COMMERCIALIZATION OPTIONS FOR A SET OF COMMERCIALIZATION OPTIONS FOR A SET OF

WIRELESS PATENTSWIRELESS PATENTS

Project Advisor : Prof. Mary Mathew

Industry Supervisor: Mr. Mihir Mahajan

Shanmukha Sreenivas P , M.MGT II Year

Department of Management Studies, IISc

ContentsContentsProblem StatementObjectivesLiterature ReviewMethodologyResultsConclusionsBibliography

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3

Problem StatementProblem Statement To compare a given set of patents to class similar

benchmark patents of the world and suggest commercialization options for a selected set of patents.

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ObjectivesObjectives1) To compare the given set of wireless patents with the

identified sample of wireless world patents.

2) To identify a benchmark sample of wireless patents in the world, given the patent classes of the given set of wireless patents.

3) To evolve an elimination model to select a sample of patents with higher commercial potential.

4) Suggest commercialization options for the selected set of patents.

Literature ReviewLiterature Review

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Variable Insights Author

No of US classes Breadth, Extent of core technology diffusion Shapiro (2003)No of IPC classes Breadth, Extent of core technology diffusion Shapiro (2003)

No of InventorsDegree of inventor collaboration, Opposition Survivability

Reitzig (2003), Gibbs (2008)

No of family members Patent value and Market size Gambardella et al. (2008)Patent Grant Lag Degree of Technology Complexity, Patent Value Popp (2003), Retzig (2003)Age Probability of Patent trade, Patent Value Serrano (2008)

Backward citations count Quantitative indicator of prior art, Market sizeReitzig (2003), Lemley (2013)

Forward citations count Patent Value, Probability of patent trade Serrano (2008)No of claims Patent Value Ughetto (2011)No of words in first claim Scope of Claim, Patent Quality Osenga (2012)No of elements in first claim Scope of Claim, Patent Quality Osenga (2012)

MethodologyMethodology

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Demographic analysis

Patent Bucketing exercise(3 methods)

Three search techniques for potential licensees

Set of 175 Wireless communication patents

World benchmark patents obtained for each bucket.

(n5 = 135)

Selected set of patents(n4 = 135)

Demographic comparison of benchmark and given set of

patents

Discriminant analysis to identify patents similar to benchmark

Commercialization strategy

Shortlist of frequently appearing companies

Cont…

Sampling of world patents from above

companies(n2 = 252);(n3 = 252)

25 Buckets

Patents of high potential

List of potential licensees for each Bucket

8

Given set of patents Sample of world patents

from above

(n2 = 252);(n3= 252) (n1 = 175)

Cont…

Comparison of 2 random samples & given set of patents

Data SetsData SetsGiven Set of Patents (n1= 175)

Two samples of patents from short listed companies of random world sample (n2= 252, n3= 252)

Patents from the given set considered after bucketing (n4= 135)

World benchmark patents obtained for each bucket (n5= 135)

Ocean Tomo auctioned patents (n6= 10)Extracted from – Innography(2013) ; Relecura(2013) )

USP class wise analysis of given data setStatus of the applications (awarded v/s filed)Patents by inventor type ( academic v/s non-academic)Patent class by key inventorsAnalysis of familiesDescriptive statistics on :Patent lag and Age Number of Citations – forward and backwardNumber of Foreign FilingsNumber of InventorsNumber of words and elements in the first claim

1.1 Patent Demographic Analysis1.1 Patent Demographic Analysis

1.2 Patent Bucketing Exercise1.2 Patent Bucketing Exercise Identified 5 broad categories.

The above 5 categories further into 25 buckets.

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1.3 Search techniques employed on 1.3 Search techniques employed on bucketsbuckets

Search Techniques:IPC classification based search

Forward and Backward citations based search (Two - level)

Keyword based search

Outcome:List of potential licensees for each bucketShortlist of frequently appearing companies (14)

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2.1 Model to shortlist patents with 2.1 Model to shortlist patents with commercial potential - LDAcommercial potential - LDA

Classification methodD= v1X1+v2X2+v3X3+v4X4+…+c

D= Discriminate function

v=Discriminant coefficient or weight for that variableX=Variable consideredc=Constant

Patents of the given set (n4) having a greater extent of similarity with the benchmark patents (n5) are considered for further analysis.

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2.2 Positioning of shortlisted patents 2.2 Positioning of shortlisted patents on Innovation chain & Wireless chainon Innovation chain & Wireless chain

Concept / Device basedBasic R&D / Applied R&D / NPDAcademic / Industry based inventors

Device value chainNetwork value chain Infrastructure value chainApplication value chainContent value chain

14

} Wireless Value Chain

RESULTSRESULTS

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Demographic Analysis of Given Set (Demographic Analysis of Given Set (nn1 1 =175)=175)

16

Demographic Analysis…1Demographic Analysis…1

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No. of patents/patent applications filed in each USP class

Patent filings w.r.t Filing Year and Publication Year

Based on data extracted from Innography

Demographic Analysis…2Demographic Analysis…2Jurisdictional Spread and Family analysis

18

Publication_Country No of

Applications CA 1

CN 35

DE 7

EP 6

JP 33

KR 23

US 175

WO 89

Total 369

No. of Filings No. of applications

1 68

2 61

3 19

4 16

5 10

8 1

Total 175

Based on data extracted from InnographyFew country filings are not included in Innography

Patent buckets identified :Patent buckets identified :

19

Telecommunications Software 34Digital Image Processing 5Quality of Service 7Security 13Data Management 5Other 4

Communication 60Massive MIMO 16Modulation 2Space Time Coding 7Energy Optimization & Error detection

9

Cognitive Radios 8Multi hop Communication 4Other 14

Networking 64Location Discovery 7Node authentication 7Internetwork Load balancing 3Quality of Experience determination

4

Device handoff 3Scheduling in adhoc networks 5Optical Networks 5Packet Management 9Sensor Management 4Resource – Network Management 8Other 9

OTHER 10Hardware-Medical Devices 7

Category-Buckets No. of patents

Category-Buckets No. of patents

Category-Buckets No. of patents

Category-Buckets No. of patents

Search techniques applied on buckets identified…1Search techniques applied on buckets identified…1

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Ex: Mass ive MIMO IPC Classification based search

Forward & Backward citations based search Keyword based search

Airgo Networks Inc. Alcatel-lucent Alcatel-lucentAtheros Communications, Inc. Deere & Company Broadcom Corporation

Broadcom Corporation Ems Technologies, Inc.Electronics And Telecommunications Research Institute

Electronics And Telecommunications Research Institute Fujitsu Limited Fujitsu LimitedFujitsu Limited General Telecommunications Institute Huawei Technologies Co., Ltd.Hitachi, Ltd. Google Inc. Intel CorporationIntel Corporation Htc Corporation Interdigital, Inc.Interdigital, Inc. Ikanos Communications, Inc. Koninklijke Philips Electronics NvLg Corp. Intel Corporation Lg Corp.Marvell Technology Group Ltd. Kathrein-werke Kg Mimos, BerhadNippon Telegraph & Telephone Corp. Microsoft Corporation Nec CorporationPanasonic Corporation Motorola Solutions Inc Nippon Telegraph & Telephone Corp.Qualcomm, Inc. Nokia Corporation Nokia CorporationSony Corporation Qualcomm, Inc. Panasonic CorporationSharp Corporation Rockwell Collins, Inc. Qualcomm, Inc.Samsung Electronics Co., Ltd. Samsung Electronics Co., Ltd. Samsung Electronics Co., Ltd.Telefonaktiebolaget Lm Ericsson Toshiba Corporation Sony CorporationToshiba Corporation Unwired Planet Inc Telefonaktiebolaget Lm EricssonWionics Res Xr Communications, Llc Zte Corporation

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Potent ia l l i censees - Mass ive MIMO Airgo Networks Inc.Atheros Communications, Inc.Deere & CompanyEms Technologies, Inc.Ikanos Communications, Inc.Kathrein-werke KgMarvell Technology Group Ltd.Mimos, BerhadRockwell Collins, Inc.Unwired Planet IncWionics ResXr Communications, Llc

AppleBroadcomCisco SystemsFujitsu LimitedHuaweiKoninklijke Philips ElectronicsLG ElectronicsMotorola Mobility (acquired by Google)NEC corporationNokia corporationQualcommResearch in Motion (Blackberry)Samsung ElectronicsZTE corporation

Potent ia l l i censees for the port fo l io

Search techniques applied on buckets identified…2Search techniques applied on buckets identified…2

Patent Demographic comparisons - Patent Demographic comparisons - nn1 1 (Given Set) v/s n(Given Set) v/s n22 & n & n3 3 (World Samples)(World Samples)

22

Patent Demographics Patent Demographics nn1 1 v/s v/s nn22 & & nn33

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  Mean of Given Set(1)

Mean of World Set-I(2)

Mean of World Set-II(3) F statistic

t12

statistict13

statistict23

statistic

No of IPC classes 1.57 3.29 2.98 21.934** -6.54** -6.25** 1.14

No of Inventors 1.67 2.88 2.79 32.75** -7.95** -7.68** 0.558

No of family members 1.96 5.52988 4.438247 53.29** 10.343** -8.872** 1.553

Patent Grant Lag 1128.46 1507.12 1582.15 10.58** 3.872** -5.122** -0.95

Backward Citations Count

6.31 29.27 20.75 29.889** -7.81** -6.085** 2.744*

Forward Citations Count

0.57 2.69 3.02 17.551** -5.377** -6.266** -0.71

No of words in first claim 209.5 158.5 171.89 7.27** 3.6223* 2.49* -1.566

No of claims 22.01 22.12 21.33 0.269 -0.09 0.59 0.615

No of elements in first claim

4.3571 4.4936 4.6107 0.23 0.387 0.626 0.402

No of US classes 2.53 2.92 3.04 2.167 -1.62 -1.962 -0.493

Significance level: * for 0.05, ** for 0.01

Discrimination of given set ( nn44) and world benchmark (nn55) to identify commercially potential patents in the given set

Data input to the LDA modelData input to the LDA model

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Category-Buckets No. of patents from given set

No. of world benchmark

patents considered

Telecommunications Software 30 30Digital Image Processing 5 5Quality of Service 7 7Security 13 13Data Management 5 5

Similarly, we extracted data for all the remaining buckets

Variables chosen for analysis - LDAVariables chosen for analysis - LDA

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Forward Citations Count

V01

Backward Citations Count

V02

No of US classes V03No of IPC classes V04No of Inventors V05No of family members V06Patent Grant Lag V07No of claims V08Strength V09Age V10No of words in first claim

V11

No of elements in first claim

V12

{0, if patent belongs to benchmark set1, if patent belongs to given set

The class variable =

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Comparison of means between the two groupsComparison of means between the two groups

  Mean of Given Set(1)

Mean of Benchmark Set(2)

t12 statistic

Forward Citations Count 0.6 5.8 -10.79**

Backward Citations Count 5.95 19.26 4.59**

No of IPC classes 1.52 1.94 -2.98*No of Inventors 1.64 3.23 -8.12**

No of family members 1.61 2.93 6.086**

Patent Grant Lag 708.86 848.32 -2.602*No of claims 22.33 32.83 6.733**

Strength 31.07 75.07 -19.31**Age 1307.28 1736.07 7.822**

No of words in first claim 142.25 139.58 0.247

No of elements in first claim 4.14 4.17 0.119

No of US classes 2.3 2.73 -1.33

Significance level: * for 0.05, ** for 0.01

28Box Plot of the Strength variable for the two sets

Box Plot of the strength variableBox Plot of the strength variable

Low Strength benchmark patents

High Strength -Given set patents

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Linear Discriminant AnalysisLinear Discriminant Analysis

1. Classification Results without strength variable2. Classification Results with outliers removed without strength variable

Membership misfit of benchmark patents = 28.1 % Membership misfit of benchmark patents = 25.5 %

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LDA functionLDA function

Is_given_set

Predicted Group

Membership

Total0 1Cross-validatedResults

Count 0 111 24 1351 10 125 135

% 0 82.4 17.6 100.01 7.4 92.6 100.0

87.5% (236/270) of cross validated grouped cases are correctly classified

Membership misfit of benchmark patents = 17.6 %

3. Classification Results with strength variable

Goodness of fit of the modelGoodness of fit of the model

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Function Eigenvalue% of

VarianceCumulative

%Canonical

Correlation1 1.606 100.0 100.0 .785

Test of Function(s)

Wilks' Lambda Chi-square df Sig.

1 .384 253.302 9 .000

62 % of the variability is explained

Model is significant

Fairly good discrimination is achieved between the two groups

Shortlisted PatentsShortlisted Patents

32The last three patents are the additional ones that are obtained using model 3

S.No Publication No

Forward Citations

Count

Backward Citations

Count

No of US

classes

No of IPC

classesNo of

Inventors

No of family

members

Patent Grant Lag

No of claims

Patent Granted Strength Age Bucket

P1 US8266256 6 19 7 1 1 4 1148 10 1 85 1403Sensor mngmnt

P2 US20100217345 4 0 2 2 2 2 547 20 0 55 1547 Health

P3 US20100226491 3 5 3 3 2 1 549 20 0 55 1535 Health

P4 US20100271994 3 5 1 1 1 0 552 20 0 55 1489 node auth

P5 US20120014424 2 3 1 1 2 0 553 33 0 65 1042 MIMO

P6 US20110003612 1 13 1 1 2 0 553 33 0 55 1420 node auth

P7 US20120068845 1 0 1 1 1 1 566 29 0 65 992 QoSP8 US8126486 0 26 10 8 2 1 1278 18 1 55 1727 MIMO

P9 US8327367 0 39 9 5 3 3 1370 12 1 55 1539Sensor mngmnt

P10 US8193941 0 26 5 2 2 2 1126 28 1 65 1477 Health

Comparative Analysis with sold Comparative Analysis with sold patentspatentsShortlisted patents of given set – 10Ocean Tomo Auctioned Patents – 10Sample of benchmark patents – 10Sample of patents from given set – 10

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Comparative AnalysisComparative Analysis

(days)

35Source : “Value network dynamics in 3G–4G wireless communications: A systems thinking approach to strategic value assessment” Pagani, 2008

Suggested positioning in –Suggested positioning in – Wireless Value Chain Wireless Value Chainfor the shortlisted patents for the shortlisted patents of given setof given set

P1P1 P2P2

P3P3

P4P4

P5P5

P6P6 P7P7

P8P8

P9P9

P10P10

P8P8

P9P9P7P7

Suggested positioning in –Suggested positioning in –Innovation Value Chain Innovation Value Chain for the shortlisted patents of given setfor the shortlisted patents of given set

36Source : Innovation Value Chain , Hansen (2007)

P2P2P3P3P4P4 P5P5 P6P6 P7P7

P8P8 P9P9

P10P10

P1P1

Rationale for commercialization Rationale for commercialization optionsoptionsCommercialization options available are : New product development investments:

Valid if the patent is a concept suitable to enter the device development stage.

License the patent/s : Valid if a potential licensee keen to work further on the patent and based on a mutually agreed royalty model.

Sell out of the patent/s: Selling a patent may not be substantial unless the product has been on the market for a long time. The patent buyer usually won't want to spend a lot for an unproven product that might not generate a big profits.

Initiate a startup: Valid if the patent is at that stage where it can be manifested into a service or product for a customer and revenues are in sight within 6 months. It should also have a willing entrepreneur keen to take it out.

Cross Licensing:  Usually, this type of agreement happens between two parties in order to avoid litigation or to settle an infringement dispute. Very often, the patents that each party owns covers different essential aspects of a given commercial product.

37Source: Shapiro, Carl, “Navigating the Patent Thicket: Cross Licenses, Patent Pools, and Standard Setting )”,2010

Suggested commercialization options for Suggested commercialization options for the shortlisted Patents/Patent Applicationsthe shortlisted Patents/Patent Applications

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Publication NoPatent

GrantedDevice based

Concept based

Academic Inventor

Industrial Inventor

Suggested positioning in - Wireless Value

Chain

Suggested positioning in -

Innovation Value Chain

Suggested – Bucket

Suggested - Commercialization

Route

US8266256 • • • Infrastructure Applied R&DSensor mgmt Technology Licensing

US20100217345 • • InfrastructureDevelopment &

Design Health NPD

US20100226491 • • DeviceDevelopment &

Design Health NPD

US20100271994 • • Infrastructure Applied R&D Node Auth Technology Licensing

US20120014424 • • Infrastructure Applied R&D MIMO Technology Licensing

US20110003612 • • Infrastructure Applied R&D Node Auth Technology Licensing

US20120068845 • •Network &

InfrastructureDevelopment &

Design QoS NPD

US8126486 • • • Infrastructure Applied R&D MIMO Technology Licensing

US8327367 • • •Network &

Infrastructure Applied R&DSensor mgmt Technology Licensing

US8193941 • • • InfrastructureDevelopment &

Design Health NPD

Snoring Treatment

ConclusionsConclusionsObjectives1) To compare the given set of wireless

patents with the identified sample of world wireless patents.

2) To identify a benchmark sample of wireless patents in the world, given the patent classes of the given set of wireless patents.

3) To evolve an elimination model to select a sample of patents with higher commercial potential.

4) Suggest commercialization options for the selected set of patents.

Results1) Analyzed the gap between the given set of

wireless patents with the identified sample of world wireless patents based on Patent Latent Variables.

2) Identified benchmark patents of 14 companies shortlisted on applying search techniques on the buckets identified.

3) Used Linear Discriminant Analysis to identify the patents with higher commercial potential.

4) Positioned the shortlisted patents on the Wireless Value Chain and on the Innovation Value Chain and suggested commercialization options.

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