Clay, William et al.

Patent Trials and Appeals Board

Jan 29, 2020

14338215 - (D) (P.T.A.B. Jan. 29, 2020)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
14/338,215 07/22/2014 William Clay ACXM-01063-US-1 1021
160811 7590 01/29/2020
Wright, Lindsey & Jennings LLP - Acxiom
200 W. Capitol Ave.
Ste. 2300
Little Rock, AR 72201
EXAMINER
ANDERSON, FOLASHADE
ART UNIT PAPER NUMBER
3623
NOTIFICATION DATE DELIVERY MODE
01/29/2020 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
aelliott@wlj.com
jdougherty@wlj.com
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte WILLIAM CLAY, KRISTEN MOUGEOT,
BRENTLY BARROW, BRIDGET FARRIS,
STEVE MANATT, and CHARLES ZINSMEYER

Appeal 2019–003515
Application 14/338,215
Technology Center 3600
____________

BEFORE ERIC B. GRIMES, RICHARD M. LEBOVITZ, and
TAWEN CHANG, Administrative Patent Judges.

LEBOVITZ, Administrative Patent Judge.

DECISION ON APPEAL
The Examiner rejected the claims under 35 U.S.C. § 102 as
anticipated, under 35 U.S.C. § 103 as obvious, and under 35 U.S.C. § 101 as
reciting patent ineligible subject matter. Pursuant to 35 U.S.C. § 134(a),
Appellant appeals from the Examiner’s decision to reject the claims.1 We
have jurisdiction under 35 U.S.C. § 6(b).
We AFFIRM.

1 We use the word “Appellant” to refer to “applicant” as defined in 37
C.F.R. § 1.42. Appellant identifies the real party in interest as Acxiom
Corporation. Appeal Br. 2.
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STATEMENT OF THE CASE
The claims stand finally rejected by the Examiner as follows:
Claims 1–9, 12–17, and 20–22 under 35 U.S.C. § 103 as obvious in
view of Lewis (US 2011/0066476 A1, published Mar. 17, 2011) (“Lewis”)
and Dagnino (US 2007/0150293 A1, published Jun. 28, 2007) (“Dagnino”).
Final Act. 8.
Claims 18 and 19 under 35 U.S.C. § 102(a)(1) as anticipated by
Lewis. Final Act. 23.
Claims 1–9 and 12–22 under 35 U.S.C. § 101 because the claimed
invention is directed to a judicial exception. Final Act. 3.
Claim 1 is representative of the rejected claims and reads as follows:
1. A computer-implemented method for self-
assessment of the marketing capability of an organization,
comprising the steps of:
a. receiving at the processor a pre-defined configuration
from a normative database, wherein the normative database
comprises peer group average data and peer group leader data
for a plurality of business organizations, and wherein the
normative database is dynamically updated with additional peer
group average data and peer group leader data for a plurality of
business organizations over time;
b. generating at a processor a set of business challenges
based on the pre-defined configuration and building a computer
display of business challenges outputting the set of business
challenges;
c. receiving at the processor a selection instruction
selecting at least a subset of the set of business challenges;
d. retrieving from a body of knowledge (BOK) a plurality
of attributes for each of the business challenges in the at least a
subset of business challenges, wherein the BOK comprises a
global, multi-channel database comprising a plurality of
business challenges and business attribute definitions and
questions associated with each of the plurality of business
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challenges, and further comprising sets of industry knowledge,
channel knowledge, and geography knowledge;
e. sending from the processor each of the plurality of
attributes to a computer display of attributes, wherein the
computer display of attributes comprises a selection tool for
selecting a current attribute maturity level for each of the
attributes on the computer display of attributes;
f. receiving at the processor the current attribute maturity
level for each of the plurality of attributes;
g. receiving at the processor a targeted desired state from
the normative database; and
h. generating a report comprising an indicator of current
maturity for each of the at least a subset of the set of business
challenges and the targeted desired state, and generating a
computer display report.

§ 103 REJECTION
Claim 1
Claims 1–9, 12–17, and 20–22 stand rejected over Lewis and
Dagnino. Lewis describes “an automated system and method for managing
the delivery of management knowledge and other resources.” Lewis,
Abstract. Lewis also teaches that its invention “includes the design of
assessment instrument(s) based on affiliate/service provider objectives.
Assessments include the evaluation and scoring on seven management
practices.” Id. Lewis explains that these “practices and the Management
Maturity Model (M3) are used to help users understand their business’ or
organization’s maturity level.” Id. Similar to Lewis, claim 1 is also directed
to an assessment tool (“computer-implemented method for self-assessment”)
and also determines the maturity level of the organization (“f. receiving at
the processor the current attribute maturity level for each of the plurality of
attributes”).
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The Examiner found that Lewis describes steps a), b), and d)–h) of
claim 1. Final Act. 8–12. The Examiner found that Lewis does not describe
step c) of claim 1 (“c. receiving at the processor a selection instruction
selecting at least a subset of the set of business challenges”), but found that
Dagnino describes this limitation. Final Act. 12. The Examiner determined
it would have been obvious to one of ordinary skill in the art to use
Dagnino’s selection step in Lewis for its expected function. Final Act. 12–
13.

Does Lewis describe step a) of claim 1?
Appellant contends that Lewis does not describe step a) of claim 1 in
which the “normative database . . . is dynamically updated with additional
peer group average data and peer group leader data for a plurality of
business organizations over time.” Appeal Br. 23 (emphasis omitted).
The Examiner found step a) of claim 1 to be described in paragraphs
27 and 41 of Lewis. Final Act. 8–9. These paragraphs are reproduced
below:
FIG. 5 is an illustration of the above-noted implementation
showing the relationships between the server, where the
software is stored, and the various roles that the system
manages interaction between, according to at least one
embodiment of the present invention. As shown, the present
invention is generally implemented in a server 100 that is
accessed by an administrator 102, an affiliate 104, an advisor
108 and a user 110. As will be explained in further detail
hereinbelow, the administrator 102 accesses the server 100 to
provide all the back-end data in the tool (i.e. inputs the
assessment questions, establishes the criteria for resources,
develop codes for affiliates, set-up affiliate, advisor and user
profiles, and updates content on the web site). Affiliates 104
use the system to view and manage their affiliate members
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(users) and can also use the system to assign and manage
affiliate advisors. Affiliates may have their own resources and
databases that may[]be made available on their website 106
through the system. The advisors 108 use the system to view
assessment results and prescribe resources, reports and
proposals to users 110. The users 110 interface with the system
server 100 to take assessments, receive knowledge and other
resources, and request reports and request other consulting
assistance. As noted above, users 100 may also access affiliate
websites 106 if such access if given to the user depending on
their relationship to the affiliate and/ or their level of
subscription.
Lewis ¶ 27.

At Step (31), after each assessment is completed and the data is
calculated, the assessment results are stored in the system
database to use for several purposes: matching up criteria
definitions to the results to determine knowledge distribution,
exporting data, and presenting the changes results associated
with average and top scores.
Lewis ¶ 41.
Paragraph 27 describes a server that “provide[s] all the back-end data
in the tool.” The tool is part of the “systems and methods for assessing an
organization’s management maturity by evaluating its current management
processes against a set of standards.” Lewis ¶ 2. We understand the “back-
end data” on the server which is accessed by the tool to meet the claimed
limitation of a “database” as recited in claim 1. Lewis specifically describes
databases (“Affiliates may have their own resources and databases that
may[]be made available on their website 106 through the system.”). Id. ¶ 27
(emphasis omitted). The database can be accessed through the internet. See
Lewis ¶¶ 18, 27.
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The claim requires that the database “is dynamically updated with
additional peer group average data and peer group leader data.” We address
this limitation below, beginning with the discussion of who are the users of
Lewis’s database.
Lewis explains that “Affiliates 104 use the system to view and
manage their affiliate members (users).” Lewis ¶ 27. Lewis doesn’t provide
an express definition of “affiliate.” However, in the context of Lewis’s
disclosure, we understand “affiliate” to be a business organization using the
assessment system “for evaluating an organization’s level of maturity, and
management capability and practices to complete a desired change
successfully.” Lewis ¶ 18. The affiliate has affiliate members or users who
use the system. Lewis ¶ 27. “The users 110 interface with the system server
100 to take assessments, receive knowledge and other resources, and request
reports and request other consulting assistance.” Id. Lewis explains that the
users are assessed by collecting information from them (“The invention
embodies an on-line assessment by collecting information from users, using
the responses to the assessment to calculate a result.”). Lewis ¶¶ 18, 32–34
(describing the user taking an assessment online and the system performing
a calculation based on the assessment question responses).
Lewis further explains that after the assessment is completed, “the
data is calculated” and “the assessment results [for the affiliate users] are
stored in the system database to use for several purposes: matching up
criteria definitions to the results to determine knowledge distribution,
exporting data, and presenting the changes results associated with average
and top scores.” Lewis ¶ 41 (emphasis added). The latter, as explained
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below, correspond to the claimed “peer group average data and peer group
leader data.”
Lewis teaches that “[i]n addition to the user’s results, the user can also
be displayed an average score of all users who took the assessment and the
highest score of all users.” Lewis ¶ 35. The “average and top scores” are
the scores of users of an affiliate organization because the users register and
access an affiliate website to take the assessment. Lewis ¶ 27. The
Examiner found that the users constitute a “peer group.” Final Act. 9. The
term “peer” means “a person of the same legal status” or “a person who is
equal to another in abilities, qualifications, age, background, and social
status.”2 Thus, the Examiner reasonably found that the users of the same
affiliate organization are in the same “peer group” (Ans. 39) because each
user of the affiliate would be considered equal with respect to their
membership in the affiliate. The average and top scores therefore
correspond to the claimed “peer group average data and peer group leader
data.”
Appellant argues “there is no teaching or suggestion in Lewis of a
normative database that is dynamically updated with additional peer group
average data and peer group leader data for a plurality of business
organizations over time.” Appeal Br. 23 (emphasis omitted). Appellant
acknowledges that in paragraph 27 of Lewis “content” is updated, but argues
that the content is undefined and there is “no mention of any update of peer
group average data or peer group leader data.” Id. at 24.
As explained above, Lewis teaches peer group average and leader data
based on the users of an affiliate. Appellant recognizes that this calculation

2 https://www.dictionary.com/browse/peer (lasted accessed Jan. 1, 2020).
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is made, but argues that “[c]omparing a business’s maturity in various
categories to all other businesses, rather than comparing only to businesses
in the same peer group, is of little or no value to the business.” Appeal Br.
24.
We are not persuaded. Appellant did not explain why the calculation
of average and top scores is for users of all businesses, and not only users in
the same peer group of the affiliate organization or affiliates of the same
type of business. Indeed, in paragraph 27, which is cited by the Examiner,
Lewis teaches that “Affiliates may have their own resources and databases
that may[]be made available on their website 106 through the system.”
Lewis ¶ 27. When the affiliate uses its own database, the resulting
calculation of user average and top score would reasonably be understood to
represent the users of the affiliate. See also Lewis ¶ 24 (“Provide additional
targeted assessments to a user — assessments can be assigned to a code so
that assessment will only be available to users who have a matching code.
This allows the dedicating of individual resources to affiliates and those
users associated with that affiliate.”). Lewis also teaches that “the system
can then export the results and the data through the use of queries for
analysis across a large group of users and across a large group of affiliates.”
Lewis ¶ 18 (referenced in Ans. 39). Because Lewis is interested in
comparing peer group scores, as evidenced by Lewis’s calculation of the
average and top scores for the peers of a single affiliate organization, it
would be obvious to one ordinary skill in the art that to compare peer group
scores of related business organizations when querying data “across a large
group of users and across a large group of affiliates.” Lewis ¶ 18.
Accordingly, we are not persuaded by Appellant’s argument that Lewis
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compares “a business’s maturity in various categories to all other businesses,
rather than comparing only to businesses in the same peer group.” Appeal
Br. 24. Appellant recognized the disclosure of Lewis in paragraph 35 of
average and top scores,3 but did not consider it in the context of the
complete teachings in Lewis. Appeal Br. 24–25.
As to the disclosure in Lewis of updating of the “content” (Lewis ¶
27), the user scores are content on the affiliate’s server, and thus would
generally be understood to be part of the content which is updated.
Moreover, if the average and top scores are to have meaning, they must be
updated periodically to determine the actual average and top scores as more
users take the assessment. The scores would not be average and top scores,
if they did not represent all users who use the assessment instrument.
Appellant did not provide a definition of “dynamically updated” with the
additional data that would differentiate the updating of the database content
to determine current user average and top scores. Appeal Br. 24.

Does Dagnino describe step c) of claim 1?
Appellant argues that Dagnino does not describe step c of claim 1 of
“receiving at the processor a selection instruction selecting at least a subset
of the set of business challenges.”
Appellant contends that the “process areas” cited by the Examiner as
being equivalent to the business challenges of claim 1 are, in fact, “wholly
different.” Appeal Br. 26. To make this distinction, Appellant refers to

3 Appellant cited paragraph 34, but the cited disclosure is from paragraph 35
of Lewis.
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paragraph 21 of Dagnino. Id. Paragraph 21 of Dagnino is reproduced
below:
At present, the main disciplines that CMMI covers include: (1)
systems engineering; (2) software engineering; (3) integrated
product and process development; and (4) supplier sourcing.
These four disciplines described in the CMMI are addressed or
defined by what are referred to as “Process Areas” associated
with each discipline. A Process Area may be defined as a
cluster of related best practices in an area that, when
implemented collectively, satisfies a set of goals considered
important for making significant improvement in that Process
Area.

Dagnino ¶ 21 (emphasis added).
Appellant argues:
A process area is thus a cluster of best practices for an area that
are intended to be implemented collectively by the business.
By contrast, the business challenges of claim 1 are not a cluster
of anything; they are individual business challenges that are not
grouped together by area or by any other criteria. In the
invention of claim 1, the user is able to select the specific
business challenges of interest to that user.
Appeal Br. 26 (emphasis added).
This argument is not persuasive. Claim 1 recites in step d) that “a
plurality of attributes for each of the business challenges” is retrieved. Thus,
each business challenge comprises a plurality of attributes, which could be
alternatively characterized as a “cluster” of attributes because they are a
group of attributes associated with same business challenge. Appellant did
not distinguish the claimed business challenges,4 and claimed attributes,

4 Figure 4 of the Specification lists examples of Business Challenges:
Analytics, Consumer Connections, Data Quality, Engagement Across
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from the process areas5 and best practices described by Dagnino. Indeed,
Dagnino’s “best practices” serve the same function as the claimed
“attributes.” Specifically, Dagnino teaches that the “best practices” are set
as goals for making improvements in a Process Area. See Dagnino ¶ 21.
Similarly, the Specification teaches that the levels of each attribute are
measured as a “level of maturity” and are considered as relevant for meeting
a desired business challenge, i.e., a goal for improving the maturity level of
the business challenge. Spec. ¶¶ 43 (“The integration of attribute ranking
definitions from BOK 12 aids the user in accurately identifying the level for
each of the attributes being considered as are relevant to the most pressing
business challenges for the user’s organization.”), 45 (“After the user has
scored the level of maturity for each of the attributes 82 on associated
attributes page 80 and clicked the attribute page next button 92, the
calculations are performed in order to determine a marketing maturity
quotient (MMQ) for each of the selected business challenges.”), and 47 (“On
slider bar display page 100, the user is requested to indicate how far the user
wishes to advance the maturity of the user’s organization in the next one-
year period, or other designated period, with respect to each of the selected
business challenges.”).
Appellant argues that, in Dagnino, “once the user selects the process
area using the GUI, the system then generates goals related to that process

Channels, Risk Management, Segmentation, Single View of consumers,
Support Resources, and Technology Resources.
5 Dagnino discloses examples of process areas as Requirements
Management 302, Project Planning 304, Project Monitoring and Control
306, Supplier Agreement Management 308, Measurement and Analysis 310,
Process and Product Quality Assurance 312, Configuration Management
314. See Dagnino ¶ 24.
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area. The user has no choice, however, in which goals are generated.”
Appeal Br. 26. Claim 1, however, does not require the selection of goals.
Rather, the selection is of business challenges, which as discussed above, are
the same as the process areas described in Dagnino. Appellant
acknowledges that process areas are selected. Appeal Br. 26 (“once the user
selects the process area”). Thus, Appellant’s argument regarding the
selection of goals is unavailing because the claim does not require these to
be selected. Appeal Br. 26–27.
For the foregoing reasons, we conclude that a preponderance of the
evidence supports the Examiner’s determination that claim 1 is obvious in
view of Lewis and Dagnino.

Claim 2
Dependent claim 2 is directed to the computer-implemented method
of claim 1, “further comprising the step of calculating at the processor a
marketing maturity quotient (MMQ) for each of the business challenges.”
Appellant contends that Lewis does not teach this calculation. Appeal Br.
28. Appellant states that “claim 2 calls for the calculation of a new metric
(the MMQ)” which is not taught or suggested in either Lewis or Dagnino.
Id. at 29. Appellant also argues that the claims relate to marketing, and
neither of the cited publications teaches or suggests “any application of
capability maturity models to marketing in any manner.” Id. at 28–29.
The Examiner determined that Lewis at paragraph 34 and Figure 3
shows percentages that represent normalization, and which correspond to the
MMQ calculation described in paragraph 45 of the Specification. Final Act.
13; see also Ans. 40–41. Appellant did not identify a defect in the
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Examiner’s fact-finding or reasoning. Appellant’s only argument is that the
value in Lewis is not applied to marketing. Appeal Br. 28–29. However,
each of Lewis and Dagnino contain express statements that their methods are
not limited to the disclosed embodiments. Lewis ¶ 104; see also Dagnino
¶ 57. Lewis describes various aspects of management that are assessed
(customer relations, supplier/partner relations, business planning) (Lewis,
Fig. 3) which would reasonably suggest marketing, e.g., in customer
relations and business planning.

Claim 6
Dependent claim 6 is directed to the computer-implemented method
of claim 3, reciting the following limitation (emphasis added):
wherein each of the MMQ for each of the subset of business
challenges may comprise a not applicable value and wherein
the step of calculating the MMQ for each of the subset of
business challenges comprises the step of generating the not
applicable value for each of the business challenges for which
more than a threshold percentage of the associated plurality of
attributes have the not applicable value.
The Examiner found that Lewis does not describe “the step of
calculating the MMQ for each of the subset of business challenges
comprises the step of generating the not applicable value for each of the
business challenges” as recited in claim 6. Final Act. 14 (emphasis added).
Citing paragraph 46, however, the Examiner found that Dagnino teaches
using a “not applicable value” and determined it would have been obvious to
have included such value in Lewis’s method. Final Act. 14–15. For clarity,
paragraph 46 of Dagnino is reproduced below:
A Heuristic Appraisal Expertise KB 714 may also be accessed
by the inference engine 708. The Heuristic Appraisal Expertise
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KB 714 may contain heuristic knowledge of appraiser human
experts that may help in the formulation of the subsequent or
follow-on questions 716 that the system may asks [sic] the
respondent or respondents after the initial seed questions 712
have been presented and responded to by the respondent or
respondents or users. Based on the role and profile of the
respondents there may be sets of Process Areas and questions
that may be relevant to them. For example, if diagnostic activity
is focused on members of a development organization
answering questions, depending on the roles of the members,
certain Process Areas will not apply while others will be
relevant. In such cases, the Heuristic Appraisal Expertise KB
714 may guide the system 700 in identifying which Process
Areas may be applicable. The questions for both the CMMI
Process Areas KB 710 and the Heuristic Appraisal Expertise
KB 714 may be organized according to the Process Areas and
the questions may be triggered or generated based on the
previous responses from the user or users.
Paragraph 46 of Dagnino describes triggering questions based on
previous responses. While such trigger may relate to a “threshold” as recited
in claim 6, there is no mention in this paragraph of using a “not applicable
value” in the manner recited in the claim.
The Examiner, in response to Appellant’s argument regarding claim 6,
cited the disclosure in paragraph 46 of Dagnino that “certain Process Areas
will not apply while others will be relevant.” Ans. 42 (emphasis omitted).
Dagnino teaches in this paragraph that the system may determine which
process areas “may be applicable,” and that “the questions may be triggered
or generated based on the previous responses from the user or users,”
indicating that such questions may be involved in identifying additionally
relevant “applicable” process areas. Dagnino ¶ 46. In other words, an
answer to a question may trigger the presentation of additional questions
from the same or different process area. However, this disclosure has not
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been adequately shown by the Examiner to use a “not applicable” value in
the calculation of the MMQ. Dagnino’s disclosure is focused on identifying
applicable process areas, not using a non-applicable value to calculate the
maturity level of a business challenge as required by claim 6.

Claims 9 and 20
Appellant separately argues claims 9 and 20, but the arguments are the
same as for claim 1. Appeal Br. 32. Thus, we find the arguments
unpersuasive for the same reasons.

Summary
For the foregoing reasons, the obviousness rejection of claims 1, 2, 9,
and 20 are affirmed. Separate arguments were not made for claims 2–5, 7,
8, 12–17, 21, and 22, these claims therefore fall with claim 1.
37 C.F.R § 41.37(c)(1)(iv). The obviousness rejection of claim 6 is
reversed.

§ 102 REJECTION
Claims 18 and 19 stand rejected by the Examiner as anticipated by
Lewis. Final Act. 23. Appellant makes the same unpersuasive arguments
they did for claims 1 and 2. Appeal Br. 33. Consequently, we affirm the
anticipation rejection of claims 18 and 19 for the same reasons.

§ 101 REJECTION
Under 35 U.S.C. § 101, an invention is patent-eligible if it claims a
“new and useful process, machine, manufacture, or composition of matter.”
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However, not every discovery is eligible for patent protection. Diamond v.
Diehr, 450 U.S. 175, 185 (1981). “Excluded from such patent protection are
laws of nature, natural phenomena, and abstract ideas.” Id. The Supreme
Court articulated a two-step analysis to determine whether a claim falls
within an excluded category of invention. See Alice Corp. Pty. Ltd. v. CLS
Bank Int’l, 573 U.S. 208 (2014); see also Mayo Collaborative Servs. v.
Prometheus Labs, Inc., 566 U.S. 66, 75–77 (2012).
In the first step, it is determined “whether the claims at issue are
directed to one of those patent-ineligible concepts.” Alice, Alice, 573 U.S. at
218–219. If it is determined that the claims are directed to an ineligible
concept, then the second step of the two-part analysis is applied in which it
is asked “[w]hat else is there in the claims before us?” Id. The Court
explained that this step involves “a search for an [‘]inventive concept[’] —
i.e., an element or combination of elements that is sufficient to ensure that
the patent in practice amounts to significantly more than a patent upon the
[ineligible concept] itself.’” Id. (citing from Mayo, 566 U.S. at 75–77).
Alice, relying on the analysis in Mayo of a claim directed to a law of
nature, stated that in the second part of the analysis, “the elements of each
claim both individually and ‘as an ordered combination’” must be
considered “to determine whether the additional elements ‘transform the
nature of the claim’ into a patent-eligible application.” Id.
The PTO has published revised guidance on the application of 35
U.S.C. § 101. USPTO’s January 7, 2019 Memorandum, 2019 Revised
Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 51–57 (2019)
(hereinafter “Eligibility Guidance” and/or “Eligibility Guidance, 84 Fed.
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Reg.”). This guidance provides additional direction on how to implement
the two-part analysis of Mayo and Alice.
Step 2A, Prong One, of the 2019 Guidance, looks at the specific
limitations in the claim to determine whether the claim recites a judicial
exception to patent eligibility. In Step 2A, Prong Two, the claims are
examined to identify whether there are additional elements in the claims that
integrate the exception in a practical application, namely, is there a
“meaningful limit on the judicial exception, such that the claim is more than
a drafting effort designed to monopolize the judicial exception.” See
Eligibility Guidance, 84 Fed. Reg. 54 (2. Prong Two).
If the claim recites a judicial exception that is not integrated into a
practical application, then as in the Mayo/Alice framework, Step 2B of the
Eligibility Guidance instructs us to determine whether there is a claimed
“inventive concept” to ensure that the claims define an invention that is
significantly more than the ineligible concept, itself. See Eligibility
Guidance, 84 Fed. Reg. 56.
With these guiding principles in mind, we proceed to determine
whether the claimed subject matter in this appeal is eligible for patent
protection under 35 U.S.C. § 101.

Discussion
Claim 1 recites a “computer-implemented method for self-assessment
of the marketing capability of an organization.” Following the first step of
the Mayo analysis, we find that the claims are directed to a method, and
therefore fall into one of the broad statutory categories of patent-eligible
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subject matter under 35 U.S.C. § 101. We thus proceed to Step 2A, Prong
One, of the Eligibility Guidance.

Step 2A, Prong One
In Step 2A, Prong One, of the Eligibility Guidance, the specific
limitations in the claim are examined to determine whether the claim recites
a judicial exception to patent eligibility, namely whether the claim recites an
abstract idea, law of nature, or natural phenomenon.
The Examiner found that the claims are directed to an abstract idea,
which the Examiner also identified as “organizing human activity.” Final
Act. 3. The Eligibility Guidance lists “[c]ertain methods of organizing
human activity,” including “advertising, marketing or sales activities or
behaviors,” as one of the three groupings of abstract ideas. Eligibility
Guidance, 84 Fed. Reg. 52.
Claim 1 is directed to a “computer-implemented method for self-
assessment of the marketing capability of an organization.” The steps of the
claims comprise generating and outputting business challenges (step b),
receiving instructions for selecting a subset of business challenges (step c),
retrieving and displaying attributes of the business challenges (steps d and
e), receiving the maturity level for the attributes (step f), and receiving a
targeted desired state (step g). The method uses peer group data from the
organization to determine the targeted desired state (step a and step g), i.e.,
the level of capability the organization desires to achieve for each business
challenge. Spec. ¶¶8–9. Each of these steps are part of the self-assessment
process of measuring marketing capability, which are integral to the abstract
idea of organizing human activity.
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The self-assessment of the attributes of each business challenge is
performed by individual users of the organization. Spec. ¶¶ 7 and 16–20;
see also Appeal Br. 17. Examples of business challenges are analytics,
consumer connections, data quality, engagement across channels, and risk
management. Spec., Fig. 4. Examples of attributes are offline data
collection/assembly, analytic skillset, online data collection, and analytics
strategy. Spec., Fig. 5.
After steps a–g are accomplished, a “report” is generated “comprising
an indicator of current maturity for each of the at least a subset of the set of
business challenges and the targeted desired state” (step h). The claimed
method therefore is a self-assessment of the “marketing capability” of users
of the organization.
The Specification explains that capability maturity models (“CMM”)
for measuring an organization’s “capability” were first developed “in the
1980’s for the purpose of evaluating the capability of software contractors
working for the U.S. Department of Defense.” Spec. ¶ 4. The Specification
further teaches that “[t]he successful deployment of CMMs in these various
areas has led to significant improvement in the measured processes by
identifying the level of maturity and further by identifying those steps
required in order for an organization to advance to a greater level of
capability in the areas measured.” Id. The Specification describes the
“capability framework” of these models as “a specific type of analytical tool
that provides a common structure to measure the current performance of
capabilities, identify desired performance, determine the gaps between
current and desired performance, and perform a series of diagnostic and
analytical tests to establish priorities for capability improvement.” Id. ¶ 5.
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Thus, the claimed method of self-assessing “marketing capability of an
organization” is directed to organizing human activity involved in marketing
because it assesses the capability of the organization based on the users who
take the self-assessment test. The 2019 Eligibility Guidance lists “marketing
or sales activities” as an example of patent-ineligible methods of organizing
human activity. See Eligibility Guidance, 84 Fed. Reg. 52 (under grouping
“(b)”).
Appellant contends that the claimed method is not directed to
organizing human activity because the “conventional method of performing
any type of capability maturity model analysis is for human experts to
perform the process by hand.” Appeal Br. 17. Appellant argues that
“[a]mong the advantages of the applicant’s invention is that the intervention
of human experts to perform the analysis is eliminated.” Id. (emphasis
omitted).
This argument is not persuasive. Appellant did not explain how
executing the capability maturity model on a computer makes it any less
directed to the abstract idea of organizing human activity. The Court in
Alice made clear that a claim directed to an abstract idea does not move into
section 101 “eligibility territory” by “merely requir[ing] generic computer
implementation.” Alice, 573 U.S. at 221; see also buySAFE, Inc. v. Google,
Inc., 765 F.3d 1350, 1354 (Fed. Cir. 2014). Therefore, while we
acknowledge Appellant’s statement that “invention is directed to a
programmed machine and a programmed machine-implemented method that
eliminates human activity” (Appeal Br. 18), the implementation of the
method on a computer does not, itself, make it eligible for a patent under §
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101 and certainly does not make it any less a method of organizing human
activity.

Step 2A, Prong Two
Prong Two of Step 2A under the 2019 Eligibility Guidance asks
whether there are additional elements that integrate the exception into a
practical application. As in the Mayo/Alice framework, we must look at the
claim elements individually and “as an ordered combination” to determine
whether the additional elements integrate the recited abstract idea into a
practical application. As discussed in the Eligibility Guidance, “[a] claim
that integrates a judicial exception in a practical application will apply, rely
on, or use the judicial exception in a manner that places a meaningful limit
on the judicial exception, such that the claim is more than a drafting effort
designed to monopolize the judicial exception.” Eligibility Guidance, 84
Fed. Reg. 54.
Integration into a practical application is evaluated by identifying
whether there are additional elements individually, and in combination,
which go beyond the judicial exception. Eligibility Guidance, 84 Fed. Reg.
54–55. As explained in the October 2019 Update to Subject Matter
Eligibility,6 “first the specification should be evaluated to determine if the
disclosure provides sufficient details such that one of ordinary skill in the art
would recognize the claimed invention as providing an improvement.” PEG
Update 12. According to the PEG Update, the “specification need not

6 Available at
https://www.uspto.gov/sites/default/files/documents/peg_oct_2019_update.p
df (last accessed Nov. 15, 2019) (“PEG Update”).

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explicitly set forth the improvement, but it must describe the invention such
that the improvement would be apparent to one of ordinary skill in the art.”
Id.
The Specification describes how “CMMs have been used in industry
to achieve business improvement for decades,” but states that “attempts to
use CMMs for marketing analysis have been limited in their utility because
they are not based on objective criteria.” Spec. ¶ 7. To address this
problem, the Specification describes using a normative database (step a of
claim 1) and a body of knowledge database (“BOK”) (step d of claim 1).
Spec. ¶¶ 8, 27. Each of these elements constitutes information. “Claim
limitations directed to the content of information and lacking a requisite
functional relationship are not entitled to patentable weight because such
information is not patent eligible subject matter under 35 U.S.C. § 101.”
Praxair Distribution, Inc. v. Mallinckrodt Hospital Products IP Ltd., 890
F.3d 1024, 1032 (Fed. Cir. 2018). To be given patentable weight, the
printed matter must be “functionally related to the substrate on which the
printed matter is applied. E.g., In re DiStefano, 808 F.3d 845, 848 (Fed. Cir.
2015); In re Gulack, 703 F.2d 1381, 1385 (Fed. Cir. 1983).” Praxair, 890
F.3d at 1031–1032. In this case, while the information in the database is
used to assess the organization’s marketing capability, it does not have the
requisite functional relationship to the substrate because it does not change
how the method is performed. In contrast, in Gulack, where a band was
printed with digits, the court found that the digits imparted a functional
relationship to the band because the printed digits enabled the band to
display various aspect of number theory. See Gulack, 703 F.2d at 1383,
1385, 1387 (“the digits exploit the endless nature of the band.”). The
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normative and BOK databases do not have a functional relationship to the
substrate on which they are stored as the digits did in Gulack.
Appellant argues, however, that the normative and BOK databases
“represent non-abstract elements, despite the fact that they are implemented
in software, because the structure of these elements themselves is distinct
from the ordinary, conventional method of implementing a database.”
Appeal Br. 16. Appellant describes how the BOK “is able to organize the
various capabilities necessary to meet multi-channel challenges.” Id.
Appellant explains that utilizing the BOK “for generating the appropriate
questions related to business challenges, and then utilizing the industry data
from the normative database, it is possible to generate a maturity report that
also includes comparisons with industry (i.e., peer) norms and industry
leaders.” Id. Appellant also identifies the dynamic updating of the
normative database as “technological structure of the invention itself.” Id. at
16–17. Appellant concludes that “just as with the database structure” in
Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016), “the
structure of the present invention is non-conventional and leads to
improvements in the function of the technological system as a whole.”
Appeal Br. 17.
Appellant’s arguments are not persuasive.
In Enfish, the claims were directed to a data storage and retrieval
system for a computer memory. Enfish, 822 F.3d at 1336. The system
comprised a system for configuring the memory according to logical table,
where the logical table included:
a plurality of logical rows, each said logical row including an
object identification number (OID) to identify each said logical
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row, each said logical row corresponding to a record of
information;
a plurality of logical columns intersecting said plurality of
logical rows to define a plurality of logical cells, each said
logical column including an OID to identify each said logical
column; and
means for indexing data stored in said table.
Id.
The court found that the claimed “self-referential table functions
differently than conventional database structures.” Enfish, 822 F.3d at 1337.
The court found the claims were not simply directed to the concept of
organizing information, but instead “are directed to an improvement in the
functioning of a computer.” Id. at 1338. Specifically, the court found that
“self-referential table recited in the claims on appeal is a specific type of
data structure designed to improve the way a computer stores and retrieves
data in memory.” Id. at 1339.
Here, we have not been directed to disclosure in the Specification that
describes a different structure for the BOK and normative databases.
Appellant explains how the databases are used differently to achieve the
desired result of determining maturity levels and a targeted desired state, but
Appellant does describe not how the database structures improve the
functioning of the computer as they did in Enfish. Appeal Br. 16.
Appellant contends that the claims are significantly more because the
claims recite “unique, unconventional architectural elements” which include
the BOK and normative databases which “enable the dynamic, evolving
system to perform the functions of the claimed invention in an
unconventional manner.” Appeal Br. 20. Appellant points out that “the
normative database is dynamic, such that the peer group norms and peer
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group leader data are changing with each use of the overall system. The
system thus grows in complexity and accuracy over time.” Id. Appellant
cites Amdocs (Israel) Limited v. Openet Telecom, Inc., 841 F.3d 1288 (Fed.
Cir. 2016) to support this argument. Appeal Br. 18–19.
In Amdocs, the representative claim was directed to “[a] computer
program product embodied on a computer readable storage medium for
processing network accounting information.” Amdocs, 841 F.3d at 1299.
The claim comprised “computer code for using the accounting information
with which the first network accounting record is correlated to enhance the
first network accounting record.” Id. The court construed the term
“enhance” to invoke the “invention’s distributed architecture” which the
court found was “a critical advancement over the prior art” because it
“reduce[s] congestion in network bottlenecks but still allows the data to be
accessible from a central location.” Id. at 1300. The court explained that the
claim “entails an unconventional technological solution (enhancing data in a
distributed fashion) to a technological problem (massive record flows which
previously required massive databases)” which “necessarily requires that
these generic components operate in an unconventional manner to achieve
an improvement in computer functionality.” Id. at 1300–1301.
Appellant asserts that the rejected claims, like those in Amdocs, have
an unconventional architecture to improve computer function. Appeal Br.
2–21. However, the only improvement that Appellant has guided us to is in
how the databases are used to perform the self-assessment survey. Appeal
Br. 16 (The BOK “is able to organize the various capabilities necessary to
meet multi-channel challenges;” utilizing BOK “for generating the
appropriate questions related to business challenges, and then utilizing the
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industry data from the normative database, it is possible to generate a
maturity report that also includes comparisons with industry (i.e., peer)
norms and industry leaders.”). Appellant has not identified how the
architecture of the databases is different from conventional databases nor
does Appellant identify the technological problem solved by the database
which improves computer or internet function. The problem addressed by
the claims, as explained in the Specification, is improving business
assessment using the databases in a self-assessment tool. Spec. ¶ 8. The
steps involving the use of the databases are integral to the abstract idea of
organizing human activity. As discussed above, an additional element,
beyond the abstract idea of organizing human activity, is necessary to
integrate the idea into a practical application. See supra at pp. 16–17, 21.
The improvement asserted by Appellant is to the content of the databases
and their application to assessing marketing capability. Appeal Br. 16. The
latter represent the abstract idea, itself, and therefore cannot serve as the
“additional element” necessary to integrate the abstract idea into a practical
application.
Appellant further argues:
In the present case, the claims are also an ordered combination
that achieves functionality greater than that of its individual
components because of a non-generic arrangement. In creating
the presently claimed invention, the inventors combined a body
of knowledge (BOK) and normative database in a particular
arrangement so that the system dynamically improves its
function over time as the invention is applied to more and more
organizations.
Appeal Br. 21.
However, Appellant has not identified an arrangement of the system
that is responsible for the dynamic improvement in function to take place
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over time. The claim recites “wherein the normative database is
dynamically updated with additional peer group average data and peer group
leader data for a plurality of business organizations over time.” The step
does not recite how the dynamic updating is achieved. Rather, only the
result is claimed. As discussed in McRO, the “abstract idea exception has
been applied to prevent patenting of claims that abstractly cover results
where ‘it matters not by what process or machinery the result is
accomplished.’ [O’Reilly v. Morse, 56 U.S. 62, 113, (1853)]; see also Mayo,
132 S.Ct. at 1301.” See McRO, Inc. v. Bandai Namco Games Am. Inc., 837
F.3d 1299, 1314 (Fed. Cir. 2016). McRO stated that therefore, a court must
“look to whether the claims in these patents focus on a specific means or
method that improves the relevant technology or are instead directed to a
result or effect that itself is the abstract idea and merely invoke generic
processes and machinery.” McRO, 837 F.3d at 1314. In this case, while the
dynamic updating of the normative database (step a) may facilitate the self-
assessment, the claim does not require it to be executed in any specific
manner.
The claimed steps, as a whole, recite the desired result, but not
specific rules that would deter preemption of the abstract idea of organizing
human activity. In McRO, the court held that the “limitations in claim 1
prevent preemption of all processes for achieving automated lip-
synchronization of 3–D characters.” McRO, 837 F.3d at 1315. The court
explained that “[t]he specific structure of the claimed rules would prevent
broad preemption of all rules-based means of automating lip
synchronization.” Id. Here, the steps in rejected claim 1 are recited in such
general terms – “dynamically updated” (step a), generating and receiving
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business challenges and a subset of challenges (steps b and c), receiving
attributes from a BOK (step d), receiving attributes and maturity levels for
attributes (steps e and f) – that generating a report based on such steps would
preempt the abstract idea embodied in the claims. The step of using the
normative database by “g. receiving at the processor a targeted desired state
from the normative database” is also stated as a result and does not explain
how the desired state is derived from the database. Thus, the claim
limitations that led to the claims in McRO being held patent-eligible are not
present here.
Appellant has not provided sufficient evidence that the computer
functionality is improved or that the databases are arranged in unique
combination to have solved a technological problem. Rather, the claims in
this appeal are deficient for the same reasons as in BSG Tech LLC v.
Buyseasons, Inc., 899 F.3d 1281 (Fed. Cir. 2018). As explained by the
court:
[T]he asserted claims are directed to the abstract idea of
considering historical usage information while inputting
data. . . . Claim 1 of the ’699 patent recites a method of
indexing wherein a user adds data to a database using “a
mechanism for posting the data as parametized items” after
receiving “summary comparison usage information” about
parameters and values selected by prior users. ’699 patent col.
10 l. 64–col. 11 l. 10. BSG Tech does not purport to have
invented database structures that allow database users to input
item data as a series of parameters and values. . . . Rather, the
claim’s “focus” is guiding database users by presenting
summary comparison information to users before they input
data. . . . This is not a method “necessarily rooted in computer
technology in order to overcome a problem specifically arising
in the realm of” wide access databases. DDR Holdings, LLC v.
Hotels.com, L.P., 773 F.3d 1245, 1257 (Fed. Cir. 2014).

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BSG Tech, 899 F.3d at 1286.
The benefits described by Appellant – dynamically updating a
normative database and the BOK database – “are not improvements to
database functionality. Instead, they are benefits that flow from performing
an abstract idea in conjunction with a well-known database structure.” Id. at
1288.
Accordingly, for the foregoing reason, we conclude that the abstract
idea of organizing human activity is not integrated into a practical
application.

Step 2B
Because we determined that the judicial exception is not integrated
into a practical application, we proceed to Step 2B of the Eligibility
Guidance, which asks, as in the Mayo/Alice framework, whether there is an
inventive concept. In making this Step 2B determination, we must consider
whether there are specific limitations or elements recited in the claim “that
are not well-understood, routine, conventional activity in the field, which is
indicative that an inventive concept may be present” or whether the claim
“simply appends well-understood, routine, conventional activities previously
known to the industry, specified at a high level of generality, to the judicial
exception, indicative that an inventive concept may not be present.”
Eligibility Guidance, 84 Fed. Reg. 56 (footnote omitted). We must also
consider whether the combination of steps in the claim perform “in an
unconventional way and therefore include an ‘inventive step,’ rendering the
claim eligible at Step 2B.” Id. In this part of the analysis, we consider “the
elements of each claim both individually and ‘as an ordered combination’”
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must be considered “to determine whether the additional elements
‘transform the nature of the claim’ into a patent-eligible application.” See
Alice, 573 U.S. at 217.
Appellant asserts:
[T]he [A]pplicant’s invention cannot be fully understood by
simply looking at each step, and each particular component, in a
vacuum. The ordered combination of these components allows
the invention to provide revised outputs for each iteration,
while also improving the invention's accuracy after each
iteration. This combination is not routine or conventional; it is
a dramatic step forward in achieving the solution to which the
invention is addressed.
Appeal Br. 21.
The stated “ordered combination” is said to reside in the arrangement
of BOK and normative databases to improve in function over time. Id.
However, while the recited steps in the claims are performed on a computer,
“a particular way of programming or designing the software” is not recited.
Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1241 (Fed. Cir. 2016).
Appellant asserts that the solution provided by the claims is an
improvement to the abstract idea of organizing human activity using the
dynamically updated normative database. However, while Appellant asserts
the “ordered combination” improves the invention’s accuracy, Appellant did
not identify what step(s) operates in combination with the dynamic updating
of step a of claim 1. Appeal Br. 16, 20. Appellant also has not explained
how the recited processor in the steps operates in an unconventional way to
achieve the dynamic updating of the normative database.
Consequently, under Step 2B, we are not persuaded that the Examiner
erred in determining that the additional limitations of claim 1 do not
transform the claim into significantly more than the abstract idea.
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Summary
For the foregoing reasons, we affirm the rejection of claim 1 under 35
U.S.C. § 101. Claims 2–9 and 12–22 fall with claim 1 for the same reasons.

CONCLUSION
In summary:
Claims
Rejected
35 U.S.C. § Reference(s)/Basis Affirmed Reversed
1–9, 12–17,
20–22
103 Lewis, Dagnino 1–5, 7–9,
12–17, 20–
22
6
18, 19 102 Lewis 18, 19
1–9, 12-22 101 Eligibility 1–9, 12–22
Overall
Outcome
1–9, 12–22

TIME PERIOD
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).

AFFIRMED