Se lf-Se rvic e Da ta Ma na g e me nt fo r Ana lytic s Use rs a c - - PowerPoint PPT Presentation
Se lf-Se rvic e Da ta Ma na g e me nt fo r Ana lytic s Use rs a c ro ss the E nte rprise Unle a shing the Po te ntia l o f Gre a t Co mpa nie s Busine ss Solutions Pro ve n, inte g ra te d so lutio ns to de live r ra pid re turn-o
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Pro ve n, inte g ra te d so lutio ns to de live r ra pid re turn-o n-inve stme nt
Busine ss Solutions
Se a so ne d da ta sc ie ntists to pro vide stra te g y a nd c o nsulting se rvic e s
SAS Analytic E xpe r tise
E nte rprise c la ss a rc hite c ture s fo r o ptima l SAS pe rfo rma nc e
Optimize d SAS Ar c hite c tur e s
High-Impac t Busine ss Outc ome s
Unle a shing the Po te ntia l
ne t pro fit inc re a se fro m I VR flo w re de sig n
inc re a se in c usto me r re te ntio n
sa ve d b y c lo sing g a ps in me mb e r c a re
sa ve d via ide ntifying hig h risk c hurne rs
inc re a se in c usto me r spe nd
re ve nue inc re a se via ne xt b e st o ffe rs
pe r da y I nte ra c tive lo ya lty tra nsa c tio ns
uplift in inc re me nta l sa le s
time sa ving s fo r use rs wo rking with ra w da ta
de g re e re a l-time vie w
Time Value of Information
Value of the Analytics
T he va lue o f da ta de c re a se s o ve r time a nd
va lue thro ug h the use o f a na lytic s
E xisting Ana lytic s Pro c e sse s
Adva nc e d Use r Sa nd- Boxe s
T suppo rt a nd g o ve rna nc e
a ste r a c c e ss to da ta
limina tio n o f duplic a te da ta
Be ne fits
Data L abs L ab Gr
T able Database
F le xibility vs. IT Proc e ss
e st Ne w T he o rie s
e st F a st
a ilure )
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3r d Par ty Data
va lid a tio n, o nly a pplie s to so me pro je c ts
T e mpor ar y & Re se ar c h Data
xplo ra to ry me tric s a nd a g g re g a te s, re q uire me nts no t fully d e fine d , sho rt live d , e a rly sta g e wo rk
Pr e - Pr
ithe r o f the a b o ve c a n tra nsfo rm into this
e xists in the Da ta L a b
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What is diffe r e nt fr
aditional sandboxing?
e na b le s g o ve rna nc e
mpro ve d fle xib ility with wo rklo a d ma na g e me nt
a nd se rvic e c a pa b ilitie s a t the b usine ss unit le ve l
F unc tion Sa ndbox Da ta L a bs
Runs Unsuppo rte d Pro duc tio n Apps Ye s No E nviro nme nt Ba c kup & Re c o ve ra b le No Ye s Spe e d o f Pro c e ssing & Prio rity No Ye s DBA Suppo rt (a g re e me nt) No Ye s Use rs c a n impa c t & impa c t o the r use rs Ye s No Spa c e is ne ve r c le a ne d up o r re c la ime d Ye s No Wo rk lo a d ma na g e me nt se t up No Ye s Use rs T ra ine d o n Optima l use No Ye s
Da ta L a b hie ra rc hy to ma na g e use r g ro ups, spa c e , a nd wo rklo a d
Data Labs
Wo rkspa c e s a llo c a te d fo r a na lysis
a b s e xpire
a b s a re a llo c a te d with a fix size , b ut a re e la stic
L ab Gr
Wo rkspa c e a llo c a te d fo r a g ro up
la b s. Gro ups c a n b e a rra ng e d b y de pa rtme nt o r pro je c t Gro ups c a n b e ma de priva te L a b Gro up is a fixe d size tha t’ s sha re d b y use rs.
Table
Da ta b a se ta b le to sto re the da ta
ta b le a nd lo a d da ta
Database
Da ta b a se whe re the la b g ro up re side s
e ra da ta use r- da ta b a se
Marketing Lab Group Campaign Lab Data Scientist Lab Group Sales Lab Group Promotion Lab Risk Analytics Lab Hierarchy Lab Sales Forecast Lab Demand Curve Lab Customer Segmentation Lab Personal Lab Teradata Database DW1
Vie wpo int
Before After Gains
Core Process /ROI Modeling
Tools Measure Tools Measure Difference Improvement Data Aggregation
Base SAS / SPDS 1200 Minutes SQL / SAS DI / In-DB 2 Minutes
59900%
Model Execution
Base SAS / SPDS
1800 Minute s
SQL / SAS / In-DB 30
Minute s
5900%
Model Fit/QC
Base SAS / SPDS
1200 Minute s
SQL / SAS / In-DB 240
Minute s
400%
Manual QC
Excel/SAS
3600 Minute s
Data Lab / SAS / Excel 10
Minute s
Total Time
130 Hours 5 Hours
2768%
FTE's
3 1
200%
Brands
5 (18 Possible)
5
Core process (70%) (Strategic 10%) Tactical (20%) Steps to be taken to reduce time in the core processes:
e.g in the ROI and Marketing mix process high level of automation and standardization has been achieved
Steps for expanding the work-stream:
stream
Core process (30%) Strategic (60%) Tactical (10%)
Efficiencies gained in core process and tactical projects could be funneled into doing more strategic projects
On a ve ra g e , US me rc ha nts re po rte d a n 8% inc re a se in the c o st pe r do lla r o f fra ud lo sse s, fro m $2.23 to $2.40. T his me a ns tha t fo r e ve ry do lla r o f lo sse s, me rc ha nts a re lo sing $2.40 b a se d o n c ha rg e b a c ks, fe e s a nd me rc ha ndise re pla c e me nt. T he a ve ra g e numb e r o f mo nthly fra ud a tte mpts ha s spike d b y 33% (2015 – 2016).
$30,076
Pe r Mo nth
($1002 pe r da y)
F aste r analytic syste ms allow use r s to build, te st and imple me nt ne w mode ls mor e quic kly, c r e ating additional value for the or ganization.
T his va lue is c o mpo und e d b y the # o f mo d e ls intro d uc e d o r upd a te d e a c h ye a r.
Ave ra g e Da ily E xtra Da ys # o f Mo de ls Additio na l Va lue Va lue Cre a te d o f Usa g e Cre a te d Cre a te d
Time to Develop Model Value Creation Additional Value Created Current Process Improved Process
Be ing able to do mor e mode l te sting and to update e xisting mode ls to ac hie ve optimal pe r for manc e c an add signific ant value ove r time
Ave ra g e Mo nthly E xtra Ga in in # o f Mo de ls Additio na l Va lue Va lue Cre a te d Pe rfo rma nc e Cre a te d Cre a te d Pe r Mo nth
Mo nth 2 Mo nth 4 Mo nth 6 Mo nth 8 Mo nth 10 Mo nth 12
$500k $400k $300k $200K $100k $0
Improve d Mode ls E xisting Mode ls
$216,000
Additional Value Cre ate d Pe r Ye ar
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Busine ss Solutions SAS Analytic E xpe r tise Optimize d SAS Ar c hite c tur e s
High-Impac t Busine ss Outc ome s
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