DataPalooza 2022
This is the eBook for DataPalooza 2022, held virtually on October 18-20, 200.
DataPalooza 2022
October 18-20, 2022
Data Literacy and the Pioneer’s Advantage
CSBS DataPalooza October 18, 2022 12:45pm – 1:30pm EST
Valerie Logan, CEO & Founder, The Data Lodge
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© 2019- 2022 The Data Lodge, Inc. All rights reserved.
© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
Do you speak a 2 nd language?
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© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
Do you speak a 2 nd language?
Do you “speak data”?
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© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
XFMDPNF
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© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
XFMDPNF WELCOME
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© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
Data Literacy and the Pioneer’s Advantage
• The Market, Myths & Momentum (what)
• the role of pioneers (WHO)
• Making data literacy personal (HOW)
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© 2019- 2022 The Data Lodge, Inc. All rights reserved.
Data Literacy and the Pioneer’s Advantage
• The Market, Myths & Momentum
• the role of pioneers
• Making data literacy personal
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© 2019- 2022 The Data Lodge, Inc. All rights reserved.
PRIMARY RESEARCH: DATA LITERACY Key Findings
1HZ 9DQWDJH 3DUWQHUV 'DWD DQG $, /HDGHUVKLS ([HFXWLYH 6XUYH\ -DQXDU\ )RUHZRUG %\ 7KRPDV + 'DYHQSRUW DQG 5DQG\ %HDQ • A new high of 73.7% of organizations surveyed have appointed a Chief Data and Analytics Officer (CDAO), up from 12.0% when this survey was first conducted in 2012. • Yet, 59.8% of these organizations see the Chief Data and Analytics Officer (CDAO) role as still nascent and evolving, and 44.2% have struggled with turnover in the role. • 2UJDQL]DWLRQV FRQWLQXH WR VWUXJJOH WR EHFRPH GDWD GULYHQ ZLWK RQO\ UHSRUWLQJ KDYH DFKLHYHG WKLV JRDO DQG RQO\ UHSRUWLQJ KDYLQJ HVWDEOLVKHG D GDWD FXOWXUH • &XOWXUDO LPSHGLPHQWV UHPDLQ WKH JUHDWHVW EDUULHU WR RUJDQL]DWLRQV EHFRPLQJ GDWD GULYHQ ZLWK RI VXUYH\ UHVSRQGHQWV LGHQWLI\LQJ WKLV DV WKH JUHDW FKDOOHQJH • Data ethics is emerging as an issue of rising importance, with just 44.1% of organizations reporting well-established data and AI ethics policies and practices in place, and only 21.6% responding that the industry has done enough to address data and AI ethics.
© 2019- 2022 The Data Lodge, Inc. All rights reserved.
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The State of Data Literacy 2022 The Tipping Point • $Q 8QH[SHFWHG $ZDNHQLQJ DQG 7LSSLQJ 3RLQW • 'DWD /LWHUDF\ MXVW JRW UHDO &DQ QR ORQJHU EH LJQRUHG • &ULWLFDO WR ZRUNIRUFH XSVNLOOLQJ DQG IRVWHULQJ GDWD LQIRUPHG FXOWXUHV¬ • ¬DQG FULWLFDO WR OLYLQJ GDWD LQIRUPHG OLYHV DV SDUHQWV SDWLHQWV FRQVXPHUV WUDYHOHUV HQWKXVLDVWV FLWL]HQV IULHQGV IDPLOLHV DQG FRPPXQLWLHV
• 'DWD OLWHUDF\ HPHUJHV DV D NH\ SDUW RI WKH &'2 $JHQGD • $ FRUQHUVWRQH RI D PRGHUQ 'DWD $QDO\WLFV VWUDWHJ\ • %XW RIWHQ YLHZHG DV MXVW ´WUDLQLQJµ RU YLVXDOL]DWLRQ
© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
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The State of Data Literacy 2022 What’s in a name?
$ 9DULHW\ RI &RPPRQ 5HODWHG 7HUPV 8VHG
• Data Literacy • Data Fluency • Data Acumen • Data Capability • Data Competency • Data Proficiency • Analytics Capability • Data Culture • Data Science for Everyone
• AI for Everyone • Digital Dexterity • Digital Literacy • Business Literacy • Information Literacy • AI Literacy • and more…!
© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
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SETTING CONTEXT What is Data Literacy?
Data Literacy: The ability to read, write, and communicate with data in context — in both work and life. MINDSET Being open, willing & curious. Seeing the world through data glasses. LANGUAGE Business, Data + Analytics Acumen. “Speaking Data” as a shared language.
SKILLS Thinking critically. Engaging others. Applying data constructively.
© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
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Setting Context Describing Data Literacy
POOR/LIMITED DATA LITERACY
Don’t want to share data
Reacting, assuming, avoiding
Assume, don’t know sources, quality
I’m not sure
Just give me all the data
GOOD/STRONG DATA LITERACY
Curious, asking questions
Describing the problem to solve
Confidently telling a data story
Let’s collaborate
I will find help
© 2019- 2022 The Data Lodge, Inc. All rights reserved.
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Setting Context The Need for a Shared Language
CEOs, Boards, Executives
Chief Digital Officers, CMOs, CSOs
Chief Data Officers Chief Analytics Officers
'LYHUVLW\ LV GHVLUHG DQG KHDOWK\ Yet it can result in
CISOs CIOs CTOs
Data Architects & Data Engineers
Business Function professionals (including managers, marketers, sales, HR and finance)
&UHDWLQJ DQG QXUWXULQJ D VKDUHG ODQJXDJH LV IXQGDPHQWDO
natural communication friction and disconnects.
Data Scientists, AI/ML Developers
DIVERSITY OF ROLES
&UHDWRUV
&RQVXPHUV
Business Analysts
Consultants & Solution Providers
'LYHUVH %DFNJURXQGV •
Citizen Data Scientists
Industry sector experience Business domain experience
• •
Data, Software and Platform Providers
Data versus analytics backgrounds
Business Operations Management
Global vs. local
• •
Academia, Research & Education Service Providers
Veterans vs. rookies
Front-line Associates (including teachers, doctors, drivers, customer service reps and agents)
Life Roles (Citizens, Parents, Consumers, Patients, Enthusiasts, etc.)
© 2019 - 2022 The Data Lodge, Inc. All rights reserved. [Adapted from Previously Published Research while at Gartner]
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Setting Context The Need for a Shared Language
Data-Informed Leadership
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MASTERY (To coach & help others.)
FLUENCY (To apply and create.)
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LITERACY: (To understand, do & work with. The ability to read, write & communicate with data in context.)
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A Few Examples Mindset
GET CURIOUS:
LIMITING BELIEFS:
I’m not a data person.
That’s an IT thing.
I’m not good at math.
This isn’t relevant to me.
© 2019 – 2022 The Data Lodge, Inc. All rights reserved.
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Fostering Data Literacy with ISL The Need for a Shared Language
Information as a Second Language® (ISL): The Foundation for Data Literacy
ISL 3.0
© The Data Lodge, Inc.
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6.,//6
• 7KLQNLQJ (how do you process?)
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86( &$6(
/$1*8$*( '(9(/230(17 • Training • Professional Development • Community • Communications • Coaching • Embedding
/(9(/6 2) 352),&,(1&< • Conversational • Intermediate • Fluent • Bilingual • Multilingual
,
$
',$/(&76 • Industry • Business Process • Topic • Company
• (QJDJLQJ (how do you interact?)
92&$%8/$5< • Value (V) • Information (I) • Analysis (A)
(
• $SSO\LQJ (how do you add value?)
$
[Adapted from Previously Published Research while at Gartner]
© 2019 - 2022 The Data Lodge, Inc. All rights reserved.
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A Few Examples Language- Shared Vocabulary
EXAMPLE: Say you are part of a newly assembled diverse team that is exploring a new use case. Can you explain what you know to someone else in a way that they can understand it?
Value What is the question, business problem or target outcome? How is value realized?
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GET CURIOUS:
86( &$6(
,
$
Source: WIRED 5 Levels
Information What data or data sources are involved?
Analysis What analytical or data science methods are applied to the data?
© 2019 – 2022 The Data Lodge, Inc. All rights reserved. [Adapted from Previously Published Research while at Gartner]
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A Few Examples Language- Business Value (Metrics & KPIs)
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FRQVHTXHQFHVµ FRXOG EH RFFXUULQJ EDVHG RQ \RXU PHWULFV DQG .H\ 3HUIRUPDQFH ,QGLFDWRUV .3,V "
© 2019- 2022 The Data Lodge, Inc. All rights reserved.
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A Few Examples Language- Understanding Data Sources
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© 2019- 2022 The Data Lodge, Inc. All rights reserved.
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A Few Examples Skills- Thinking with Data: Cognitive and Confirmation Bias
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6HH ´ &RJQLWLYH %LDVHV 7KDW 6FUHZ 8S © 2019- 2022 The Data Lodge, Inc. All rights reserved. 21 A Few Examples Skills- Engaging with Data: Basics of Telling a Story with Data QUESTION: Data storytelling is both an art and science. How confident are you, and your colleagues, at telling a story with data? GET CURIOUS - Pick one of the twelve Data Story Telling lessons for the week. Take 10 minutes to explore and practice as part of a team meeting. Source: Twelve One-minute Data Story Telling Lessons © 2019- 2022 The Data Lodge, Inc. All rights reserved. 22 Key Needs & Drivers Why Data Literacy Matters WHY DATA LITERACY? 1. To upskill your workforce as part of broader digital dexterity. 2. To unlock radical collaboration and innovation using data. 3. To maximize capacity and talent of your Data & Analytics professionals. 4. To foster a data-informed and insight-driven culture . AN INSURANCE POLICY TO REALIZE VALUE FROM YOUR DATA & ANALYTICS INVESTMENTS. © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 23 Data Literacy and the Pioneer’s Advantage • The Market, Myths & Momentum • the role of pioneers • Making data literacy personal 24 © 2019- 2022 The Data Lodge, Inc. All rights reserved. Learning from Pioneers What is a Pioneer? 3LRQHHU noun • a person who is among those who first enter or settle a region, thus opening it for occupation and development by others. • one who is first or among the earliest in any field of inquiry, enterprise, or progress verb • to be the first to open or prepare (a way, settlement, etc.). • to take part in the beginnings of; initiate 7KH\¬ • *R ILUVW $QG KDYH ILUVW PRYHU DGYDQWDJH (The Pioneer ’s Advantage) • +DYH JULW UHVLOLHQF\ DQG UHVRXUFHIXOQHVV (The Pioneer Spirit) © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 25 Pioneers Lead the Way 7KH )RUG (QJOLVK 6FKRRO )RVWHULQJ VKDUHG ODQJXDJH DFURVV GLYHUVH LPPLJUDQW ZRUNHUV IRU HQKDQFHG VDIHW\ HIILFLHQF\ ´$ ODUJH SHUFHQWDJH RI WKH HPSOR\HHV LQ WKH IDFWRU\ FRXOG QRW VSHDN WKH (QJOLVK /DQJXDJH ZKLFK QHFHVVLWDWHG WKH HPSOR\PHQW RI D ODUJH QXPEHU RI LQWHUSUHWHUV ¬ HVVHQWLDO WKDW D ZRUNPDQ KDYH D NQRZOHGJH RI (QJOLVK IURP D 6DIHW\ )LUVW VWDQGSRLQW What Can we Learn from History? 7KLV NQRZOHGJH DOVR KHOSV WR PDNH EHWWHU FLWL]HQV µ '$7$ /,7(5$&< ,6 7+( 1(: 6+$5(' /,7(5$&< 2) 285 ',*,7$/ (5$ http://www.autolife.umd.umich.edu/Labor/L_Overview/FordEnglishSchool.htm © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 26 Learning From Literacy Pioneers 'DWD /LWHUDF\ LV WKH QHZ EDVHOLQH OLWHUDF\ RI RXU WLPH RI What Can we Learn from Pioneers in Other Areas? GLJLWDO VRFLHW\ 5XWK &ROYLQ 'ROO\ 3DUWRQ %DUEDUD %XVK “Inspiring kids to love to read became my mission…. here we are today with a worldwide program that gives a book a month to well over 1 million children.” “The American Dream is about equal opportunity for everyone who works hard. If we don’t give everyone the ability to simply read and write, then we aren’t giving everyone an equal chance to succeed.” “Because you can’t read doesn’t mean you’re dumb. In fact, you’re really very smart, because you’re able to cope without the skills that we take for granted. So once you can tap that and give them the self confidence, and give them the basic skills, they can do anything.” https://proliteracy.org/Blogs/Article/326/Women-in-Literacy-The-Pioneers © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 27 About Data Literacy Programs For companies, agencies, non-profits, etc. $Q LQWHQWLRQDO FRPPLWPHQW WR XSVNLOOLQJ WKH ZRUNIRUFH DQG FXOWXUH • to enable the full SRWHQWLDO RI DOO associates • with a VKDUHG PLQGVHW ODQJXDJH DURXQG GDWD DQG PRGHUQ GDWD OLWHUDF\ VNLOOV (e.g. critical thinking, data storytelling, understanding data bias, blending insights with judgment, etc.) • at the PRPHQWV WKDW PDWWHU (to drive growth, reduce cost, mitigate risk, delight customers, improve data quality, innovate across functions, etc.) What is a Data Literacy Program? WKURXJK D FRPELQDWLRQ RI HQJDJHPHQW GHYHORSPHQW DQG HQDEOHPHQW DFWLYLWLHV © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 28 Data Literacy Pioneers Program Elements What’s included in a Robust Data Literacy program? '(9(/230(17 Language Development Learning: Self-Paced Professional Development & Training (1$%/(0(17 Technology Augmentation, Enablement Resources & Support (1*$*(0(17 Leadership Community Communications '$7$ /,7(5$&< 352*5$0 0$1$*(0(17 © The Data Lodge, Inc. 6XFFHVV )DFWRUV 9 )RVWHULQJ GDWD OLWHUDF\ ERWK WRS GRZQ DQG ERWWRP XS JUDVV URRWV 9 0DNLQJ GDWD OLWHUDF\ ´SDUW RIµ HYHU\WKLQJ ZH GR © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 29 Data Literacy Program Pioneers who is doing this? Read/Hear their stories! )ULHQGV RI 7KH 'DWD /RGJH (;$03/(6 3XEOLF 6HFWRU • &DQDGD 6FKRRO RI 3XEOLF 6HUYLFH 'LJLWDO $FDGHP\ • (PSOR\PHQW 6RFLDO 'HYHORSPHQW ( 6' &DQDGD • 1HSDO 'DWD /LWHUDF\ IRU 3URVSHURXV 1HSDO • 8 6 'HSDUWPHQW RI (GXFDWLRQ (;$03/(6 1RW IRU 3URILW 2WKHU • 'DWD 6FLHQFH IRU (YHU\RQH '6( &RDOLWLRQ IRU . HGXFDWLRQ • +DUYDUG 8QLYHUVLW\ 6WUDWHJLF 'DWD 3URMHFW 6'3 • ,QWHUQDWLRQDO 5HG &URVV • 1DWLRQDO 6WXGHQW &OHDULQJKRXVH (;$03/(6 &RPPHUFLDO • $LUEQE • /XULH &KLOGUHQ
V +RVSLWDO • &KLFN ILO $ • 0D\R &OLQLF • 'XNH 8QLYHUVLW\ +HDOWK 6\VWHP • 1DWLRQZLGH %XLOGLQJ 6RFLHW\ • (FRODE • 1RUWKZHVWHUQ 0XWXDO • *HQHUDO 0RWRUV • 5HG +DW • -// • 5HJHQHURQ 30 © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 3 Key Success Factors What do you have to get right? 1 $ &/($5 &$6( )25 &+$1*( :KDW DUH \RX UHDOO\ VROYLQJ IRU" • Start your data literacy program by excavating your clear and compelling case: • Definition • The language root • Needs & drivers • For who? • Mitigate myths & misconceptions Data Literacy is just a work skill Data Literacy = Training Data Literacy = Data Visualization and Storytelling Data Literacy is about internal structured data and statistics Data Literacy is about making everyone a junior data scientist © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 31 3 Key Success Factors What do you have to get right? 'LJLWDO 7UDQVIRUPDWLRQ ´'LJLWDO 'H[WHULW\µ &217(;7 $'-$&(1&,(6 +RZ GRHV 'DWD /LWHUDF\ ILW RU DOLJQ ZLWK RWKHU SURJUDPV DQG HIIRUWV" • Data & Analytics, Digital, and HR/Workforce Development • Related D&A programs • Making Data Literacy “part of”, not separate 2 '$7$ /,7(5$&< +5 :RUNIRUFH 'DWD $QDO\WLFV ´'DWD 'ULYHQ &XOWXUHµ 'HYHORSPHQW ´)XWXUH RI :RUNµ © The Data Lodge, Inc. © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 32 3 Key Success Factors What do you have to get right? $3352$&+ .H\ 6WHSV a) Determine the 6SRQVRU DQG D /HDG . b) Develop the Narrative. Document the &DVH IRU &KDQJH . Make data literacy explicit- give it a brand/identity. c) Craft your %OXHSULQW DQG LQLWLDO 3ODQ , and inventory what you already have underway to leverage. Make it “part of”. d) Explore data literacy and “speaking data” with some SLORW ZRUNVKRSV across diverse business/data/quant groups. Make it personal. De-mystify it and replace fear with fun. e) Launch pragmatically with TXLFN ORZ FRVW ZLQV f) Share the stories. (QJDJH WKH OHDGHUV DQG LQIOXHQFHUV at all levels. Ignite bottom-up momentum. g) Enhance the case by teaming with HR and other key partners. Refine your SODQ IRU VFDOH . 3 *(77,1* 67$57(' +RZ WR VWDUW ZRUN VPDUW DQG QRW ZDVWH WLPH UHVRXUFHV" • Don’t go it alone • Make most of what exists internally and externally • Beware of a market that is still emerging © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 33 3 Key Success Factors What do you have to get right? 1 2 3 $ &/($5 &$6( )25 &+$1*( :KDW DUH \RX UHDOO\ VROYLQJ IRU" • Start your data literacy program by excavating your clear and compelling case: • Definition • The language root • Needs & drivers • For who? • Mitigate myths & misconceptions &217(;7 $'-$&(1&,(6 +RZ GRHV 'DWD /LWHUDF\ ILW RU DOLJQ ZLWK RWKHU SURJUDPV DQG HIIRUWV" • Data & Analytics, Digital, and HR/Workforce Development • Related D&A programs • Making Data Literacy “part of”, not separate *(77,1* 67$57(' +RZ WR VWDUW ZRUN VPDUW DQG QRW ZDVWH WLPH UHVRXUFHV" • Don’t go it alone • Make most of what exists internally and externally • Beware of a market that is still emerging © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 34 Data Literacy and the Pioneer’s Advantage • The Market, Myths & Momentum • the role of pioneers • Making data literacy personal 35 © 2019- 2022 The Data Lodge, Inc. All rights reserved. Making It Personal We are all part of this movement. Data Literacy: The ability to read, write, and communicate with data in context — in both work and life. MINDSET Being open, willing & curious. Seeing the world through data glasses. LANGUAGE Business, Data + Analytics Acumen. “Speaking Data” as a shared language. SKILLS Thinking critically. Engaging others. Applying data constructively. © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 36 Making It Personal A Challenge For You 'XULQJ WKH 1H[W 'D\V RI 'DWD3DORR]D IXQ EH RQ WKH ORRNRXW DQG FDSWXUH WKH IROORZLQJ • 0,1'6(7 Jot down examples of where you see signs of… • Limiting Beliefs (e.g., “I’m not a data person…”) • 2-3 examples of Strong/Good data literacy • 2-3 examples of Poor/Limited data literacy What Can You Do over the Next 3 days at DataPalooza? • /$1*8$*( Capture a list of at least 5 terms that you observe that are not commonly understood or shared as a common language among attendees. • Business acumen/value (V), data/information acumen (I) and analytics acumen (A) • 6.,//6 Related to the skills of storytelling and engaging others, be on the lookout for GREAT data storytellers, and those who “are not”. • What do the GREAT data storytellers do specifically that makes them standout? • And what’s missing for those that don’t hit the mark? ¬ WKHQ VKDUH WKLV EDFN ZLWK \RXU RZQ WHDP DV DQ LQWUR WR 'DWD /LWHUDF\ © 2019 - 2022 The Data Lodge, Inc. All rights reserved. 37 CRISIS DOESN’T CHANGE PEOPLE; IT REVEALS THEM. NEVER DOUBT THAT A SMALL GROUP OF THOUGHTFUL, COMMITTED CITIZENS CAN CHANGE THE WOR D. INDEED, IT IS THE ONLY THING THAT EVER HAS. Eric Walters s Margaret Mead © 2019 - 2022 The Data Lodge, Inc. All rights reserved. Data Literacy and the Pioneer’s Advantage 9 The Market, Myths & Momentum 9 the role of pioneers 9 Making data literacy personal 39 © 2019- 2022 The Data Lodge, Inc. All rights reserved. Where Do I Go to Learn More? Key Resources 7KH 'DWD /RGJH :HELQDU 6HULHV https://www.thedatalodge.com/blog?tag=webinar -RLQ WKH /LQNHG,Q 'DWD /LWHUDF\ $GYRFDWHV *URXS https://www.linkedin.com/groups/13653008/ 7KH 'DWD /LWHUDF\ 3URMHFW https://thedataliteracyproject.org/ DQG DPD]LQJ 'DWD 6WRU\WHOOLQJ 5HVRXUFHV • Story-Telling Lessons • Charts & Graphs: Best-of Examples • One-minute Data Storytelling Lessons 'DWD /LWHUDF\ $VVHVVPHQWV DQG &RXUVHV • Data to the People- with Data Literacy Assessments • dataliteracy.com- with Data Literacy courses and resources © 2019- 2022 The Data Lodge, Inc. All rights reserved. 40 Thank you! Additional Q&A? vlogan@thedatalodge.com © 2019- 2022 The Data Lodge, Inc. All rights reserved. Internal Use Only Change Leadership: Your Role in Unlocking Data Adoption & Implementation DataPalooza – October 18, 2022 Terrie Szucs SVP, Organizational Strategy & Transformation tszucs@csbs.org Heather Cornett Senior Director, Change Management Office hcornett@csbs.org Internal Use Only Our Focus for Today Basics of Change Management (the People side of Change) Engaging Leaders in Change Engaging Individuals to Change Leading Individuals through Change Leading through Resistance Open Q&A 2 Internal Use Only 5 Tenets of Change Management 3 Internal Use Only What is Adoption of Change? Speed of Adoption Utilization Proficiency Speed of adoption is how quickly employees adopt a change to how they do their jobs when it is introduced by a project or initiative. When the new processes or technologies "go live", how long does it take employees to adopt the change? Ultimate utilization is how many employees eventually adopt the change to how they do their jobs. Proficiency is how effective employees are once they've adopted the change . Proficiency is tied to how the benefit of the change is realized ‐ in process, workflow, technology, tool, system, etc. is How we drive employee adoption and usage to capture the portion of project benefits that depends on people changing how they do their jobs. 4 Internal Use Only Our Focus for Today Basics of Change Management (the People side of Change) Engaging Leaders in Change Engaging Individuals to Change Leading Individuals through Change Leading through Resistance Open Q&A 5 Internal Use Only Change Management versus Change Leadership Change Management • Refers to a methodology, tools or structures intended to drive any change and focus on adopting the new changes Change Leadership • Focuses on the driving forces, visions and processes that fuel strategy and transformational change • Equips the agency to bring the changes to life to achieve the strategies • Delivers change outcomes through bringing the people/employees along • Demonstrates commitment by ensuring the people side of the changes have the right effort, time and resources Active and visible support of the change by leadership is the #1 contributor to change success 6 Internal Use Only What does Change Leadership look like? • Getting past the head nod • Demonstrating commitment • Remaining Visible throughout • Demonstrating support and advocacy • Championing the change • Influencing others • Asking probing questions • Focusing on What, Why, How actually matter • Building trust • Showing up everyday 7 Internal Use Only Our Focus for Today Basics of Change Management (the People side of Change) Engaging Leaders in Change Engaging Individuals to Change Leading Individuals through Change Leading through Resistance Open Q&A 8 Internal Use Only A Change Leader Question: What can an individual do to accept and adopt change? Stay Positive ‐ Before, During and After the change Before the Change During the Change After the Change • Ask questions about the future • Ask how the change will impact day ‐ to ‐ day operations • Provide input to the solution • Find out what new skills and abilities you will need to perform effectively after the change is in place • Assess your own strengths and weaknesses • Seek training that will be available to fill skill gaps • Take advantage of the change to develop new skills and grow professionally • Reinforce the change with peers and subordinates • Help the business achieve the objectives of the change (be results ‐ oriented) • Avoid reverting back to old processes or ways of doing work when problems arise with the new processes and systems • Help solve problems that arise with new work processes and tools. • Learn about the change • Ask how you can help • Find out how you can prepare for the change • Display a positive outlook • Encourage constructive conversations with fellow employees • Be open and honest with your feedback about the change • Be quiet and observe, which is OK during the early phases of a change Adapted from book: Employee’s Survival Guide to Change Copyright © 2012 by Prosci Inc. All rights reserved. Each person has a choice and an accountability for change. ** Blank template in Appendix 9 Internal Use Only Our Focus for Today Basics of Change Management (the People side of Change) Engaging Leaders in Change Engaging Individuals to Change Leading Individuals through Change Leading through Resistance Open Q&A 10 Internal Use Only ADKAR- An Individual Model for Change This model was developed by Prosci Inc. to: • Equip leaders with the right strategies and tools • Enable leaders to focus their activities on what will drive individual change and therefore achieve agency results • Provide individuals with the right information • Create motivation and ability to successfully move through changes in the agency The Prosci ADKAR® Model | Prosci 11 Internal Use Only Use ADKAR as your Tool for Change • Ensure targeted communication explaining Why, why now and what are the risks if not now • Provide the rationale for the direction • If this isn’t present, it may prevent employees from adopting the change Awareness • Compel employees to want to participate, engage, support • May not be about love or like • If this isn’t present, change fails Desire • What do people need to know • This is the training part • If this isn’t present, employees can't demonstrate new skills, aren’t learning the new way Knowledge • This is where adoption and benefit realization happen • Where you see the behavior changes, new skills emerge, increased proficiency • If this isn’t present, you don’t see the intended results because employees are performing in new way Ability • Will employees and leadership commit to the change • How the change is sustained and ingrained into the teams • If this isn’t present, people find work arounds, go back to old ways, revert back Reinforcement 12 Internal Use Only Our Focus for Today Basics of Change Management (the People side of Change) Engaging Leaders in Change Engaging Individuals to Change Leading Individuals through Change Leading through Resistance Open Q&A 13 Internal Use Only Identify, Manage and Understand Resistance? Resistance is a natural response to change and can be destructive Resistance can also be constructive and improve change outcomes. 14 Internal Use Only Resistance 15 Internal Use Only Contact Heather Cornett CSBS Sr. Director, Change Management Office hcornett@csbs.org Terrie Szucs CSBS SVP, Organization Strategy & Transformation tszucs@csbs.org Resources Change Management Resource Center | Prosci Change Management Free Downloads | Prosci Change Management Free Downloads | Prosci | ADKAR Change Management Blog - Prosci 16 Internal Use Only Appendix Templates Internal Use Only Template: 5 Key Messages to Drive Change Question Answer What is changing? Why are we changing? Why Data Why are we changing now ? What is not changing? What is the risk of not changing? (Why is the way we do things today no longer good enough?) These key questions are critical for early engagement to change. Internal Use Only Template Think about implementing Data Analytics across your agency. What do (or what did) individuals need to do in the 3 phases noted in the table below? • Each person has a choice and an accountability for change. How will you build that accountability and engagement? What does adoption look like in these three phases? • How will you know/understand the adoption issue: Skill issue ‐‐ don’t know how to use it; or Willingness issue ‐‐ not aware or don’t want to use it Before the Change During the Change After the Change Internal Use Only Template: Apply ADKAR Create a roadmap to adopt data analytics capability Knowledge Awareness • Of the need to change • Of the nature of the change Reinforcement Desire • To support the change • To participate and engage Ability • To implement the change • To demonstrate performance • On how to change • On how to implement new skills and behaviors • To sustain the change What activities can you lead to enable individual adoption? Internal Use Only Enabling Analytics Carlos Cordova, Data Scientist, Research & Analytics Internal Use Only Agenda • CSBS.org/DATA • Obtaining a CSBS Account • Supporting Resources • Outlier Dashboard • Risk Identification for State Chartered Institutions (RISCI) • Depository Deep Dive Internal Use Only Data Analytics Landing Page csbs.org/data Internal Use Only Data Analytics Landing Page csbs.org/data Internal Use Only Data Analytics Landing Page DEMO Internal Use Only CSBS account Reach out to our Regulatory User Group to obtain a CSBS account Account needs access to the following: • Analytics – for on platform interactive tools and reports (3D, RISCI, Outliers) • CSBS.org – for economic products available on csbs.org/state-economic-dashboards (State Level Economic Dashboard, Delinquency Rates by State) Regulatory User Group: RUG@csbs.org Internal Use Only O UTLIER D ASHBOARD Internal Use Only OUTLIER DASHBOARD What is it? • Bank list showing key ratios • Filters can be applied to narrow the bank list • Shows a ratio’s value and how its changed over time What are the benefits? • Offsite monitoring • Summary statistics • Custom peer comparisons Internal Use Only OUTLIER DASHBOARD DEMO Internal Use Only R ISK I DENTIFICATION for S TATE C HARTERED I NSTITUTIONS (RISCI) Internal Use Only What is RISCI? RISCI is a tool for understanding exceptions scores, which are a numerical representation of risk. RISCI allows users to quickly see how scores are changing and which specific metrics are driving the change. Internal Use Only RISCI Origin Story • Evolved from the Excel Risk Scoping Workbook (ERSW) • Utilizes the exception scoring framework • Includes multiple time periods for trend analysis • ERSW is point in time Internal Use Only Exception Scoring Framework Ratio Individual Bank High Risk Threshold Breach? Exception Score Tier 1 Leverage Ratio 11% Under 6% No 0 Total Past Due Loans / Total Loans Return on Average Assets 12.8% Above 10% Yes 1 0.2% Under 0.4% Yes 1 Net Interest Margin 5% Under 3% Under 10% No No 0 0 Liquid Assets / Total Assets 23% TOTAL 2 Internal Use Only Narrow the list based on score Input bank certificate number to see bank view Narrow the list based on CHANGE in score Total Exception Score Internal Use Only Internal Use Only See how “Total” Score breaks up between CAEL components Quickly visualize where increases are coming from Buttons take you to “CAEL” specific pages Internal Use Only New exceptions from last quarter Internal Use Only Numerator Denominator Internal Use Only New exceptions from last quarter Internal Use Only RISCI DEMO Internal Use Only Adopting RISCI • Benefits to different levels of state agency • Check out RISCI Resource center watch intro video • https://data.csbs.org/risci • Incorporate RISCI into surveillance process • Monitor any banks who add points to exception score over quarter Internal Use Only D EPOSITORY D EEP D IVE (3D) Internal Use Only Overview • Analysis on an individual bank • 41 pages • 92 charts / graphs • Peer Comparisons • Bank vs State vs All Banks • Customizable time periods / horizons • Calculation Glossary included • Uses quarterly bank call report/UBPR data Internal Use Only Additional Details • Color coded • Easily export to PDF • Governance / maintenance process • Integrates into existing products (Outliers, ERSW) Internal Use Only Use Cases / Audience Pre-exam planning UBPR complement Training tool Banker outreach Internal Use Only Key Pages Internal Use Only Key Pages Internal Use Only Key Pages Internal Use Only Key Pages Internal Use Only Key Pages Internal Use Only Key Pages Internal Use Only Summary of Product Features/Benefits 1. Visual representation of data 2. Ability to view a longer time period 3. Quarterly data to pinpoint timing of ratio changes 4. Comparisons to state and national medians 5. Narrative comments 6. Custom charts Internal Use Only PDF vs Interactive version PDF The PDF version of the report is a static document which cannot be customized. Interactive In the online, interactive version of the Depository Deep Dive users can customize their report. Specifically, users can change the selected quarters and modify formatting such as text, coloring, font, etc. Internal Use Only Internal Use Only DEPOSITORY DEEP DIVE DEMO Internal Use Only Supporting Materials • Product Page https://data.csbs.org/3d/ • User Guide • Cheat Sheet • FAQ • Examiner Perspective Internal Use Only Governance • Feedback Form https://forms.office.com/r/1Aa7ydCZSC • Interest List https://data.csbs.org/3d/ • Used as invite list for periodic report maintenance calls (2-4 times a year) Internal Use Only CONTACT US data@csbs.org rug@csbs.org General data inquiries Account provisioning RESTRICTED Total Eclipse of the Chart Elizabeth Rychlinski RESTRICTED Agenda Who we are New SES Apps MSBCR Compliance Tools MSBCR Analytics Scoping Tools MSBCR Subcommittee RESTRICTED 1983 RESTRICTED 75% RESTRICTED CSBS Research & Analytics What we do • Create analytics tools using NMLS and call report data • Provide customized reports for agencies • Host analytics trainings • Staff call report subcommittees RESTRICTED SES Tools SA Analytics Complaints Analytics RESTRICTED SES SA Analytics: How to Access NMLS login required SA Analytics Must have Analytics user role in NMLS Under the “Home” tab RESTRICTED New SES Data Tools • SA Analytics • Complaints Analytics • What regulators are saying: • “SA Analytics shows promise as a good way to quickly and effectively keep tabs on all ongoing exams at a manager level and compile monthly performance/completion reports” RESTRICTED SES Demo SA Analytics Complaints Analytics RESTRICTED 411 RESTRICTED MSB Tools MMTA Compliance Calculators MSBCR Analytics RESTRICTED MSCBR Analytics: How to Access NMLS login required MSBCR Analytics Must have Analytics user role in NMLS Under the “Home” tab RESTRICTED Profiling with the MSBCR MTMA Prudential Standards: 1. Tangible net worth calculator 2. Permissible investment calculator 3. Surety bond requirement RESTRICTED MTMA Compliance RESTRICTED Tangible Net Worth Compliance calculated with: • Total assets • Good will and other intangibles • Total liabilities RESTRICTED Surety Bond Requirement Compliance calculated with: • Total assets • Average daily transmission liability RESTRICTED Permissible Investments Line item Category Percent allowed Cumulatively allowed PI10 PI20 PI30 PI50 PI60 PI70 PI80 PI90 Deposits in domestic banks Deposits in foreign banks Cash on hand and in transit Irrevocable letter of credit 100% 10% 100% 100% Due from agents – net of allowance for doubtful accounts 50% 20% Investments rated A or its equivalent and above 50% Investments rated BBB or its equivalent and lower non ‐ rated 0% Investments in US Treasury securities 100% Other investments 20% 50% PI100 RESTRICTED Scoping with the MSBCR 1. Outliers 2. Burn Rate 3. Country of Destination 4. Data Flags RESTRICTED MSB Call Report Analytics: Risk Profiling RESTRICTED MSB Call Report Analytics: Outliers RESTRICTED MSB Call Report Analytics: Burn Rate RESTRICTED MSB Call Report Analytics: International Transactions RESTRICTED MSBCR Subcommittee • Purpose • Responsible for ongoing MSBCR development and maintenance • Membership • Two-year terms • Monthly meetings • Current work • Improving data quality following analysis of both state-wide and company-wide reporting inconsistencies RESTRICTED 911 Million RESTRICTED CONTACT US 202-905-2996 erychlinski@csbs.org Conference of State Bank Supervisors 1129 20th Street NW 9th Floor Washington, DC 20036 Internal Use Only CSI: Carlos Simulated Investigation Carlos Cordova, Data Scientist, Research & Analytics Internal Use Only Agenda • Headline investigation • Dashboard creation • Ad hoc requests Internal Use Only Email from coworker Hello Carlos, We’ve been seeing a few headlines about credit card balances increasing. See links below. Can you apply a state-chartered lens to this looking at loans? How have the total amount of credit card loans changed over the past year for the states? • https://www.bankrate.com/finance/credit-cards/fed-consumer-credit-g19/ • https://www.cnbc.com/2022/05/10/consumer-credit-card-debt-near-an-all-time high.html • https://www.lendingtree.com/credit-cards/credit-card-debt-statistics/ Internal Use Only Reply to coworker Internal Use Only Reply to coworker Internal Use Only Email from coworker Hello Carlos, This looks great. Thanks for the info, amazing stuff. Can we expand on this to include all consumer loans? And can we make it a dashboard where users can come in and pick their state? Internal Use Only Email from coworker Hello Carlos, We’ve been hearing that there is an increased focus on tangible capital and FHLB lending. Using these two different formulas, can you see which banks have negative tangible capital? Internal Use Only Email from coworker Internal Use Only CONTACT US data@csbs.org rug@csbs.org General data inquiries Account provisioning Internal Use Only CSBS Predictive Dashboard Carlos Cordova, Data Scientist, Research & Analytics Internal Use Only Predictive Journey • Target Variables • Source Data • Assumptions • Model Development • Model Inputs • Business Rules Internal Use Only Target Variables What are we attempting to predict? 1. Exception Score • When a ratio’s value breaches a specified threshold, an exception is counted 2. Adjusted Texas Ratio • Numerator: Non-Performing Assets + Loans 90 Days Past Due • Denominator: Total Equity Capital + Loan Loss Reserves – Goodwill – Other Intangible Assets Internal Use Only Source Data • Call report data • State-level unemployment data • Economic data from Moody’s Analytics • Mortgage • Delinquency • Bankruptcy • Bank ETF data Internal Use Only Assumptions • Model is built on historical quarterly call report data starting from 2006 • Economic data from Moody’s Analytics is quarterly • Data from state and national community banks were included in the model training and test data • Banks missing necessary data were excluded from the model Internal Use Only Model Development • Identified input variables to help predict high risk banks using a random forest algorithm • Examined variables that contributed the most by their relationship to the risk level • Narrowed the list of input variables from 280+ to around 40 • With the more selective list of variables, likelihood of high risk is modeled using logistic regression • Tested additional variables for significance based on regulator input • A model using the Liquidity Ratio as the target variable was developed but the predictive accuracy was not satisfactory Internal Use Only Exception Model Inputs • Liquidity Ratio (%) • Core Deposits / Total Deposits (%) • Cost of Savings Deps (Incl MMDAs) (%) • Liquid Assets / Total Assets (%) • Net Loans and Leases / Total Deposits (%) • Number of quarters in which the asset grew more than 10% in the last four quarters • Pre ‐ Provision Run Rate • Commercial and Industrial Loans / Risk ‐ Based Capital (%) • Construction and Dev Loans / Risk ‐ Based Capital (%) • Net Loans and Leases/ Assets (%) • Total CRE Loans / Risk ‐ Based Capital (%) • Total Past Due Loans / Loans (%) • Return on Average Assets (%) • Terms Conventional Mortgages: All Loans ‐ Composite Effective Rate; (%; NSA) • Total Securities / Assets (%) • Treasuries & Agencies / Total Securities (%) • Net Loans & Leases / Total Deposits (%) • Other Securities / Total Investments (%) Internal Use Only Adjusted Texas Ratio Model Inputs • Construction and Dev Loans/ Risk ‐ Based Capital (%) • Loan Loss Reserves/ Gross Loans (%) • Net Loans and Leases/ Assets (%) • NonCurrent Loans/ Loan Loss Reserves (%) • NonOwner Occupied CRE Loans/ Risk ‐ Based Capital (%) • Total PD + Nonaccrual Loans/ Loans (%) • Tier 1 Capital Leverage Ratio (%) • Efficiency Ratio (FTE) (%) • Return on Average Assets (%) • Bankruptcies: Personal ‐ Total ‐ 12 months ending; (#; NSA) • Consumer Credit: Non ‐ revolving; (Mil. USD; SA) • Consumer Credit: Revolving; (Mil. USD; SA) • Home Mortgages: All Loans ‐ Percent of Loans Past Due 90 Days; (%; SA) • Terms Conventional Mortgages: All Loans ‐ Composite Effective Rate; (%; NSA) • Total Securities/ Assets (%) • Treasuries & Agencies / Total Securities (%) • Net NonCore Funding Dependence (%) • Pre ‐ Provision Run Rate • Long ‐ term Assets/ Assets (%) • Tier 1 Capital ($000) • State ‐ level unemployment rate (%) • Changes in state ‐ level unemployment rate over the past two quarters • Change in Financial Select Sector SPDR Fund Index over past one quarter Internal Use Only Business Rules A bank is considered high risk if it meets any of the following criteria: Using Exception Risk Score: • Risk Score is 0.3 or greater this quarter Using Adjusted Texas Ratio Risk Score: • Risk Score is 0.2 or greater this quarter AND it increased at least 3x since last quarter • Risk Score is 0.6 or greater this quarter • Risk Score is 0.1 or greater this quarter AND it was considered high risk last quarter Internal Use Only CSBS PREDICTIVE DASHBOARD DEMO Internal Use Only Questions? Internal Use Only The State of the Union: What’s the Economic Story Using Data Analytics? (Or, How to Spot a Recession?) By Thomas F. Siems, Ph.D. CSBS Chief Economist CSBS DataPalooza October 20, 2022 Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts Industrial Production, Sept 2022 = 105.18 Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance Industrial Production up 0.4% from 8/22 up 5.3 % from 9/21 Industrial Production 110 105 85 Industrial Production Index (2012 = 100) 90 95 100 Sources: The Conference Board; Bureau of Economic Analysis 80 Jan ‐ 20 Feb ‐ 20 Mar ‐ 20 Apr ‐ 20 May ‐ 20 Jun ‐ 20 Nov ‐ 20 Dec ‐ 20 Jan ‐ 21 Feb ‐ 21 Jul ‐ 20 Aug ‐ 20 Sep ‐ 20 Oct ‐ 20 Mar ‐ 21 Apr ‐ 21 May ‐ 21 Jun ‐ 21 Nov ‐ 21 Dec ‐ 21 Jan ‐ 22 Feb ‐ 22 Jul ‐ 21 Aug ‐ 21 Sep ‐ 21 Oct ‐ 21 Mar ‐ 22 Apr ‐ 22 May ‐ 22 Jun ‐ 22 Jul ‐ 22 Aug ‐ 22 Sep ‐ 22 Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance meaning/purpose Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance meaning/purpose Industrial Production 100 20 Industrial Production Index (2012 = 100) 40 60 80 Sources: The Conference Board; Bureau of Economic Analysis 0 May ‐ 20 Jul ‐ 16 Oct ‐ 10 Sep ‐ 12 Nov ‐ 08 Feb ‐ 03 Jan ‐ 05 Dec ‐ 06 Mar ‐ 01 May ‐ 97 Jul ‐ 93 Oct ‐ 87 Sep ‐ 89 Nov ‐ 85 Feb ‐ 80 Jan ‐ 82 Dec ‐ 83 Mar ‐ 78 May ‐ 74 Jul ‐ 70 Oct ‐ 64 Sep ‐ 66 Nov ‐ 62 Jan ‐ 59 Dec ‐ 60 Jun ‐ 18 Aug ‐ 14 Apr ‐ 99 Jun ‐ 95 Aug ‐ 91 Apr ‐ 76 Jun ‐ 72 Aug ‐ 68 Apr ‐ 22 Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance meaning/purpose productivity/growth Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance meaning/purpose productivity/growth Policy options to stimulate U.S. manufacturing Encourage technological innovation Improve supply chains Etc. Internal Use Only DATA INFORMATION KNOWLEDGE DECISIONS metrics/facts context/relevance meaning/purpose productivity/growth Internal Use Only What Does This Barcode Say? Internal Use Only Internal Use Only The U.S. Business Cycle Black = Months in Contraction (Recessions) 1855 1865 1875 1885 1895 1905 1915 1925 1935 1945 1955 1965 1975 1985 1995 2005 2015 Internal Use Only How is a Recession Defined? Internal Use Only How is a Recession Defined? • Two consecutive quarters of negative real GDP growth (two contracting quarters)? (Simplistic Rule of Thumb) Internal Use Only Internal Use Only How is a Recession Defined? • Two consecutive quarters of negative real GDP growth (two contracting quarters)? (Simplistic Rule of Thumb) • A significant decline in economic activity that is spread across the economy and that lasts more than a few months? (NBER Definition)
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