Ex Parte Barlow et al

Patent Trial and Appeal Board

Mar 17, 2015

11968315 (P.T.A.B. Mar. 17, 2015)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte LISA R. BARLOW, JAMES H. DREW,
KATHERINE T. ROSS, and PAULA WEHMEYER
____________

Appeal 2012-009390
Application 11/968,315
1

Technology Center 3600
____________

Before ANTON W. FETTING, NINA L. MEDLOCK, and
SHEILA F. McSHANE, Administrative Patent Judges.

McSHANE, Administrative Patent Judge.

DECISION ON APPEAL
The Appellants seek our review under 35 U.S.C. § 134(a) of a
decision of the Examiner to reject claims 1–2, 4–9, and 11–20. We have
jurisdiction under 35 U.S.C. § 6.

We AFFIRM.

1
According to Appellants, the real party in interest is Verizon
Communications Inc. (Appeal Brief filed March 5, 2012, hereafter “Appeal
Br.” 1).
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BACKGROUND
The invention relates to a method and apparatus for modeling to
dynamically forecast workforces and workloads as they relate to a service
provider environment (Specification, hereafter “Spec.” at ¶ 12). The
purpose of the invention is to provide more efficient workforce and
workload modeling to facilitate workforce decision making (id., ¶ 2).
Representative claims 1, 15, and 17 are reproduced from pages 18,
and 20–21 of the Appeal Brief (Claims App’x) as follows, with emphasis
added to relevant claim limitations:
1. A method comprising:
presenting a portal configured as a user interface to receive
input from a user, wherein the input relates to forecasting workload
and workforce for providing a communication service, the workload
including ticket loads relating to repair and provisioning, the
workforce including human resources and equipment;
outputting, via the portal, a load prediction that is calculated by
at least one processor in response to the input, wherein the load
prediction is generated by a forecast model that utilizes regression
analysis of historical data and real-time information that includes
workforce availability data and one or more factors impacting the
workload; and notifying the user when the load prediction results in a
particular quantity of jobs that have been scheduled but are, as yet,
incomplete.
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15. A computer-implemented method comprising:
defining a plurality of prediction periods;
determining, via at least one processor, a quantity of
tickets corresponding to each of the prediction periods, wherein
a ticket corresponds to a job;
computing, via the at least one processor, an average
quantity for the tickets for a predetermined duration;
determining, via the at least one processor, average
amount of precipitation, or average amount of relative
humidity, or a combination thereof, for a corresponding
plurality of locations;
retrieving coefficients corresponding to the locations,
wherein the coefficients indicate degree of influence of weather
condition or prior load for the respective locations; and
outputting, via the at least one processor, a predicted
ticket load based on the average quantity, the average amount
of precipitation, the average amount of relative humidity, and
the coefficients.
17. A method according to claim 15, further comprising:
receiving workforce information; and
determining quantity of incomplete jobs based on the
workforce information and the predicted ticket load.
The Examiner rejected claims 1–2, 4, 6–9, 11, and 13–14, under
35 U.S.C. § 103(a) as unpatentable over Laperi,
2
Wetzer,
3
and Salman.
4

2
US Patent Publication 2007/0179829 A1, published August 2, 2007.
3
US Patent Publication 2004/0162811 A1, published August 19, 2004.
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Claims 5 and 12 were rejected under 35 U.S.C. § 103(a) as unpatentable
over Laperi, Wetzer, Salman, and Dondi.
5
The Examiner rejected claims 15,
17, and 19–20 under 35 U.S.C. 103(a) over Laperi, Dondi, and Kiran.
6

Claim 16 was rejected under 35 U.S.C. 103(a) over Kiran, Laperi, Dondi,
and Hsu.
7
Finally, claim 18 was rejected under 35 U.S.C. 103(a) over Kiran,
Laperi, Dondi, and Salman. (Final Action, hereafter “Final Act.,” mailed
February 2, 2012, 2; Examiner’s Answer mailed April 27, 2012, hereinafter
“Ans.,” 2–26).
DISCUSSION
The Appellants grouped the rejections of claims 1, 2, 4, 6–9, 11, 13,
and 14, with claim 1 serving as the representative claim (Appeal Br. 6–10).
For claims 5 and 12, Appellants asserted that the additional reference,
Dondi, did not address the deficiencies noted for claim 1 (id. at 10);
therefore, the issues we will address for claim 1 apply to claims 5 and 12.
Independent claim 15 was argued on common issues with dependent claims
17, 19, and 20, with additional issues presented for claim 17 (id. at 11–15),
so we will address claims 15 and 17 individually. For claim 16, Appellants
argued that the additional reference, Hsu, did not address the deficiencies
noted for claim 15 (id. at 16); therefore, the issues we will address for claim
15 apply to claim 16. Similarly for claim 18, Appellants argued that the

4
Iyad A. Salman, Forecasting Models For Maintenance Work Load With
Seasonal Components, International Symposium on Product Quality and
Integrity, Vol. XVIII-679, pp. 514–520, Los Angeles CA, January 26, 2004.
5
Peter Dondi, et al., Internet Service Provider - Load Forecast, lEE
Conference Publication No. 482, June 18–21, 2001.
6
US Patent Publication 2005/0240465 A1, published October 27, 2005.
7
Y.Y. Hsu, et al., Fuzzy expert systems: an application to short-term load
forecasting, lEE Proceedings-C, Vol. 139, No. 6, pp. 471–477, November
1992.
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additional reference, Salman, did not address the deficiencies noted for
claim 15 (id.); therefore, the issues we will address for claim 15 apply to
claim 18.
Representative Claim 1

The Appellants asserted that because the references of Laperi, Wetzer
and Salman do not teach all the limitations of representative claim 1, the
Examiner did not establish prima facie obviousness (id. at 6). Specifically,
Appellants argued that there is no disclosure of “notifying the user when the
load prediction results in a particular quantity of jobs that have been
scheduled but are, as yet, incomplete” in any of the prior art references (Id.).
Appellants characterized Laperi’s disclosures as “[a]t best, reallocation of a
trouble ticket [that] might be indicative of an unfinished resolution of a
problem but [] clearly does not act to notify ‘the user when the load
prediction results in a particular quantity of jobs that have been scheduled
but are, as yet, incomplete,’ since there is no notification of any ‘particular
quantity of scheduled, but incomplete jobs.’” Id. at 7. More specifically,
rather than providing notification of the status of incomplete jobs, the
Appellants asserted that Laperi only notifies managers regarding the number
of overtime hours needed per the remaining workforce members for the day
(id., citing Laperi ¶ 72). Further, the Appellants asserted that although
Laperi may disclose that managers may be easily updated on workloads and
a need for overtime, it fails to teach notifications as a result of “load
predictions.” Id. at 8–9.
The Examiner found that Laperi disclosed automatic suggestions for
managers for forecasted workloads, determining overtime requirements for
additional work items, with graphical representations of quantities of
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workloads for assignment (Ans. 27 ( citing Laperi ¶¶ 59, 72; Fig. 8)).
Specifically, the Examiner referred to Figure 8 in detail, that shows jobs that
are scheduled but not complete, i.e., showing 372 work tickets left to be
assigned, with 480 tickets needing to be addressed (scheduled, but not
completed) (id. at 5–6). The Examiner noted that Figure 7 also discloses
trouble tickets left from the previous day to be completed (630), as well as
tickets forecasted for the rest of the day (id. at 28–29). The Examiner noted
Laperi’s disclosures of workload forecasts, as well as notifications to
managers (“automated suggestions”), along with graphical interfaces which
serve to notify (id. at 27–31 (citing Laperi Figs. 7 and 8; ¶¶ 50–59, 62, 64,
65, 72, 84)).
We find that the preponderance of the evidence supports the
Examiner’s determination that that the subject matter of claim 1 would have
been obvious at the time of Appellants’ invention to one of ordinary skill in
the art in view of Laperi, Wetzer, and Salman. Although Appellants make
several generalized arguments that are directed towards alleged differences
in the disclosures of Laperi and the claim limitation “notifying the user when
the load prediction results in a particular quantity of jobs that have been
scheduled but are, as yet, incomplete,” we do not agree. The Examiner’s
findings are well supported by the disclosures in the prior art references, and
we, therefore, adopt the same in affirming the obviousness rejection of
representative claim 1.
Claim 15

Appellants argued that there is no disclosure in the prior art references
teaching claim 15’s limitation of “computing, via the at least one processor,
an average for the tickets for a predetermined duration” in the prior art
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(Appeal Br. 11). More specifically, Appellants contended that the
disclosures that the Examiner relied upon, for instance, Figure 2 or
Paragraph 36 of Laperi, do not teach this limitation (id. at 11–12).
Appellants argued that although the “workload” of Laperi may represent the
number of trouble tickets handled per hour or per shift, they do not represent
an “average” of the tickets for a predetermined period (id. at 11). Further,
Appellants alleged that the Laperi teaching is inadequate because the
“weighted average” of Figure 2 does not teach the limitation at issue because
“an average of historical data does not teach an average for tickets during a
predetermine[d] duration, as ‘historical data’ does not correspond to the
claimed ‘tickets.’” (id. at 12). Additionally, Appellants asserted that Laperi
fails to disclose a “predicted ticket load based on the average quantity,
the average amount of precipitation, the average amount of relative
humidity, and the coefficients.” Id. at 13.
The Examiner responded that although the Appellants view Laperi’s
disclosures as only averages for workloads, the reference explicitly states
that “the workload may refer to the number of trouble tickets to be handled
per hour or per shift” (Ans. 32 (citing Laperi ¶¶ 29, 36)). Further, the
Examiner referred to the disclosure of the use of the term “average[s]” in the
context of using previous data in a forecast formula for tickets over specific
time durations (id. (citing Laperi ¶¶ 40, 57)). Finally, the Examiner noted
that although Laperi was relied upon for the use of computed averages in
forecasting, Dondi and Kiran were relied upon for teaching, in combination,
the use of average precipitation, relative humidity and coefficients (id. at
33).
We find that the preponderance of the evidence supports the
Examiner’s determination that that the subject matter of claim 15 would
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have been obvious at the time of Appellants’ invention to one of ordinary
skill in the art in view of Laperi, Dondi, and Kiran. Although Appellants
make several generalized arguments that are directed towards alleged
differences in the disclosures of Laperi and the claim limitation “computing,
via the at least one processor, an average for the tickets for a predetermined
duration,” we do not agree. The Examiner’s findings are well supported by
the disclosures in the prior art reference, and we further agree that one
cannot show nonobviousness by attacking references individually where the
rejections are based on combinations of references. See In re Keller, 642
F.2d 413, 426 (CCPA 1981); In re Merck & Co., Inc., 800 F.2d 1091, 1097
(Fed. Cir. 1986). We, therefore, affirm the Examiner’s rejection of claim 15.
Claim 17

Claim 17 depends from claim 15, and in addition to the issues that
Appellants raised as to claim 15, an additional allegation was made that the
claim limitation of “determining quantity of incomplete jobs based on the
workforce information and the predicted ticket load” was not disclosed
(Appeal Br. 13). Here, the Appellants argued that although Laperi may
teach suggestions and updates to managers on workloads, it does not initially
provide “the quantity of incomplete jobs,” nor base workload determination
upon predicted ticket load (id. at 14–15). In response, the Examiner referred
to Laperi’s disclosure of providing incomplete job information to managers
based on workload and the number of hours projected to cover the workload
based upon ticket load (Ans. 34 (citing Laperi ¶¶ 50–59, 62, 64, 65, 72;
Fig. 8)). We concur with the Examiner’s findings and affirm the rejection of
claim 17.

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SUMMARY
The Examiner’s rejections of claims 1–2, 4–9, and 11–20 under
35 U.S.C. § 103(a) are affirmed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a).

AFFIRMED

Ssc