Data-Driven StorytellingCOMBINING NUMBERS & NARRATIVE

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

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

Today’s presentation

Data Big data

Open data

Proprietary data

Storytelling Data Visualizations

Data leading to story

Story leading to data

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

Data Growth 2006 - 20011

http://pingv.com/f/imagecache/teaser_full/blogimgs/Exabyteslinear.png

What’s an Exabyte?

http://www.scidev.net/global/data/feature/big-data-for-development-facts-and-figures.html

http://www.scidev.net/filemanager/root/site_assets/global/data_spotlight/graph_global_mobil_data_new_fileminimizer_.jpg

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

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

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

Professional association open data

The American Medical Association https://healthinequality.org/

https://healthinequality.org/data/

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

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

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

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

Patients logged in to view their health data

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

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

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

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.

Infographics Depict data in graphical form

Easily digestible

Shareable

Inexpensive

Targeted

Promotional

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/

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

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

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

Questions