5 SLA metrics you should be monitoring

In
business
and
beyond,
communication
is
king.
Successful
service
level
agreements
(SLAs)
operate
on
this
principle,
laying
the
foundation
for
successful
provider-customer
relationships.

A

service
level
agreement
(SLA)
is
a
key
component
of
technology
vendor
contracts
that
describes
the
terms
of
service
between
a
service
provider
and
a
customer.
SLAs
describe
the
level
of
performance
to
be
expected,
how
performance
will
be
measured
and
repercussions
if
levels
are
not
met.
SLAs
make
sure
that
all
stakeholders
understand
the
service
agreement
and
help
forge
a
more
seamless
working
relationship.

Types
of
SLAs

There
are
three
main
types
of
SLAs:

Customer-level
SLAs

Customer-level
SLAs
define
the
terms
of
service
between
a
service
provider
and
a
customer.
A
customer
can
be
external,
such
as
a
business
purchasing
cloud
storage
from
a
vendor,
or
internal,
as
is
the
case
with
an
SLA
between
business
and
IT
teams
regarding
the
development
of
a
product.

Service-level
SLAs

Service
providers
who
offer
the
same
service
to
multiple
customers
often
use
service-level
SLAs.
Service-level
SLAs
do
not
change
based
on
the
customer,
instead
outlining
a
general
level
of
service
provided
to
all
customers.

Multilevel
SLAs

When
a
service
provider
offers
a
multitiered
pricing
plan
for
the
same
product,
they
often
offer
multilevel
SLAs
to
clearly
communicate
the
service
offered
each
level.
Multilevel
SLAs
are
also
used
when
creating
agreements
between
more
than
two
more
parties.

SLA
components

SLAs
include
an
overview
of
the
parties
involved,
services
to
be
provided,
stakeholder
role
breakdowns,
performance
monitoring
and
reporting
requirements.
Other
SLA
components
include
security
protocols,
redressing
agreements,
review
procedures,
termination
clauses
and
more.
Crucially,
they
define
how
performance
will
be
measured.

SLAs
should
precisely
define
the
key
metrics—service-level
agreement
metrics—that
will
be
used
to
measure
service
performance.
These
metrics
are
often
related
to
organizational

service
level
objectives
(SLOs).
While
SLAs
define
the
agreement
between
organization
and
customer,
SLOs
set
internal
performance
targets.
Fulfilling
SLAs
requires
monitoring
important
metrics
related
to
business
operations
and
service
provider
performance.
The
key
is
monitoring
the
right
metrics.

What
is
a
KPI
in
an
SLA?

Metrics
are
specific
measures
of
an
aspect
of
service
performance,
such
as
availability
or

latency.
Key
performance
indicators
(KPIs)
are
linked
to
business
goals
and
are
used
to
judge
a
team’s
progress
toward
those
goals.
KPIs
don’t
exist
without
business
targets;
they
are
“indicators”
of
progress
toward
a
stated
goal.

Let’s
use
annual
sales
growth
as
an
example,
with
an
organizational
goal
of
30%
growth
year-over-year.
KPIs
such
as
subscription
renewals
to
date
or
leads
generated
provide
a
real-time
snapshot
of
business
progress
toward
the
annual
sales
growth
goal.

Metrics
such
as
application
availability
and
latency
help
provide
context.
For
example,
if
the
organization
is
losing
customers
and
not
on
track
to
meet
the
annual
goal,
an
examination
of
metrics
related
to
customer
satisfaction
(that
is,
application
availability
and
latency)
might
provide
some
answers
as
to
why
customers
are
leaving.

What
SLA
metrics
to
monitor

SLAs
contain
different
terms
depending
on
the
vendor,
type
of
service
provided,
client
requirements,
compliance
standards
and
more
and
metrics
vary
by
industry
and
use
case.
However,
certain
SLA
performance
metrics
such
as
availability,
mean
time
to
recovery,
response
time,
error
rates
and
security
and
compliance
measurements
are
commonly
used
across
services
and
industries.
These
metrics
set
a
baseline
for
operations
and
the
quality
of
services
provided.

Clearly
defining
which
metrics
and
key
performance
indicators
(KPIs)
will
be
used
to
measure
performance
and
how
this
information
will
be
communicated
helps

IT
service
management
(ITSM)
teams
identify
what
data
to
collect
and
monitor.
With
the
right
data,
teams
can
better
maintain
SLAs
and
make
sure
that
customers
know
exactly
what
to
expect.

Ideally,
ITSM
teams
provide
input
when
SLAs
are
drafted,
in
addition
to
monitoring
the
metrics
related
to
their
fulfillment.
Involving
ITSM
teams
early
in
the
process
helps
make
sure
that
business
teams
don’t
make
agreements
with
customers
that
are
not
attainable
by
IT
teams.

SLA
metrics
that
are
important
for
IT
and
ITSM
leaders
to
monitor
include:

1.
Availability

Service
disruptions,
or
downtime,
are
costly,
can
damage
enterprise
credibility
and
can
lead
to
compliance
issues.
The
SLA
between
an
organization
and
a
customer
dictates
the
expected
level
of
service
availability
or
uptime
and
is
an
indicator
of
system
functionality.

Availability
is
often
measured
in
“nines
on
the
way
to
100%”:
90%,
99%,
99.9%
and
so
on.
Many
cloud
and
SaaS
providers
aim
for
an
industry
standard
of
“five
9s”
or
99.999%
uptime.

For
certain
businesses,
even
an
hour
of
downtime
can
mean
significant
losses.
If
an
e-commerce
website
experiences
an
outage
during
a
high
traffic
time
such
as
Black
Friday,
or
during
a
large
sale,
it
can
damage
the
company’s
reputation
and
annual
revenue.
Service
disruptions
also
negatively
impact
the
customer
experience.
Services
that
are
not
consistently
available
often
lead
users
to
search
for
alternatives.
Business
needs
vary,
but
the
need
to
provide
users
with
quick
and
efficient
products
and
services
is
universal.

Generally,
maximum
uptime
is
preferred.
However,
providers
in
some
industries
might
find
it
more
cost
effective
to
offer
a
slightly
lower
availability
rate
if
it
still
meets
client
needs.

2.
Mean
time
to
recovery

Mean
time
to
recovery
measures
the
average
amount
of
time
that
it
takes
to
recover
a
product
during
an
outage
or
failure.
No
system
or
service
is
immune
from
an
occasional
issue
or
failure,
but
enterprises
that
can
quickly
recover
are
more
likely
to
maintain
business
profitability,
meet
customer
needs
and
uphold
SLAs.

3.
Response
time
and
resolution
time

SLAs
often
state
the
amount
of
time
in
which
a
service
provider
must
respond
after
an
issue
is
flagged
or
logged.
When
an
issue
is
logged
or
a
service
request
is
made,
the
response
time
indicates
how
long
it
takes
for
a
provider
to
respond
to
and
address
the
issue.
Resolution
time
refers
to
how
long
it
takes
for
the
issue
to
be
resolved.
Minimizing
these
times
is
key
to
maintaining
service
performance.

Organizations
should
seek
to
address
issues
before
they
become
system-wide
failures
and
cause
security
or
compliance
issues.
Software
solutions
that
offer
full-stack
observability
into
business
functions
can
play
an
important
role
in
maintaining
optimized
systems
and
service
performance.
Many
of
these
platforms
use

automation
and

machine
learning
(ML)
tools
to
automate
the
process
of
remediation
or
identify
issues
before
they
arise.

For
example,

AI-powered
intrusion
detection
systems
(IDS)
constantly
monitor

network
traffic
for
malicious
activity,
violations
of
security
protocols
or
anomalous
data.
These
systems
deploy
machine
learning
algorithms
to
monitor
large
data
sets
and
use
them
to
identify
anomalous
data.
Anomalies
and
intrusions
trigger
alerts
that
notify
IT
teams.
Without
AI
and
machine
learning,
manually
monitoring
these
large
data
sets
would
not
be
possible.
 

4.
Error
rates

Error
rates
measure
service
failures
and
the
number
of
times
service
performance
dips
below
defined
standards.
Depending
on
your
enterprise,
error
rates
can
relate
to
any
number
of
issues
connected
to
business
functions.

For
example,
in
manufacturing,
error
rates
correlate
to
the
number
of
defects
or
quality
issues
on
a
specific
product
line,
or
the
total
number
of
errors
found
during
a
set
time
interval.
These
error
rates,
or
defect
rates,
help
organizations
identify
the
root
cause
of
an
error
and
whether
it’s
related
to
the
materials
used
or
a
broader
issue.

There
is
a
subset
of
customer-based
metrics
that
monitor
customer
service
interactions,
which
also
relate
to
error
rates.

• 
  First
  call
  resolution
  rate:
  In
  the
  realm
  of
  customer
  service,
  issues
  related
  to
  help
  desk
  interactions
  can
  factor
  into
  error
  rates.
  The
  success
  of
  customer
  services
  interactions
  can
  be
  difficult
  to
  gauge.
  Not
  every
  customer
  fills
  out
  a
  survey
  or
  files
  a
  complaint
  if
  an
  issue
  is
  not
  resolved—some
  will
  just
  look
  for
  another
  service.
  One
  metric
  that
  can
  help
  measure
  customer
  service
  interactions
  is
  the
  first
  call
  resolution
  rate.
  This
  rate
  reflects
  whether
  a
  user’s
  issue
  was
  resolved
  during
  the
  first
  interaction
  with
  a
  help
  desk,
  
  chatbot
  or
  representative.
  Every
  escalation
  of
  a
  customer
  service
  query
  beyond
  the
  initial
  contact
  means
  spending
  on
  extra
  resources.
  It
  can
  also
  impact
  the
  customer
  experience.
• 
  Abandonment
  rate:
  This
  rate
  reflects
  the
  frequency
  in
  which
  a
  customer
  abandons
  their
  inquiry
  before
  finding
  a
  resolution.
  Abandonment
  rate
  can
  also
  add
  to
  the
  overall
  error
  rate
  and
  helps
  measure
  the
  efficacy
  of
  a
  
  service
  desk,
  chatbot
  or
  human
  workforce.

5.
Security
and
compliance

Large
volumes
of
data
and
the
use
of
on-premises
servers,

cloud
servers
and
a
growing
number
of
applications
creates
a
greater
risk
of

data
breaches
and
security
threats.
If
not
monitored
appropriately,
security
breaches
and
vulnerabilities
can
expose
service
providers
to
legal
and
financial
repercussions.

For
example,
the
healthcare
industry
has
specific
requirements
around
how
to
store,
transfer
and
dispose
of
a
patient’s
medical
data.
Failure
to
meet
these
compliance
standards
can
result
in
fines
and
indemnification
for
losses
incurred
by
customers.

While
there
are
countless
industry-specific
metrics
defined
by
the
different
services
provided,
many
of
them
fall
under
larger
umbrella
categories.
To
be
successful,
it
is
important
for
business
teams
and
IT
service
management
teams
to
work
together
to
improve
service
delivery
and
meet
customer
expectations.

Benefits
of
monitoring
SLA
metrics

Monitoring
SLA
metrics
is
the
most
efficient
way
for
enterprises
to
gauge
whether
IT
services
are
meeting
customer
expectations
and
to
pinpoint
areas
for
improvement.
By
monitoring
metrics
and
KPIs
in
real
time,
IT
teams
can
identify
system
weaknesses
and
optimize
service
delivery.

The
main
benefits
of
monitoring
SLA
metrics
include:

Greater
observability

A
clear
end-to-end
understanding
of
business
operations
helps
ITSM
teams
find
ways
to
improve
performance.
Greater

observability
enables
organizations
to
gain
insights
into
the
operation
of
systems
and
workflows,
identify
errors,
balance

workloads
more
efficiently
and
improve
performance
standards.

Optimized
performance

By
monitoring
the
right
metrics
and
using
the
insights
gleaned
from
them,
organizations
can
provide
better
services
and
applications,
exceed
customer
expectations
and
drive
business
growth.

Increased
customer
satisfaction

Similarly,
monitoring
SLA
metrics
and
KPIs
is
one
of
the
best
ways
to
make
sure
services
are
meeting
customer
needs.
In
a
crowded
business
field,
customer
satisfaction
is
a
key
factor
in
driving
customer
retention
and
building
a
positive
 reputation.

Greater
transparency

By
clearly
outlining
the
terms
of
service,
SLAs
help
eliminate
confusion
and
protect
all
parties.
Well-crafted
SLAs
make
it
clear
what
all
stakeholders
can
expect,
offer
a
well-defined
timeline
of
when
services
will
be
provided
and
which
stakeholders
are
responsible
for
specific
actions.
When
done
right,
SLAs
help
set
the
tone
for
a
smooth
partnership.

Understand
performance
and
exceed
customer
expectations

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