5: Big Data Is Anonymous
Talking about privacy issues related to public data -- with a cell phone data you can identify 50% of who made the call with two data points, with four data points identify 95%. Finger prints require 12 data point to identify someone.
Myth 6: You can opt out
Uses Instagram as an example when they shared TOS. What it didn't have was a paid option so you could pay a fee and opt out. Will there be a two-tiered system in the future for people who want and can afford to control their data?
"Before Big Data becomes a fact of life, need to think about how we will navigate these systems - for individuals and society.
This tool lets you upload your spreadsheets, it analyzes your data, and auto generates visualizations. I haven't tried it yet, but I am wondering if it does my laundry too. Seriously, curious about whether it is any good.
The Nonprofit Finance Fund has released the results of their 2013 State of the Nonprofit Sector Survey and it is chock full of important information and analysis tools for nonprofits.The study had nearly 6000 respondents and the online survey analyzer allows you to do subset analysis.This article features some highlights of the overall survey. Marion Conway has summarized the important points.
(Debra Joy Perez [@djoyperez] currently is serving as interim vice president of research and evaluation at the Robert Wood Johnson Foundation, the largest healthcare philanthropy in the country.
Beth Kanter's insight:
The latest Q&A in the series, featuring Debra Joy Perez, the foundation's interim vice president of research and evaluation, explores how RWJF's use of social media, which has become essential to its communication efforts, can be measured to reflect the impact of that work in the context of achieving the foundation's larger social change goals.
The SumAll Foundation, a non-profit effort by cloud analytics startup SumAll, is trying to change the world by showing non-profits how to get the most out of their data by thinking more like businesspeople do.
The following is a guest post Amit Jain, lead researcher and marketing director at Coursolve. These days, it’s all too easy to find examples of “Big Data” making an impact. From solving crimes to f...
Beth Kanter's insight:
Here's another resource for finding data nerds who can work with nonprofits!
We have a different sort of solution in mind – one that harnesses the untapped potential of students. As institutions of higher education dramatically expand their data science offerings, countless students are gaining new skills, but aren’t putting them to use with real-world datasets. Next month, we’re giving tens of thousands of those students from around the world the chance to do something more exciting: work with your data to strengthen your impact.
Nonprofits of all types are now invited to apply to “Introduction to Data Science,” a massively open online course to be taught next month by Prof. Bill Howe of the University of Washington. As part of the course, students will have the option to complete a project in which they work with a real dataset to address the needs of an organization. As they learn techniques in data visualization and trend identification, these students will apply what they learn to help drive your organization’s future initiatives. The insights they offer could strengthen your impact and identify areas for growth.
In a world with limited resources, it just makes sense to utilize student talents and creativity to strengthen your work. Tens of thousands of students have already registered for the course – don’t miss your chance to recruit thei
Looking to measure your Pinterest ROI? Here's an overview of the different Pinterest analytics tools you can use to track your Pinterest marketing efforts, and how to start using this data to improve your Pinterest marketing strategy.
More than 80% of nonprofit leaders recently surveyed believe that demonstrating impact through performance measurement is a top priority. Yet for many, evaluat
Beth Kanter's insight:
This presentation is a high level overview of several resources to improve nonprofit measurement practice and several case studies on social impact assessment. The presentation comes from Mayur Patel who is Director of Evaluation for the Knight Foundation.
But is big data really all it's cracked up to be? Can we trust that so many ones and zeros will illuminate the hidden world of human behavior? Foreign Policy invited Kate Crawford of the MIT Center for Civic Media to go behind the numbers:
"With Enough Data, the Numbers Speak for Themselves."
Not a chance. The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses. Numbers can't speak for themselves, and data sets -- no matter their scale -- are still objects of human design. The tools of big-data science, such as the Apache Hadoop software framework,do not immunize us from skews, gaps, and faulty assumptions. Those factors are particularly significant when big data tries to reflect the social world we live in, yet we can often be fooled into thinking that the results are somehow more objective than human opinions. Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
Lesson Learned: We created the graph below using NodeXL. It shows the 5 key types of participation that visitors can engage in on the ACTion Alexandria website. In this graph, each dot represents a site visitor. Color represents how many activities site visitors have performed (e.g., orange=all 5 activities, dark blue=just 1 activity). Size also indicates the number of activities site visitors have performed. Each line represents an activity the site visitor engaged in on the website. The thickness of the lines (also referred to as edge thickness) shows the number of times a site visitor has performed an activity.
The graph highlights the following things about site participation:
Most people only perform one activity, although a significant number perform two activities.
Voting is by far the most popular way that people engage with the site.
Blog posters post many times, but don’t tend to comment on each other’s blogs.
People who engage with multiple types of activities are more likely to engage in them multiple times (i.e., have thicker lines).
SumAll.org is a non-profit organization dedicated to doing social good by analyzing data. One of the biggest challenges facing charities and non-profits is the lack of resources and data analytics at their disposal.