data-driven storytelling...how i discovered data-driven storytelling 1995 as a ga in the student...
TRANSCRIPT
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Data-Driven StorytellingCOMBINING NUMBERS & NARRATIVE
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What is Data-Driven Storytelling?
“The world of big data offers opportunities to uncover new insights, and to tell stories in newly compelling ways.” - Alexandra Samuel, Ph.D. – Harvard Business Review 2015
“Focused and relevant data can be incredibly effective at transmitting your content’s meaning and significance. Yet without context and proper presentation, statistics and data sets can be difficult to interpret.” – Visage Content Marketing Agency
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How I discovered Data-Driven Storytelling
1995 as a GA in the Student Life Office at MSU Tasked with creating a campus wide database of disciplinary records
Student files went back to the 1940’s
Paper files were keyed into the database
Developed codes and criteria for offenses and assigned purge dates
Created queries based on offense types
Found an abnormal spike in academic dishonesty over three year span Investigation revealed a single instructor responsible
Doubts regarding student guilt prompted file purge
Data revealed instructor at fault not students
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Today’s presentation
Data Big data
Open data
Proprietary data
Storytelling Data Visualizations
Data leading to story
Story leading to data
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Big Data
“There is no single agreed upon definition of big data. For one, it is data generated through our increasing use of digital devices and web-supported tools and platforms in our daily lives.” – SciDev.net
Big data include open data, proprietary data and much more
Data scientists are working to apply Big Data across many industries including healthcare Algorithms combing data repositories may someday help to eradicate
disease
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Data Growth 2006 - 20011
http://pingv.com/f/imagecache/teaser_full/blogimgs/Exabyteslinear.png
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What’s an Exabyte?
http://www.scidev.net/global/data/feature/big-data-for-development-facts-and-figures.html
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http://www.scidev.net/filemanager/root/site_assets/global/data_spotlight/graph_global_mobil_data_new_fileminimizer_.jpg
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How do we use Big Data?
Big data has big potential Currently much of it is of little value
Data scientists are working to format and extract applicable information
For data to be useful we need: Insights
Example: Academic dishonesty data revealed insights
Actionable insights Example: Insights were used to correct student records
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Open Data
“Open data—machine-readable information, particularly government data, that’s made available to others—has generated a great deal of excitement around the world for its potential to empower citizens, change how government works, and improve the delivery of public services.” – McKinsey - Open data: Unlocking innovation and performance with liquid information (2013)
http://www.mckinsey.com/business-functions/business-technology/our-insights/open-data-unlocking-innovation-and-performance-with-liquid-information
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Examples of open data repositories
US Government http://catalog.data.gov/dataset
California Health and Human Services https://chhs.data.ca.gov/
Missouri Open Data https://data.mo.gov/browse?category=Health&utf8=%E2%9C%93
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Professional association open data
The American Medical Association https://healthinequality.org/
https://healthinequality.org/data/
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Open Data Pros & Cons
Pros Free or low cost
Accessible
Formatted
Cons Data/programming skills may be required
May not produce actionable insights
Limited availability of local information
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Telling Stories with Open Data
"We're not lacking in data, but what we don't have is narrative. There is a dearth of good storytelling," said Roy Sekoff, founding editor of The Huffington Post and co-creator at HuffPost Live. -AdWeek 2016
Dr. Ben Wellington of Pratt Institute in Brooklyn Blog - http://iquantny.tumblr.com/
Uses open data to tell stories about NYC Found fire hydrant generating $50k in annual fines
Uncovered $791 million city budget error
Learned police where ticketing legally parked cars
costing residents $1million per year
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Proprietary data Organizations collect data everyday
ERP software (SalesForce, NetSuite, SAP, etc.)
EMR
Web sites
Financial packages (QuickBooks, JD Edwards, etc.)
Data may be queried for insights Clients/Patients
Employees
Donors
Sell access rights
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Proprietary Data Example
EMR company promoting patient portal product Physicians concerned patients would not use it
University of Michigan study regarding 65 and older patients Found less than 10% of elderly low health literacy patients used the
internet to find health information - http://link.springer.com/article/10.1007%2Fs11606-014-3069-5
Piqued my interest Studies show that patients, especially elderly, tend to do what their
doctors tell them
Created a SQL script Pulled data on 1,087 patients chosen at random
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Patients logged in to view their health data
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Proprietary Data May Be More Reliable
University of Michigan study used open data Health and Retirement Study - http://hrsonline.isr.umich.edu/index.php?p=start
Assessed whether patients searched online for health data
Did not measure patients’ willingness to view their own health data
Our data tracked when patients logged into the patient portal Percentage was much higher
Helped to placate the fears of our customers
Increased patient portal sales and adoption rates
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Data VisualizationsSimple graphs/charts may be very effective
Country Percentage
China 38%
USA 24%
UK 15%
Canda 10%
China USA UK Canda
0%
5%
10%
15%
20%
25%
30%
35%
40%
China USA UK Canda
Video may also be used to bring numbers to life -http://bit.ly/2cKgMCJ
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Florence Nightingale – Data Visualization Pioneer In the mid 1850’s Florence Nightingale kept detailed records
regarding soldiers’ deaths. She found most soldiers where not dying from their wounds but
rather infections and diseases they picked up in the hospital. She used a data visualization to plead her case for sanitary
conditions to Parliament.
http://dupress.deloitte.com/dup-us-en/deloitte-review/issue-12/telling-a-story-with-data.html#endnote-3
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The chart on the right shows the rate of soldiers’ deaths before her ideas were put into place.
The chart on the left shows the reduction in deaths after her sanitary procedures were adopted.
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Infographics Depict data in graphical form
Easily digestible
Shareable
Inexpensive
Targeted
Promotional
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Data Leading to Story
Open data and propriety data Relationships – causation and/or prediction
Rank order – highest to lowest
Trends – increases and decreases over time
Counterintuitive data – surprising and/or challenges conventional thought
Comparisons – similarities between datasets
http://buzzsumo.com/blog/how-to-write-data-driven-stories-5-core-narratives/
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Example: Story Leading to Data• My daughter visiting my mother
on Christmas Day 2015
• Mother’s 3rd surgery in 14 months
• Homebound since release from hospital on New Year’s Eve 2015.
• Awaiting 4th surgery for same issue scheduled for Oct 10th
• Anticipated in-patient length of stay 3 weeks at Barnes in STL
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Data helps generalize individual experience 1 out of every 5 Medicare patients are readmitted within 30 days of
discharge Preventable hospital readmissions cost Medicare $26 billion annually.
$17 billion considered avoidable.http://revcycleintelligence.com/news/preventable-readmissions-cost-cms-17-billion
New study shows Medicare saves an average of $2,700 per patient when surgery occurs at high quality facility. http://bit.ly/2dkauJ4
Using data to expand the story to a larger audience increases the likelihood the story will be shared.
Actionable insights for Medicare patients Demand a second opinion Consider treatment options other than surgery If surgery is the choice engage a high quality facility
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Summary
Actionable insights may be derived directly from data or they may be inspired by an event which leads to data.
Either way, big data is here to stay. Those who seek to use data to tell stories may benefit from the ability to reach audiences in new and meaningful ways.
Thank you
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Questions