U.S. patent application number 11/627064 was filed with the patent office on 2007-05-31 for method and system for estimating supply impact on a firm under a global crisis.
Invention is credited to Ching-Hua Chen-Ritzo, Pawan Raghunath Chowdhary, Thomas Robert Ervolina, Dharmashankar Subramanian.
Application Number | 20070124190 11/627064 |
Document ID | / |
Family ID | 29735522 |
Filed Date | 2007-05-31 |
United States Patent
Application |
20070124190 |
Kind Code |
A1 |
Chen-Ritzo; Ching-Hua ; et
al. |
May 31, 2007 |
METHOD AND SYSTEM FOR ESTIMATING SUPPLY IMPACT ON A FIRM UNDER A
GLOBAL CRISIS
Abstract
The availability of relevant business resources, or supply,
during a global crisis or disruption are estimated by using a
forecast of a baseline supply of human resources and various forms
of infrastructure and raw materials for a firm as input. That
forecast is corrected to account for the impact of a crisis or
other disruption, and a corrected forecast as output is provided.
The corrected forecast reflects changes in the availability of
business resources due to the crisis or disruption, dependencies
between resources, as well as any mitigating effects resulting from
the implementation of mitigation policies.
Inventors: |
Chen-Ritzo; Ching-Hua;
(Mahopac, NY) ; Chowdhary; Pawan Raghunath;
(Montrose, NY) ; Ervolina; Thomas Robert;
(Poughquag, NY) ; Subramanian; Dharmashankar;
(Tarrytown, NY) |
Correspondence
Address: |
WHITHAM, CURTIS & CHRISTOFFERSON, P.C.
11491 SUNSET HILLS ROAD, SUITE 340
RESTON
VA
20190
US
|
Family ID: |
29735522 |
Appl. No.: |
11/627064 |
Filed: |
January 25, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10989530 |
Nov 16, 2004 |
7195995 |
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11627064 |
Jan 25, 2007 |
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10650563 |
Aug 28, 2003 |
6858534 |
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10989530 |
Nov 16, 2004 |
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10230948 |
Aug 29, 2002 |
6670682 |
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10650563 |
Aug 28, 2003 |
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Current U.S.
Class: |
705/7.22 ;
257/E21.166; 257/E21.345; 257/E21.585; 257/E21.62; 257/E21.627;
257/E23.019; 257/E29.063; 705/7.12; 705/7.13; 705/7.31;
705/7.34 |
Current CPC
Class: |
G06Q 30/0202 20130101;
G06Q 10/06312 20130101; H01L 27/10888 20130101; H01L 29/6659
20130101; H01L 21/2254 20130101; H01L 27/10855 20130101; H01L
27/10873 20130101; H01L 29/1083 20130101; H01L 21/76877 20130101;
H01L 21/823475 20130101; H01L 21/28512 20130101; G06Q 10/063
20130101; G06Q 10/06311 20130101; H01L 21/28525 20130101; G06Q
10/0631 20130101; G06Q 30/0205 20130101; H01L 21/823425 20130101;
H01L 23/485 20130101; H01L 21/26586 20130101; H01L 2924/0002
20130101; H01L 21/2257 20130101; H01L 29/6656 20130101; H01L
2924/0002 20130101; H01L 2924/00 20130101 |
Class at
Publication: |
705/008 ;
705/010 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A method of estimating the availability of one or more business
resources in the event of a crisis or other disruption, comprising
the steps of: using a computer to receive as input a forecast of
business resource availability under baseline conditions, and a set
of parameter values representing one or more of business policies,
human factors, severity of said crisis or disruption, and
dependencies between resources; using a computer to determine a
corrected forecast of business resource availability to account for
an impact of a disruption by taking into account change in the
availability of one or more resources accounted for in conventional
business planning processes due to said disruption, and change in
the availability of one or more resources not accounted for in
conventional business planning processes due to said disruption;
and using a computer to provide said corrected forecast of business
resource availability as output.
2. The method of claim 1 wherein the disruption is an
epidemiological crisis.
3. The method of claim 1 wherein resources accounted for in said
conventional business planning processes include one or more of raw
materials, machinery, and human resources.
4. The method of claim 3 wherein said conventional business
planning processes lack accounting for one or more resources
selected from the group consisting of network connectivity, clean
water, electricity, roads, maritime port and shipping capacity, air
travel capacity, air freight capacity, global logistics hubs, site
access, and availability of human resources of one or more of the
firm's suppliers.
5. The method of claim 1, wherein the step of correcting the
forecast of resource availability to account for the potential
impact of a disruption takes into account a dependency between
resources accounted for in a conventional business planning process
and resources not accounted for in a conventional business planning
process.
6. The method of claim 1 wherein the step of correcting the
forecast of resource availability to account for the potential
impact of a disruption takes into account one or more potential
changes in available resources due to an effect of one or more
mitigation policies.
7. The method of claim 1 wherein input is provided for one or more
geographic locations and time periods, taking into account each
dependency between a location and a time period.
8. The method of claim 1 wherein output is provided for one or more
geographical locations and time periods, taking into account each
dependency between a location and a time period.
9. A system for estimating the availability of one or more business
resources in the event of a crisis or other disruption, comprising:
a computer receiving as input forecast data of business resource
availability under baseline conditions, and a data set of parameter
values representing one or more of business policies, human
factors, severity of said crisis or disruption, and dependencies
between resources; a computer determining a corrected forecast of
business resource availability to account for an impact of a
disruption by taking into account change in the availability of one
or more resources accounted for in conventional business planning
processes due to said disruption, and change in the availability of
one or more resources not accounted for in conventional business
planning processes due to said disruption; and a computer providing
said corrected forecast of business resource availability as
output.
10. The system of claim 9 wherein the disruption is an
epidemiological crisis.
11. The system of claim 9 wherein the resources accounted for in
said conventional business planning processes include one or more
of raw materials, machinery, and human resources.
12. The method of claim 9 wherein said conventional business
planning processes lack accounting for one or more resources
selected from the group consisting of network connectivity, clean
water, electricity, roads, maritime port and shipping capacity, air
travel capacity, air freight capacity, global logistics hubs, site
access, and availability of human resources of one or more of the
firm's suppliers.
13. The system of claim 9, wherein determining the corrected
forecast of resource availability to account for the potential
impact of a disruption takes into account a dependency between
resources accounted for in a conventional business planning process
and resources not accounted for in a conventional business planning
process.
14. The system of claim 9 wherein determining the corrected
forecast of resource availability to account for the potential
impact of a disruption takes into account one or more potential
changes in available resources due to a effect of one or more
mitigation policies.
15. The system of claim 9 wherein input is provided for one or more
geographic locations and time periods, taking into account each
dependency between a location and a time period.
16. The system of claim 9 wherein output is provided for one or
more geographical locations and time periods, taking into account
each dependency between a location and a time period.
17. A machine-readable medium for estimating the availability of
one or more business resources in the event of a crisis or other
disruption, on which is provided: machine-readable instructions for
a computer to receive as input a forecast of business resource
availability under baseline conditions, and a set of parameter
values representing one or more of business policies, human
factors, severity of said crisis or disruption, and dependencies
between resources; machine-readable instructions for a computer to
determine a corrected forecast of business resource availability to
account for an impact of a disruption by taking into account change
in the availability of one or more resources accounted for in
conventional business planning processes due to said disruption,
and change in the availability of one or more resources not
accounted for in conventional business planning processes due to
said disruption; and machine-readable instructions for a computer
to provide said corrected forecast of business resource
availability as output.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The present invention relates to the estimation of changes
in the availability of resources for the creation and delivery of
goods and/or services resulting from the impact of a global
disruption or crisis, including, but not limited to, the
circumstances created by a pandemic.
[0003] 2. Background Description
[0004] Under a disruption or crisis, the availability of resources
affecting the production of goods and/or services by a firm may be
impacted. It is important for a firm to understand how the
availability of various resources necessary for the production and
delivery of goods and/or services to their customers may change due
to a crisis, or disruptive event, since this will ultimately affect
the firm's ability to operate profitably during, and in the
aftermath of the crisis.
[0005] Examples of the impact that a crisis may have on the
availability of resources (also more generally referred to as
"supply") include, but are not limited to, the following: [0006]
Reduced availability of firm's employees; [0007] Reduced
availability of firm's partners' or suppliers' employees; [0008]
Reduced availability of infrastructure (potentially including, but
not limited to, air, water, road, telecommunications, buildings,
information technology and electricity); [0009] Reduced
availability of logistics hubs (e.g., international shipping ports
and airports); [0010] Reduced availability of raw materials and
office supplies/equipment from suppliers; and [0011] Reduced
availability of services procured or outsourced by the firm.
[0012] Under normal (i.e., non-crisis) conditions, a firm typically
considers only a subset of the resources previously listed in its
business-as-usual planning process(es). For example, a
manufacturing firm may use a process called `material requirements
planning` (MRP) for managing its manufacturing process. In MRP,
typically only raw materials or parts are considered to be a
constraining resource (i.e., physical items used directly in the
assembly or production of the final product(s)). The premise of MRP
is that a manufacturer can predict the availability of their goods,
either for distribution to retailers or delivery to customers,
based simply on the availability of the necessary raw materials and
parts. Therefore, conventional MRP systems take as input the
availability of these raw materials and parts.
[0013] Additionally, a manufacturing firm may also use a process
referred to as `capacity planning` (CP) to estimate its capacity
for producing goods. Typically, in this context, capacity refers to
both machine capacity and labor capacity. Therefore, combining MRP
with CP, under normal conditions, a manufacturer may consider only
machine, labor and raw material/part availability when managing
their manufacturing process. While resources such as clean water,
electricity, network connectivity, telecommunications and third
party logistics services may also be necessary to the
manufacturer's operations, they are typically assumed to be
unconstrained or otherwise taken for granted under normal
conditions. Therefore, these latter such resource types are
typically not considered as inputs in MRP or CP systems.
[0014] Under disruptive or crisis conditions, however, resources
that are not typically considered to be critical or constraining,
may become critical or constraining. Thus, the availability of such
resources may significantly affect the firm's ability to meet the
demand for its product(s).
SUMMARY OF THE INVENTION
[0015] A firm may be able to mitigate the potential impact of a
crisis on the availability of resources by implementing one or more
mitigation plans. For example, in the case of a disruption caused
by a hurricane, structural damage to materials stored in warehouses
could be reduced by reinforcing or otherwise protecting warehouse
windows. In the case of a disruption caused by a pandemic,
employees could be provided with vaccinations to reduce the
probability of infection. Additionally, employees could be
cross-trained so that they have overlapping skills and can `fill
in` for absent workers in the event of a crisis. These are all
examples of potential mitigation plans.
[0016] The present invention provides a method and system for
estimating the availability of resources that may affect a firm's
business operations as a result of a crisis or disruption, by:
[0017] Accounting for how a crisis may impact the availability of
resources that a firm typically factors into its conventional
business planning processes (e.g., in manufacturing, examples of
such conventional processes may include MRP and/or CP) [0018]
Accounting for how a crisis may impact the availability of
resources that a firm typically does not factor into its
conventional business planning processes [0019] Accounting for
dependencies between the availability of resources that a firm
typically factors into its conventional business planning processes
and those that it does not [0020] Assessing how one or more
mitigation strategies may impact the aforementioned effects of a
crisis on resource availability [0021] Performing at least one of
the above for one or more geographical locations and for one or
more time periods, accounting for potential dependencies between
locations and time periods.
BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The foregoing and other objects, aspects and advantages will
be better understood from the following detailed description of a
preferred embodiment of the invention with reference to the
drawings, in which:
[0023] FIG. 1 shows the use of a supply model according to the
present invention.
[0024] FIG. 2 shows a system configured according to the present
invention.
[0025] FIG. 3 shows a sample output assessing the effect of a
crisis on supply according to the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE
INVENTION
[0026] The present invention seeks to provide estimates of the
impact of crises or otherwise disruptive events on supply by
extending and adapting traditional supply estimation techniques by
assessing the impact of a disruption on resources that may be
assumed to be unconstrained under normal conditions, and which may
affect the ability of the firm to produce its product(s) and/or
which may impact the availability of resources typically accounted
for in business planning under normal conditions. According to the
present invention, a computer estimates supply requirements by (i)
receiving as input a forecast of a firm's "baseline" supply of
human resources, various forms of infrastructure and raw materials,
(ii) correcting the forecast to account for the impact of a crisis,
while also taking into account the potential effects of one or more
mitigation policies, and (iii) providing the corrected forecast of
the availability of supply of human resources, various forms of
infrastructure and raw materials as output, and (iv) providing an
additional output that includes a forecast of the availability one
or more resources during said crisis that may not have been
included in the said forecast of business resource availability
under baseline conditions, whose availability is derived from one
or more of the following: the availability of other resources that
may have been included in the said forecast of business resource
availability under baseline conditions, input parameter values. For
example, the availability of resource type "site-open" (described
in model details) is derived from the availability of employees and
the business policy that determines when a site will be made
accessible. As another example, the availability resource type
"hub" (described in model details) at one location is derived from
the availability of "localxport" resources and human resources in
one or more other locations.
[0027] The details of the supply estimation model are described
next.
Supply Model Details
[0028] The supply model takes as input the "baseline" availability
of each relevant type of resource, in one or more geographical
locations and over one or more time periods. This baseline
corresponds to the availability of resources under normal,
non-crisis conditions. Outputs produced by the present invention
may include a time-profile of resource availability over the
planning horizon, for each resource type and each geographical
location of interest. The types of resources, or supply, that may
be considered by the present invention span at least the following
three categories: [0029] Human Resources; [0030] Raw Materials; and
[0031] Infrastructure, which comprises, without limitation,
sub-types such as [0032] "localxport": a measure of availability of
infrastructure which has been defined to include Air-travel, Water,
Roads, Networks and Electricity [0033] "hub": a measure of the
availability of global logistical hubs [0034] "site-open": a
measure of the availability of a firm's facilities [0035] "lift": a
measure of the availability of the global air freight capacity
Details regarding the method for modeling each of the above types
of resources are provided in the sections that follow.
Human Resources
[0036] Human resources, or people, may be modeled as a function of
the number of employees that are working on-site, working from
home, or absent, in each geographical location in each time period
in the planning horizon. These numbers can be obtained, for
example, from an existing epidemiological model which captures
human behavioral effects. Productivity factors for employees in
each of these three states may also be modeled as follows: [0037]
X.sub.s,l,t: Fraction of employees working at on-site at location,
l, and time, t. [0038] .alpha.: Productivity factor for employees
working at site, 0.ltoreq..alpha..ltoreq.1. A default (for example,
.alpha.=0.95) may be set. [0039] X.sub.h,l,t: Fraction of employees
working at home, at location, l, and time, t. [0040] .beta.:
Productivity factor for employees working at home,
0.ltoreq..beta..ltoreq.1. A default (for example, .beta.=0.80) may
be set. [0041] X.sub.a,l,t: Fraction of employees absent at site,
at location l, and time, t. [0042] S.sub.t,l.sup.people: Baseline
supply of people at location l. [0043]
S.sub.t,l,adjusted.sup.people: Adjusted supply of people at
location l, at time, t, due to the crisis. Thus, the effective
availability of employees at location l in time period t is given
by:
S.sub.t,l,adjusted.sup.people=S.sub.t,l.sup.people*(.alpha.X.sub.s,l,t+.b-
eta.X.sub.h,l,t). Human resources can be further categorized by,
for example, job type, skill set, industry expertise, years of
experience and years of education. The same general approach for
estimating the impact of a crisis on human resource availability
would apply in these cases.
Raw Material from Suppliers
[0044] The availability of one or more raw materials from suppliers
may be modeled in terms of a linear dependence between the
availability of a supplier's workforce and the ability of the
supplier to deliver raw materials. [0045] .gamma.: Supplier
Sensitivity. This parameter models the sensitivity of supplier's
capacity to people availability. It stands for the proportional
drop in supplier's capacity, per unit proportional drop in net
employee availability. A default value may be set (for example, a
default value of 0.5 would mean that, if net employee availability
at a supplier location drops by 10%, then supplier parts capacity
would drop by 5%, i.e., 5%=0.5.times.10%). [0046] .kappa.: Supplier
Buffer. This parameter models the buffer that each supplier has
planned for delivery of material to the firm. It stands for the
proportion of the baseline supply amount, which is the buffer
planned by the supplier over and above the baseline amount, for
delivery to the firm. A default value (for example, 0.10) may be
set. [0047] S.sub.t,l.sup.parts: Baseline Supply of supplier parts
from location l, at time, t. S.sub.t,l adjusted.sup.parts: Adjusted
supply of supplier parts from location, l, at time, t, due to the
crisis. Thus the adjusted availability of supplier parts in
location l in time period t due to a crisis may be given by,
S.sub.t,l,adjusted.sup.parts=Min(S.sub.t,l.sup.parts,S.sub.t,l.sup.parts*-
(1+.kappa.)*(1-(.alpha.X.sub.s,l,t+.alpha.X.sub.h,l,t))*.gamma.).
Infrastructure-Related Supply
[0048] The dependence of a firm's operations on
infrastructure-related types of supply may be modeled in terms of
the following items:
[0049] 1. "localxport"
[0050] This sub-type models the effect of local infrastructure in a
given location. It is a measure of availability of infrastructure
which has been defined to include Air-travel, Water, Roads,
Networks and Electricity: [0051] S.sub.t,l.sup.localxport: Baseline
Supply of "localxport", in location, l, and at time, t. [0052]
Y.sub.road,l,t: Proportional availability of Roads, in location, l,
and at time, t. [0053] Y.sub.water,l,t: Proportional availability
of Clean Water, in location, l, and at time, t. [0054]
Y.sub.elec,l,t: Proportional availability of Utilities and
Electricity, in location, l, and at time, t. [0055]
Y.sub.network,l,t: Proportional availability of Network
Communications, in location, l, and at time, t. [0056]
Y.sub.air,l,t: Proportional availability of Air-travel, in
location, l, at time, t. [0057] S.sub.t,l,adjusted.sup.localxport:
Adjusted supply of "localxport", in location, l, and at time, t.
Thus,
S.sub.t,l,adjusted.sup.localxport=S.sub.t,l.sup.localxport*Average{Y.sub.-
road,l,t,Y.sub.water,l,t,Y.sub.elec,l,t,Y.sub.network,l,t,Y.sub.air,l,t}.
[0058] 2. "hub"
[0059] This infrastructure resource type models the dependency of
the firm on the availability of logistics hubs (typically, these
are major international airports). Any given hub may service one or
more geographical regions. A set of hubs may service overlapping
geographical regions. The availability of a hub depends on the
availability of human resources and local infrastructure in the
location of the hub: [0060] S.sub.t,l.sup.hub: Baseline Supply of
"hub", in location, l, and at time, t. [0061] H(l): A set of hub
locations that may service location, l. [0062]
S.sub.t,l,adjusted.sup.hub: Adjusted availability of logistics hubs
in location, l, at time, t. The adjusted availability of logistics
hubs in location l and time period t may be given by,
S.sub.t,l,adjusted.sup.hub=S.sub.t,l.sup.hub*Average.sub.{h in
(H(l)}[(Y.sub.road,h,t+Y.sub.water,h,t+Y.sub.elec,h,t,+Y.sub.network,h,t,-
+Y.sub.air,h,t+(.alpha.X.sub.s,l,t+.beta.X.sub.h,l,t))/6].
[0063] 3. "site-open"
[0064] This infrastructure resource type reflects on whether a site
or facility is open or closed. It takes on value of 0, or 1.0
denotes a closed site, and 1 denotes an open site. When a site is
closed, then the availability of one or more resources located at,
or associated with, that site may be considered unavailable. Site
availability (or "site-open") is computed as follows: [0065]
S.sub.t,l.sup.site-open: Baseline Supply availability of
facility/site, in location, l, and at time, t.
S.sup.t,l.sup.site-open is assumed to be equal to 1, i.e., the site
is considered open, in the baseline. [0066]
S.sub.t,l,adjusted.sup.site-open: Adjusted availability of
facility/site, in location, l, and at time, t. [0067] .eta.: Site
closure threshold fraction. Fraction of employee absenteeism, above
which, a site will be closed. A default value may be set (for
example, a default value of 0.9 would mean that a site is
considered closed if absenteeism exceeds 90%). The adjusted
availability of a site in location l in time period t may be given
by S.sub.t,l,adjusted.sup.site-open=1, if .eta.<=X.sub.a,l,t ,
and S.sub.t,l,adjusted.sup.site-open=0, otherwise.
[0068] 4. "lift"
[0069] This infrastructure resource type models the availability of
global air freight capacity: [0070] S.sub.t.sup.lift: Baseline
Supply of global "lift", at time, t. This is an estimate (or
actual) of air freight capacity that is typically available under
non-crisis conditions at time, t, in order to deliver on the
baseline demand. [0071] .delta.: Scaling factor for reduction in
global air-lift supply. A default value (for example, 80% or 0.8)
may be set. [0072] S.sub.t,adjusted.sup.lift: Adjusted supply of
global air-lift. The adjusted availability of global air freight
capacity may be given by
S.sub.t,adjusted.sup.lift=S.sub.t.sup.lift*.delta..
[0073] The present invention is capable of assessing the effects of
mitigation actions on the availability of resources. For example,
employee cross-training may be implemented as a mitigation policy
in a supply model according to the present invention. Such a model
requires as input a set of cross-trained resource types, each of
which is defined in terms of regular resource types that contribute
towards the creation and composition of a cross-trained type.
EXAMPLE
[0074] A cross-trained resource type named JAVA_C++ could be
defined as being composed of people drawn from regular resource
types, namely JAVA and C++, which contribute towards creating the
cross-trained type, JAVA_C++. The set of cross-trained resource
types, along with the corresponding regular resource type
definitions, is input for each supply location of interest. The
cross-trained resource type, which is desired as a mitigation
policy in any given location, is assumed to be created from its
associated regular resource types that are present in the same
location.
[0075] Other user-input policy parameters include, without
limitation: [0076] .omega.: Yes/No: Whether cross-training policy
is in place, or not. It takes values, 0 or 1. A default value may
be set (for example, a default value of zero would indicate no
cross-training in place). [0077] .chi.: Cross-training extent. This
is a percentage value that stands for the extent of cross-training
implementation. A value of 25% means that 25% of the relevant
regular resource types get cross-trained. A default value may be
set (for example, a default value of zero would indicate no
cross-training had occurred). [0078] T: Time at which cross-trained
resource availability starts. [0079] CR.sub.l,i,t: Cross-trained
resource type, i, in location, l, at time, t. [0080] R(CR.sub.l,i):
Set of regular resources that contribute to the composition of
cross-trained resource type, i, in location, l. The model preserves
head count by ensuring that the cross-trained set of resources are
created from the associated regular set of resources. In other
words, for each unit increase in the size of any cross-trained
resource type, there is a corresponding unit decrease in the size
of some regular resource type that is associated with the
cross-trained resource type.
EXAMPLE
[0081] Let there be 100 Java programmers and 200 C++ programmers in
the baseline set of people supply in location Yorktown Heights.
Also let there be a cross-trained resource type, Java_C++, which is
associated with regular resource types Java and C++. Further, let
the extent of cross-training be 50%, and let the cross-training
start time index (in weeks) be T=5. For weeks 1 through 4, the
following resource profile is used as the baseline set of people
supply. [0082] Java: 100 [0083] C++: 200 [0084] Java_C++: 0
Starting at week 5, the following resource profile is used as the
baseline set of people supply, in Yorktown Heights. [0085] Java: 50
[0086] C++: 100 [0087] Java_C++: 150 Note that the head-count is
conserved across the cross-training mitigation policy. There are a
total of 300 heads in either case. The mitigation results from the
observation that, the cross-trained resource type, Java_C++ is able
to service requests for both Java as well as C++ programming tasks.
[0088] CR.sub.l,i,t=.sub..chi.*
Sum{r(R(CRl,i)}[(S.sub.t,l,adjusted.sup.people,r|.sub.without
cross-training)/N.sub.r], if t>=T, and .omega.=1 [0089]
CR.sub.l,i,t=0, otherwise [0090]
S.sub.t,l,adjusted.sup.people,r=(S.sub.t,l,adjusted.sup.people,r|.sub.wit-
hout cross-training) *.sub..chi., if t>=T, and .omega.=1 [0091]
S.sub.t,l,adjusted.sup.people,r=S.sub.t,l,adjusted.sup.people,r|.sub.with-
out cross-training, otherwise where [0092] N.sub.r: The number of
cross-trained resource types that the regular resource type, r,
contributes towards [0093]
S.sub.t,l,adjusted.sup.people,r|.sub.without cross-training: The
adjusted (people) availability of resource type, r, at time, t, in
location, l, when there is no cross-training policy in place.
[0094] The present invention is capable of estimating the
availability of resources in cases where there exist dependencies
between the resources being estimated. For example, the
availability of resource type "siteopen" may further depend on the
availability of human resources with specific job role of "facility
operations".
[0095] In this case, additional user-input policy parameters
include, without limitation: [0096] f: Min Facility Operations
threshold. This is the minimum number of Human Resource with job
role "facility operations" that must be available for site to open.
To calculate the availability of "siteopen" the availability of the
facility operations resource is calculated first. Let
Y.sub.t,l,adjusted.sup.facility-operations represent the adjusted
availability of human resource type "facility operations". It is
calculated according to the present invention described above for
human resources. The adjusted availability of the siteopen resource
for a site in location l in time period t may be given by [0097]
S.sub.t,l,adjusted.sup.site-open=1, if .eta.<=X.sub.a,l,t, and
Y.sub.t,l,adjusted.sup.facility-operations>=f and [0098]
S.sub.t,l,adjusted.sup.site-open=0, otherwise. This example
illustrates a specific example of how the invention calculates
resource availability when the resource depends on another
resource. Resources which do not depend on other resources are
called independent resources. Resources which depend on other
resources are called dependent resources. To effectively estimate
availability of all the resources, the supply model is first
invoked on the independent resources. The output of the supply
model on the independent resources is then fed in as input to the
supply model on the dependent resources.
[0099] Thus, according to the present invention, there is provided
a method, a system, and a machine-readable medium with instructions
for a computer or other data processing apparatus to estimate the
availability of one or more business resources in the event of a
crisis or other disruption, by: [0100] Receiving as input a
forecast and/or forecast data of business resource availability
under baseline conditions and a data set of parameter values
representing, for example, one or a plurality of business policies,
crisis severity, human factors and resource dependencies; [0101]
Determining a corrected forecast of business resource availability
to account for an impact of a disruption by taking into account
change in the availability of one or more resources accounted for
in conventional business planning processes due to said disruption
and change in the availability of one or more resources not
accounted for in conventional business planning processes due to
said disruption; and [0102] Providing the corrected forecast of
business resource availability as output. The disruption or crisis
may or may not be an epidemiological crisis. Examples of resources
that may typically be accounted for in the business planning
processes may or may not include raw materials, machinery and/or
human resources. Examples of resources that are typically not
accounted for in said business planning processes may or may not
include, without limitation: [0103] Network connectivity and/or
other utilities [0104] Clean water and electricity [0105] Roads
[0106] Maritime port and shipping capacity [0107] Air travel
capacity [0108] Air freight capacity [0109] Global logistics hubs
[0110] Site/facility access and/or [0111] Availability of human
resources belonging to a firm's suppliers and/or partners. The
correction of the forecast to account for the potential impact of a
crisis or disruption may further take into account dependencies
between resources accounted for in conventional business planning
processes and resources that are not accounted for in conventional
business planning processes. The corrected resource availability
forecast may also take into account any potential changes in
available resources due to the effects of one or more mitigation
policies. Input may be provided for one or more geographic
locations and/or one or more time periods, taking into account any
dependencies between locations and time periods.
[0112] Referring now to the drawings, and more particularly to FIG.
1, there is shown a set of crisis parameters 101 being used as
input by a supply calculator 110, which also receives data
concerning baseline resource availability 102 and mitigation
policies 103. The supply calculator 110 produces an adjusted
resource availability 120, which is used as input by a resource
interdependency calculator 130, which receives a capacity
calculating function for determining resource availability as a
function of interactions of resource types 109. Finally, the
resource interdependency calculator 130 produces output in the form
of crisis-impacted resource availability 190 to be used in supply
chain or other business planning.
[0113] FIG. 2 shows a system configured according to the present
invention. A computer 200 with a machine-readable medium 201
containing machine-readable instructions 202 for the computer 200
to receive a baseline business resource availability forecast as
input and to provide a forecast corrected for crisis conditions as
output. Said computer 200 receives operator instructions via a
keyboard 210. The computer 200 obtains the baseline business
resource availability forecast data via a network 230, either
directly from databases 250a, 250b, 250c or from a server 240
obtaining the baseline business resource availability forecast data
from databases 250a, 250b, 250c. The computer 200 then corrects the
firm's baseline business resource availability forecast data to
account for the impact of a crisis and provides a forecast
corrected for crisis conditions as output either in human-readable
format via a computer screen 221 or printer 225 or in
machine-readable format over the network 230 as input to the server
240.
[0114] FIG. 3 shows a sample output assessing the effect of a
crisis on supply according to the present invention.
[0115] While the invention has been described in terms of its
preferred embodiments, those skilled in the art will recognize that
the invention can be practiced with modification within the spirit
and scope of the appended claims.
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