B r y c e G a r t n e r , F o u n d e r & C h i e f E x p e r i e n c e O f f i c e r , i c i m o , L L C

G o r d o n S c h m i t t l i n g , C I O , A m e r i c a n A c a d e m y o f F a m i l y P h y s i c i a n s

P r a b h a s h S h r e s t h a , V i c e P r e s i d e n t o f I n f o r m a t i o n Te c h n o l o g y, T h e A m e r i c a n G a s t r o e n t e r o l o g i c a l A s s o c i a t i o n

Creating a Big Data Strategy with Tact ics for Quick Implementat ion

December 16, 2014Hashtag: #tech14

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IntroductionP r a b h a s h S h r e s t h a , V i c e P r e s i d e n t o f I n f o r m a t i o n T e c h n o l o g y

T h e A m e r i c a n G a s t r o e n t e r o l o g i c a l A s s o c i a t i o n i s t h e t r u s t e d v o i c e o f t h e G I c o m m u n i t y . F o u n d e d i n 1 8 9 7 , t h e A G A h a s g r o w n t o i n c l u d e m o r e t h a n 1 6 , 0 0 0 m e m b e r s f r o m a r o u n d t h e g l o b e w h o a r e i n v o l v e d i n a l l a s p e c t s o f t h e s c i e n c e , p r a c t i c e a n d a d v a n c e m e n t o f g a s t r o e n t e r o l o g y .

G o r d o n S c h m i t t l i n g , C h i e f I n f o r m a t i o n O f f i c e r

T h e A m e r i c a n A c a d e m y o f F a m i l y P h y s i c i a n s i s t h e n a t i o n a l a s s o c i a t i o n o f f a m i l y d o c t o r s . I t i s o n e o f t h e l a r g e s t n a t i o n a l m e d i c a l o r g a n i z a t i o n s , w i t h m o r e t h a n 11 5 , 9 0 0 m e m b e r s i n 5 0 s t a t e s , D . C . , P u e r t o R i c o , t h e V i r g i n I s l a n d s , a n d G u a m , a s w e l l a s i n t e r n a t i o n a l l y .  

Vision: AAFP’s Vision is to transform healthcare to achieve optimal health for everyone.

Mission: The mission of the AAFP is to improve the health of patients, families, and communities by serving the needs of members with professionalism and creativity.

B r y c e G a r t n e r , C h i e f E x p e r i e n c e O f f i c e r & F o u n d e r

I c i m o h e l p s o r g a n i z a t i o n s b e c o m e d a t a d r i v e n t h r o u g h a c o m b i n a t i o n o f s o f t w a r e t o o l s a n d s e r v i c e s e n a b l i n g d a t a d i s c o v e r y , v i s u a l i z a t i o n a n d d a t a a n a l y s i s . W e h a v e a s s i s t e d p r o f e s s i o n a l a n d t r a d e a s s o c i a t i o n s , d o n o r b a s e d o r g a n i z a t i o n s a n d f o r - p r o f i t o r g a n i z a t i o n s r a n g i n g f r o m $ 1 M i l l i o n t o $ 6 B i l l i o n i n a n n u a l r e v e n u e .

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Your Expectations and Objectives

What ins igh ts a re you hop ing to ga in f rom today ’s sess ion?

What a re some o f the f rus t ra t ions you a re dea l ing w i th in leverag ing your da ta?

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Learning ObjectivesA f t e r p a r t i c i p a t i n g i n t h i s s e s s i o n , y o u w i l l b e a b l e t o :

Leave with a Big Data Strategy that you could sell to your leadership

Leave with tactics that you could use to implement your new strategy

Understand how one tool could get you there sooner, rather than later

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Data is the new untapped frontier

“Data is the new Oil. Data is just like crude. It’s valuable, but if unrefined it cannot really be used”

Clive Humby

“We have for the first time an economy based on a key resource [information] that is not only renewable, but self-generating. Running out of it is not a problem, but drowning in it is.”

John Na isb i t t

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Associations Need a new Approach to their Data

P r o b l e m :

Our Associations staffs want IT to give them better access to their data and/or ability to utilize it.

M i s s i o n :

The Associations need a new approach to our data in order to leverage analytics as a game-changer to maximize our business outcomes.

V i s i o n

Deliver trusted data in minutes, not days, weeks or months. Enable staff to work smarter not harder

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Why do Associat ions need a new Approach to Data

G o o d t o G r e a t : G r e a t c o m p a n i e s d o n o t g e t p a s s i o n a t e a b o u t w h a t t h e y d o , r a t h e r t h e y o n l y d o t h o s e t h i n g s a b o u t w h i c h t h e y c a n b e c o m e p a s s i o n a t e .

H o w d o w e h e l p s t a f f g a i n i n s i g h t i n t o w h a t t h e y s h o u l d b e p a s s i o n a t e a b o u t ?

H o w d o w e h e l p b u s i n e s s p a r t n e r s d i s c o v e r n e w i d e a s f o r r e s h a p i n g m e m b e r, p r o d u c t a n d p a r t n e r e x p e r i e n c e s ?

H o w d o w e h e l p s t r a t e g i s t s f i n d b u s i n e s s o p p o r t u n i t i e s ?

H o w d o w e b e c o m e f i r s t t o m a r k e t ?

H o w d o w e a n t i c i p a t e o u r n e x t c h a l l e n g e ?

H o w d o w e s e p a r a t e n o i s e f r o m u s e f u l i n f o r m a t i o n ?

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Top Performing CompaniesForrester 2012

T h e r e i s a s t r o n g a l i g n m e n t b e t w e e n d a t a a n d b u s i n e s s p r o c e s s e s a n d t h e p e o p l e r e s p o n s i b l e f o r b o t h - 6 6 %

To p p e r f o r m e r s a r e 3 2 % m o r e l i k e l y t o u t i l i z e e x t e r n a l d a t a s o u r c e s

To p p e r f o r m e r s a r e 2 4 % m o r e l i k e l y t o e x p a n d b e y o n d c u s t o m e r a n d p r o d u c t d a t a

Ty p i c a l o r g a n i z a t i o n s s t i l l s t r u g g l e w i t h t h e f o u n d a t i o n s o f t h e d a t a q u e s t i o n s … . t o p p e r f o r m e r s s t r u g g l e w i t h c e i l i n g s

Ty p i c a l o r g a n i z a t i o n s s t r u g g l e w i t h w h o w i t h i n t h e o r g a n i z a t i o n o w n s t h e d a t a a n d c r e a t e d a t a s i l o s ; t o p p e r f o r m e r s h a v e d e m o c r a t i z e d t h e i r d a t a

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What is Big Data?Te rm o r i g i na l l y c o i ned t o des c r i be t he mas s i v e amoun ts o f da ta co mp i l ed by o rgan i z a t i ons l i k e Goog l e an d t he U S g ove rnmen t .

T h e s i z e o f t he da ta se t s s u rpas s ed t he l i m i t s o f t r ad i t i ona l da ta ana l y t i c t oo l s ; new t oo l s r equ i r ed t o s i f t ou t i n s i gh t s o f vas t da ta r es ou rce .

5 V ’s :

Volume

Velocity

Variety

Veracity

Value

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3 Things1. B e m o r e t h a n t h e B u z z w o r d

2. B e i n t h e K n o w

3. S h o w t o Te l l

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Where does Big Data begin?

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The Real i ty of “Big” DataMonth Division v0 Campaigns v0 Tactic Type v0 Tactic v0

March 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Offline FaxMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Offline Direct mailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Board Review Express 2012 EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Offline Direct mailMarch 2012Continuing Medical Education Board Review Express 2011 P&SMarch 2012Continuing Medical Education 2012 CME Portfolio EmailMarch 2012Continuing Medical Education 2012 CME Portfolio Email

2009 - Hyatt Regency Washington, DC  Wed Thurs Fri Sat Sun Mon Tue Mon Tues Wed

 

Total P/U %Date 8-Jul 9-Jul 10-Jul 11-Jul 12-Jul 13-Jul 14-Jul 15-Jul    Block 0 0 0 0 40 50 40       130

92%P/U 1 1 4 12 30 48 22 1     119

Attrition Set At: 80%Attrition Fee's paid: $0Room Rate: $xxxRoom Revenue $xx,xxxF/B (excluding T/G)F/B (including T/G) $xx,xxxNumber of Attendees: 115Comments:

Speaker Name OverallAverage Practical_KnowledgeAverage ReleventAverage BarriersAverage DifficultyAverage #SessionsSample Speaker 4.43 4.35 4.37 4.12 3.32 6Sample Speaker 4.70 4.64 4.51 4.42 3.35 2Sample Speaker 4.57 4.43 4.50 4.31 3.32 2Sample Speaker 4.29 4.15 4.26 3.89 3.40 2Sample Speaker 4.10 4.15 4.26 3.89 3.40 2Sample Speaker 4.11 4.15 4.26 3.89 3.40 2Sample Speaker 4.47 4.34 4.48 4.11 3.33 4Sample Speaker 4.54 4.46 4.47 4.24 3.49 4Sample Speaker 4.20 3.99 4.19 3.82 3.34 2Sample Speaker 4.81 4.76 4.73 4.53 3.41 8Sample Speaker 4.54 4.46 4.36 4.20 3.34 2Sample Speaker 4.62 4.45 4.58 4.32 3.70 1Sample Speaker 4.41 4.23 4.35 4.15 3.33 2Sample Speaker 4.62 4.39 4.21 4.31 3.28 5

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Opinion-Based Data-Driven

Experience

People

Time

Want

Can

8%

Speed to Opinion(Weeks/Months)

Conventional Self-Reliant

Speed to Insight(Seconds/Minutes)

Want Can

80%

Report Factory

App

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From Here to ThereMonth Division v0 Campaigns v0 Tactic Type v0 Tactic v0

March 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Offline FaxMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Offline Direct mailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Online EmailMarch 2012Continuing Medical Education Board Review Express 2012 EmailMarch 2012Continuing Medical Education Comp Board Review Prep 2012 Offline Direct mailMarch 2012Continuing Medical Education Board Review Express 2011 P&SMarch 2012Continuing Medical Education 2012 CME Portfolio EmailMarch 2012Continuing Medical Education 2012 CME Portfolio Email

2009 - Hyatt Regency Washington, DC  Wed Thurs Fri Sat Sun Mon Tue Mon Tues Wed

 

Total P/U %Date 8-Jul 9-Jul 10-Jul 11-Jul 12-Jul 13-Jul 14-Jul 15-Jul    Block 0 0 0 0 40 50 40       130

92%P/U 1 1 4 12 30 48 22 1     119

Attrition Set At: 80%Attrition Fee's paid: $0Room Rate: $xxxRoom Revenue $xx,xxxF/B (excluding T/G)F/B (including T/G) $xx,xxxNumber of Attendees: 115Comments:

Speaker Name OverallAverage Practical_KnowledgeAverage ReleventAverage BarriersAverage DifficultyAverage #SessionsSample Speaker 4.43 4.35 4.37 4.12 3.32 6Sample Speaker 4.70 4.64 4.51 4.42 3.35 2Sample Speaker 4.57 4.43 4.50 4.31 3.32 2Sample Speaker 4.29 4.15 4.26 3.89 3.40 2Sample Speaker 4.10 4.15 4.26 3.89 3.40 2Sample Speaker 4.11 4.15 4.26 3.89 3.40 2Sample Speaker 4.47 4.34 4.48 4.11 3.33 4Sample Speaker 4.54 4.46 4.47 4.24 3.49 4Sample Speaker 4.20 3.99 4.19 3.82 3.34 2Sample Speaker 4.81 4.76 4.73 4.53 3.41 8Sample Speaker 4.54 4.46 4.36 4.20 3.34 2Sample Speaker 4.62 4.45 4.58 4.32 3.70 1Sample Speaker 4.41 4.23 4.35 4.15 3.33 2Sample Speaker 4.62 4.39 4.21 4.31 3.28 5

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The concept is simple

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People remember 10% of what they hear,20% of what they read and

80% of what they see and do.

“Ideal visualization should not only communicate clearly, but stimulate viewer

engagement and attention.”(Friedman, 2008)

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Data Visualizers / BI Tools

• Ta b l e a u• Q l i k Te c h• S p o t f i r e

• Microstrategy

• SAP

• Microsoft

• SAS

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Agility, Adopt, Advocate

A3

ID

Opportunity

Central

Source

Visualize

Data

Target

Audiences

Explore &

Discover

Enabled

Users

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AAFP Strategy for Big DataAna lyze da ta i n “ p l ace . ”

Stop the movement of data into and out of netForum or into other databases, if appropriate.

Traditional approaches to the analysis of data required that data be moved to a central location with its own infrastructure.

This is expensive to manage & operate, creates data redundancy and prevents real-time analysis.

Ana l yze da ta i n r ea l t ime , as app rop r i a te . Move away f r om cop ies o f da ta :

that are analyzed and reported weeks after the event

or remain out of date for continuous events.

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Strategy for Big Data(continued)

Reduce the amount o f t ime i t takes to d iscover, t rans fo rm, deve lop , score , ana lyze , and pub l i sh resu l ts .

Visualize results and integrate with front-end applications.

Allow staff to make strategic insights into what the data means in real time; not weekly, quarterly when a new report is issued

Buy / ren t da ta as appropr ia te ra ther than con t inue to expens ive ly co l lec t i t .

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Strategy for Big Data(continued)

D e m o c r a t i z e d a t a a c r o s s t h e A s s o c i a t i o nAllow business units to access all Association data, if appropriate, to assist in making their decisions. Eliminate as appropriate data silos, if any exist.

S e t t h e e x p e c t a t i o n a m o n g b u s i n e s s u n i t l e a d e r s t h a t t h e i r b u s i n e s s s t r a t e g y i s t i g h t l y i n t e g r a t e d w i t h t h e i r d a t a s t r a t e g y.

Training on new business intelligence (BI) tools is an expectation for their managerial position as well as selected staff whom they designate. This expectation is not negotiable, regardless of the skill level of current staff. Set the expectation that business unit managers will ask what-if type data questions and receive real time answers.

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Tactics for Big DataW e s c a l e d b a c k o n I T r e p o r t w r i t e r s .

T h e A A F P c h o s e Ta b l e a u a s t h e p r i m a r y B I t o o l f o r A A F P s t a f f . I n a r e c e n t s t u d y o f B I a n d a n a l y t i c s p l a t f o r m s , G a r t n e r c l a s s i f i e d Ta b l e a u a s o n e o f t h e l e a d e r s i n t h i s g r o w i n g f i e l d .

C o n t i n u e t o u s e o u t s i d e Ta b l e a u c o n s u l t a n t s t o a s s i s t I T i n a d o p t i n g b e s t p r a c t i c e s w i t h r e s p e c t t o a s s o c i a t i o n a n d i n d u s t r y r e p o r t i n g s t a n d a r d s .

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Tactics for Big Data(continued)

A s s i g n a n I T B u s i n e s s A n a l y s t h a l f - t i m e f o r s i x t o 1 2 m o n t h s t o w o r k w i t h t h e b u s i n e s s u n i t s i n d e f i n i n g , s t r a t e g i z i n g a n d i m p l e m e n t i n g t h e i r d a t a a n a l y t i c s t r a t e g y.

For each business unit, understand data sources, figure out what data is available within a particular source, get a sense of its quality and relationships to other data.

Understand the business unit metrics and how data can be used to measure success.

Identify and address gaps in data that each business unit needs to fulfill its strategies. Investigate how these data may be purchased.

Identify data that is collected that is of little or no value to the business unit – stop it.

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Are you a candidate for a Big Data solution?

I f t h e A n s w e r i s y e s t o 3 o r m o r e q u e s t i o n s b e l o w – t h e n p e r h a p s y o u a r e a c a n d i d a t e f o r a B i g D a t a S o l u t i o n :

If you have staff spending any time producing reports on data residing in Association databases (e.g., netForum, Datatrax, etc.) using Excel, data exports, queries

If you have trouble keeping staff trained on the reporting tools for your databases OR if those tools are hard to use or buggy

If you have staff producing reports that are out of date within days and you need more timely reports based upon current information

If you have staff examining data anomalies in Association databases

If you need answers to ad hoc questions about data contained in Association databases and have to wait for someone not in your division to answer your data questions

If any of your staff indicate that they cannot get to their data

If you have staff who indicate that IT is the impediment to accessing their data

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Sample Dashboards

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Sample Dashboards

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Sample Dashboards

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Sample Dashboards

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Putting It ALL TogetherS i m p l e t o S t a r t

Live Examples

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Contact UsB r y c e G a r t n e r

F o u n d e r & C h i e f E x p e r i e n c e O f f i c e r

i c i m o , L L C

@ b r y c e g a r t n e r

b r y c e @ i c i m o . c o m

G o r d o n S c h m i t t l i n gC h i e f I n f o r m a t i o n O f f i c e rA m e r i c a n A c a d e m y o f F a m i l y P h y s i c i a n sg s c h m i t t @ a a f p . o r g

P r a b h a s h S h r e s t h aV i c e P r e s i d e n t o f I n f o r m a t i o n Te c h n o l o g yT h e A m e r i c a n G a s t r o e n t e r o l o g i c a l A s s o c i a t i o np s h r e s t h a @ g a s t r o . o r g