discover the real power of ktm
TRANSCRIPT
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Discover the Real Power of KTM
David Wright
Solution Enablement Specialist
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What is KTM?
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What is KTM?
Kofax
Answer to
Document Drudgery
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The Golden Rule of KTM
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Userproductivity?
Automation?
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Benefits of User Productivity
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Wholesaler
opens its
17th store
Pan European Wholesaler Improvement
invoices/person
/day
Productivity
Improvement
Manual processing without Kofax 800
After 3 months of Accuracy effortby PS
1200 +50%
After 2 weeks of User Productivityeffort by PS
2500 > 3 x
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The Fallacy of OCR Accuracy
What OCR accuracy do you have?
What is the straight-through processing rate?
How much can we automate?
85% straight-through processing 23 fields 99.29% field accuracy
6 chars/field 99.89% character accuracy
What is the cost of the other 15%?
You will lose this deal against an OCR Provider because
this deal is being fought over features and tech, and not
business value
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Productivity vs Automation
ProductivityDocuments/person/day
User focused
Business value
Optimizing core-business processes
Usability/comfort
8hrs/daySaving $
Limit =
AutomationAccuracy
Numbers
technology focusedImpossible to convert
to ROI
Technology
Diminishing returns
Limit = 100%
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Classic vs Quantum
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Newton Einstein
Schrdinger
Bohr
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God doesnt play dice. Spooky Action at a Distance
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Programmable vs Learning Software
Deterministic, logic, rules,
Laws, order
Probabilistic, data-driven,
Machine learning
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Analytics
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Transition from Determinism to Data-driven/Fuzzy/Quantum
Physics 1890 1920(Classical to Quantum)
Mathematics
1931(a system cannot demonstrate its ownconsistency, Kurt Gdels incompletenessaxiom)
Computer Science 1970 1990(machine learning, neural networks, speechrecognition, machine translation)
Business 2000 2020(Big data, analytics, learning systems)
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EUs Human Brain Project & USAs BRAIN Initiative in 2013
10 billion from the EU over 10 years to build ahuman brain simulator to push forward brain research
and test brain diseases.
100M$ from US government to revolutionize our
understanding of the human mind and uncover newways to treat, prevent, and cure brain disorders
You dont program it, it learns
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Dont program KTM, teach it
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Robodog will bite you
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Doing KTM by hand. Paper to Excel.
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Field Analysis
File Class Capa Nro_DOC NOTA CPFC EMIS VENC EMIT1.tif CapaLote 123987-20122.tif Duplicata 123987-2012 852147-A 60.000,0007.248.659/0001-03 15/02/2013 15/02/2013 Y3.tif Duplicata 123987-2012 1489/1 15.963,5717.155.342/0003-45 01/12/2011 21/01/2012 Y4.tif Duplicata 123987-2012 3112230U 2.195,3086.438.280/0001-30 22/12/2011 19/01/2012 Y5.tif Duplicata 123987-2012 4012391 81.045,0010.932.276/0001-61 14/12/2011 23/01/2012 Y6.tif Duplicata 123987-2012 3065357 F 1009,1180.089.964/0001-97 27/10/2011 21/09/2012 Y7.tif Nota Fiscal 123987-2012 65357 7.981,3980.089.964/0001-978.tif Nota Fiscal 123987-2012 194.580 48.741,9276.777.556/0001-509.tif Nota Fiscal 123987-2012 000.022.875 32.650,7456.990.526/0001-1010.tif Nota Fiscal 123987-2012 112230 2.195,3086.438.280/0001-3011.tif Nota Fiscal 123987-2012 194.562 7.454,9203.364.370/0001-46
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Overview of fields to extract What a customer typically givesfield format number of
charactersDocument type
Validation withLoss Payment Rates Budget Invoice multi-
invoiceReference
number numeric 6-7x
New ones
have noref-nr!
x xPossilby
more than
one perdoc
xx
Multiple
Ref-Nr perDocument
CIP database
Debtor LastName Text unlimited x x x x
only forvalidation,if existing
only forvalidation,if existing
CIP database incombination with Ref-Nr
Debtor FirstName Text unlimited x x x x
only forvalidation,if existing
only forvalidation,if existing
CIP database incombination with Ref-Nr
Debtor Street Text unlimited x x x x CIP database incombination with Ref-Nr
Debtor Housenumber numeric unlimited x x x x
CIP database incombination with Ref-Nr
DebtorAddress2 Text unlimited x x x x
CIP database incombination with Ref-Nr
DebtorPostCode numeric 4 Swiss onlySwiss only x Swiss only
only forvalidation,
if existingonly for
validation,
if existingCIP database incombination with Ref-
NrDebtor City Text unlimited x x x x only forvalidation,
if existingonly for
validation,if existing
CIP database incombination with Ref-Nr
DebtorTelephone numeric x
CIP database incombination with Ref-Nr. If there is no othernumber in database,then manual validation.
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The most successful KTM projects focus on the user.
Make your users happy and content.
KTM is their workplace all day every day.
It is the place of encounter and collaboration
between human and robot.
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Human Computer Interaction
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Validation Experience
Result Type Correct Valid User Experience
TruePositive
Perfect! Touchless processing.Automation.
False
Negative User must press ENTER.
TrueNegative User Corrects/Types data.
FalsePositive
Loss of trust. Drop of productivity.Bad data leaves Kofax.
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KTM Customer Query
This [deal] was sold on the strength of KTM being able to classify and
extract data from items received. This was then used to calculate theRETURN on INVESTMENT(ROI) which enabled them to purchase thesolution. The ROI was calculated with the reasonable estimate of 65%automated processing. I would expect that we should realistically see80% to 90% automated processing of inbound items.
That said, someone communicated to the client that the best they weregoing to see was 15% to 20% automated processing.
This obviously sent the client reeling that they werent going to seeanything close to their expected ROI and would potentially damage theirbusiness and not see the benefits from the system as expected.
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So what is a
reasonableexpectation of KTM?
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KTM should be able to significantly improve user productivity(perhaps 1.5-10x)
KTM will be able to extract perfectly information from
readable and known documents.
KTM should be able to learn how to understand readable &unknown documents.
KTMs value is in improving
documents/person/day
Transactions/second (TPS)
You will have access to near realtime performance graphs thatcan optimize user experience and data throughput.
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Reasonable Customer Expectations
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Goals of every KTM Project
1. Human Productivity2. Eliminate False Positives
no bad data leaving Kofax
3. Reduce False Negativesreduce user pressing ENTER
4. Few True Negativesimprove OCR Accuracy, Databasequality & learning