SenseMaker Lunch and Learn Final

8/17/2019 SenseMaker Lunch and Learn Final

1/31

SenseMaker:Evaluating ComplexAdaptive Systems

A Practitioner’s Guide to Using ACEs to Build Hopeand Resilience

Keil EggersMay 9. 2!"


2/31

On “Big Words”

• #ill $e using ne% &oca$ulary t'roug'outt'e presentation

•() so*et'ing is con)using+ please stop andas,

•

-earning t'is )or t'e rst ti*e toget'er/

2 0 May 2!"


3/31

Organizing a arty

•

1'is -unc' and-earn is acele$ration

• Blind)olded ands%inging

•

-et’s $rea, t'is$ad $oy open.

0 May 2!"


4/31

We All !no" t#e Story$

•

#'y are %e doingt'is3

• #'y can’t %e 4ustget $ac, to t'e%or,3

•

Reporting ti*e &s. 1i*e spent onprogra**ing.

5 0 May 2!"


5/31

W#at is Evaluation%

• #'y do %e do it3

• #'at outputs are %e e6pecting )ro* an

e&aluation3

• (n %'at conte6ts does CPPR 'elp %it'

e&aluation and %'at do partners e6pect3

7 0 May 2!"


6/31

W#ere We Are

• 8ri&e to anticipate t'e )uture.

• ail:sa)e progra*s to ac'ie&e set

outco*es

• Robustness: prediction and pre&ention o)

negati&e outco*es

• Hypot'esis:$ased

" 0 May 2!"


7/31

W#at are t#ose%&%

'emonade (or 'i(e)#eory o( C#ange

*esour+es,-nputs.

Progra*Co*ponents;Acti&ities<

=utputs (nter*ediate=utco*es

-ong:1er*=utco*es

eople:• )rained

'emonade (or'i(e )rainers,)t) model.

• Experien+edM-EC/0pro(essionals

!no"ledge:• Adverse

C#ild#oodExperien+esresear+#

• /ope 2resilien+eresear+#

-e*onade )or -i)e>• Prere?uisite

online ACEs*odule

• ! day training• Participant

resource*aterials;Hand$oo, @'andouts<

• Coac'ing

• u*$er o)pro)essionals

trained in-e*onade )or-i)e

• u*$er o))a*ilies engagedin *eaning)ulACEs discussion

• Pro)essionals'a&e

'ope*indset• (ncreased )a*ily

engage*ent inser&ices

• (*pro&edprogra**aticoutco*es

• Dtrong @ resilient)a*ilies

• e%er c'ildreni*pacted $yACEs

• Hope)ulco**unities

0 May 2!"

-ogic Models


8/31

Order vs3 Complexity

• Con)or*ity carries ris,• =rder is not usa$ility or adapta$ility.

• Co*ple6ity &alues action

• FGood enoug' action• -earning and DenseMa,ing can $e accurate

enoug' to *o&e on

• (rony o) Bureaucratic control


9/31

)#e 0-S-O4

Anticipatory a%arenessUnderstand t'e e&olutionary potential o)t'e present

Da)e:to:ail e6peri*ents•

a*pli)y success• da*pen )ailure

Resiliency to reco&er )ro* surprises9 0 May 2!"


10/31

SenseMaking

• Understanding actions and t'eirconse?uences t'at e*erge )ro* eorts tocreate order

•

Ma,ing sense )ro* ,no%ledge o) t'e past• Generate )uture action

• Continuous and e&ol&ing+ not rigid li,eannual planning to *eet targets

! 0 May2!"


11/31

Cyne5n ,!un6ev7in.

1'e place o) your *ultiple $elongings+religious+ tri$al+ spiritual+ geograp'ical+'istorical+ etc t'at pro)oundly inIuence%'at you are ;indi&idually and collecti&ely


12/31

W#at is SenseMaker%

• Do)t%are de&eloped $y 8a&e Dno%denand Cogniti&e Edge

• Based on co*ple6ity t'eory+ ecology+ and

distri$uted et'nograp'y

• Creates 'u*an sensor net%or, t'roug'capturing sel):identied narrati&e)rag*ents


13/31

8eatures

•8istri$uted cognition

• ine:grained *aterial

• 8isinter*ediation: original *aterial accesseddirectly+ not *ediated $y analysts to decision *a,ers

• E&idence:$ased 'ard and so)t data )or actiona$leresults

• (denties J%ea, signals’ o) 'idden opportunities

• De*i:constrained signication to not li*it to

'ypot'esis• Mi6 o) so)t and 'ard data to *a,e sense o) co*ple6

realities+ to distill patterns and to respond in a ti*ely*anner

! 0 May2!"


14/31

)#e SenseMaker9Survey7


15/31

/o" to se SenseMaker

• =ngoing Capture

• AppleAndroid *o$ile Application or paper

sur&eys entered on $ac,end

• 5:7 *inutes

• 8o%nloaded to central ser&er )or instantanalysis

!7 0 May2!"


16/31

Analysis

• Clusters: %'at is i*portant to loo, at$ased on patterns

• ector analysis•

Mo&e*ent o) stories o&er ti*e


17/31

8itness Mapping

! 0 May2!"


18/31

sing t#e 8itness Map

• 1'ree lters on t'e triangle de*onstratestrengt' or %ea,ness o) t'e la$els

• or* t'e a6es on t'e tness *ap.

• isualiLation and statistical instru*ents allo%patterns to $e detected in t'e *etadata+ andonce a pattern is detected+ t'e a$ility to go to

t'e supporting narrati&e i**ediately and%it'out interpretation+ ena$les *ore eecti&edecision *a,ing %it' respect to t'at pattern;e.g.+ encourage or da*pen<

! 0 May2!"


19/31

/uman Sensor 4et"ork

• Micro:narrati&es• Mass capture ;! N to e.g. stories<

s'o% di&ersity o) perspecti&es

•

Create an accurate Jdescription o) reality’)or progra* decision:*a,ing


20/31

8eatures o( SenseMaker

• Del):signication• Generates ?uantitati&e ;&isual< data

• Patterns @ trends against topics o)

interest• Analysis+ interpretation and use )or

actioninter&entions

•

Mi6 o) so)t and 'ard data to *a,e senseo) co*ple6 realities+ to distill patterns andto respond in a ti*ely *anner

2 0 May2!"


21/31

Outputs

• ine:grained data• Dee clusters o) stories+ and read

indi&idual narrati&e data points

•

=riginal *aterial directly accessed $ydecision *a,ers

•

E6plorer so)t%are )or easy analytics• 1a$leau output: &isual representation o)

?uantitati&e data


22/31

Sel(6Signi5+ation

• 1'e process o) tagging narrati&e

• =ld Approac'> Hierarc'ical ta6ono*y+

*ar,ing ,ey %ords and assigning t'e*aterial to a category

•

Hea&y %or, )or analysis

• But se*antically+ &ery diOcult due tocogniti&e science and t'e nature o)lan ua e

22 0 May2!"


23/31

W#y Mi+ro64arratives%

• ot a constructed story to pro&e a point• -arge a*ounts o) )rag*ented narrati&es

• Unstructured+ anecdotal %ay o) seeing

%orld• 1ell specic anecdotes+ sel):signi)y %'at it

*eans.

•

ou can’t as, generally F8oes t'is %or,3$ecause so*eti*es it does+ so*eti*es itdoesn’t’.

• Continuous )ree capture o) narrati&e %it'

instant )eed$ac,.2 0 May2!"


24/31

Surveys +an ;e limiting

• (*portance o) %ide:net story capture• Multiple identities o) t'e person

• Ga*ing t'e syste*

• 1'e $est %e can do is learn+ act+ andi*pro&e. 1'roug' continuous real:ti*e

input.

25 0 May2!"

S M k d C*7


25/31

SenseMaker and C*7s0alues

• 1'e Center )or Pu$lic Partners'ips andResearc' ;CPPR< assists partners %it'addressing co*ple6 social issues t'roug'targeted researc' and e&aluation as %ell

as co*pre'ensi&e pro4ect *anage*entand syste*s de&elop*ent.

• Mission> 1o opti*iLe t'e %ell:$eing o) at:ris, c'ildren+ yout'+ and )a*ilies $ygenerating responsi&e solutions t'ati*pro&e practice+ in)or* policy+ and

ad&ance ,no%ledge.27 0 May2!"

)# t #i it#


26/31

)#e artners#ip "it#Cyne5n Centre

• 1'e Cynen Centre )or AppliedCo*ple6ity at t'e Uni&ersity o) Bangor in#'ales

•

8a&e Dno%den+ )ounder o) Cogniti&e Edge• -eader in co*ple6ity science and Kno%ledge

Manage*ent eld

•

(nternational Researc' Consortiu*• Progra**atic researc' t'at %e can

participate in

• Additional partners'ips possi$le: pri&ate

sector+ go&ern*ents+ international grant


27/31

/o" do "e go (rom"#ere "e are to

"#ere "e "ant to;e%

2 0 May2!"

W#at to do "it# t#e


28/31

W#at to do "it# t#edata%

• D'are $ac, %it' t'ose telling stories

• Responsi&e 1A

• le6i$ility and Creati&ity


29/31

)#inking Big

• Could c'ange landscape o) social ser&icereporting

•

-)- as a rst e6peri*ent leading to %iderapplications

• 8e&elop e6pertise in inno&ati&e narrati&ee&aluation


30/31

W#at story are "e tryingto tell and "#o is telling

it%


31/31

SenseMaker Lunch and Learn Final

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