IMPUTED AVAILABILITY MODEL
Publication Date: 2017-Mar-28
The IP.com Prior Art Database
Xi Gong: AUTHOR [+3]
A resource's relative availability is imputed using historical data instead of relying on a human's assertion of availability. This is a statistical model used to aid a decision support system.
Copyright 2017 Cisco Systems, Inc. 1
IMPUTED AVAILABILITY MODEL
AUTHORS: Xi Gong
Ryan LaFountain Tom Willingham
CISCO SYSTEMS, INC.
A resource's relative availability is imputed using historical data instead of relying
on a human's assertion of availability. This is a statistical model used to aid a decision
Optimizing resource utilization has always been a goal of customer contact business
operations. However, problems exist with regard to accurately determining resource
availability. This may be caused by human behavior or the inability of current systems to
determine relative, instead of binary, availability.
Many systems that route work to resources rely on some measure of resource
availability, typically allowing the resource to assert availability in a binary way. For
example, a call center agent may tell the system that he or she is ‘available’ or ‘unavailable’
for new work. However, problems arise when this human asserted availability is inaccurate.
For instance, if an agent forgets to tell the system he or she is ‘unavailable,’ customer calls
may continue to be routed to this off shift agent.
Furthermore, when relying solely on asserted availability, resources may be
determined to be equally available/unavailable. In reality, resources working on multiple
pieces of work at once, with pieces of work taking varying times complete, have not binary,
but relative, availability. For example, a call center agent may be working on a greater
number of tasks that take a longer amount of time to complete than a peer agent. A system
with only a basic understanding of binary availability may see these agents as equally
available and route a new piece of work to the agent who is less available.
As such, the techniques described herein impute a resource’s relative availability
using historical data instead of relying on a human’s assertion of availability. They use a
statistical model to aid a decision support system in determining a resource’s availability
Copyright 2017 Cisco Systems, Inc. 2
by determining (1) a confidence factor for a resource’s asserted availability (i.e., how much
should the system trust a resource’s assertion that they are available or unavailable?); and
(2) a comparative probability that a resource is available for a new piece of work (i.e., how
available is a resource compared to that resource’s peers?).
This system uses probability models and k-means clustering techniques to enhance
its understanding of resource availability. Conventionally, a resource must tell the system
he or she is ‘available’ or ‘unavailable’. By contrast, this system may impute the confidence
of the human asserted binary availability and may also predict when a resource is
comparatively available to his or her peers to accept a piece of work. The entire system
may include two core components: (1) Availability Regeneration Function (Yo-yo
function), and (2) Profile Usage Change Reliability (PUCR). The firs...