By Bob Webb
Vice president of sales
Pipkins Inc.
Making an Accurate Call
The wrong staffing of a contact center can dent a mortgage company’s profitability
in today’S tough economic timeS
and dwindling profits, it is more important than ever for mortgage brokerage
companies to ensure they are getting
maximum benefit from software investments. One of the biggest threats to a
mortgage company’s call-center profit
margin is wasted labor expense due to
inaccurate forecasting.
Staffing operational costs account for
70 to 80 percent of a call center’s budget
and can be severely impacted by under-or overstaffing. Accurate forecasting is
the foundation of scheduling, and without it, wrong staffing can impact the
profitability of a contact center.
How? In a real-life scenario, if the
call volume is underestimated to the
extent that 100 callers out of 1,000
hang up before they speak to an agent
in a sales environment, and if the average order is just $50, then $5,000
of revenues will be lost per day, adding up to approximately $150,000
per month and $1.8 million per year.
Translate these figures to a mortgage-company environment, and the results
could be staggering.
billing cycles or other variables that
can affect call volume.
4. algorithms that include curve mapping and pattern recognition: In
variable environments, historical
trend analysis is the only way to ensure proper staffing. It is the only
methodology that can incorporate
complex historical trends in its calculations. Without pattern matching
to predict customer behavior for different events, the risk of over- or understaffing increases dramatically.
• forecasting too high: You have too
many agents scheduled. In this scenario, your company can lose money
as a result of low occupancy, agents
getting distracted or bored, and poor
agent morale and quality of work.
• forecasting too low: You have too
few agents scheduled. This also can
cost your company money because
of poor customer service and long
wait times. Your agents also will be
overworked, which will lead to low
morale and poor quality of work.
business activity, competitor activity,
weather issues, or external factors
(TV shows, sporting events, industrial actions and so on). The lifespan
and seasonal trends of each type of
event should be given consideration.
• correlating events: In the example of
mail or catalog drops, similar events
may occur on several occasions, but
will affect work differently based on
the number of letters delivered. The
system must have the capacity to identify and weigh these events appropriately to plan for future occurrences.
“Staffing operational costs
account for 70 to 80 percent
of a call center’s budget and
can be severely impacted
Methodology
Providing the required accuracy is a
task that demands a sophisticated
forecasting tool, one that accounts for
myriad historic and future dynamics.
No single methodology is optimal for
all circumstances. Four factors should
be taken into consideration, however.
1. correlated forecasting: Only the
most-sophisticated systems can
perform correlated forecasting
— that is, forecasting for specific
events such as catalog drops or
other marketing events that cause
wide fluctuations in the volume of
calls that must be processed.
2. integrated approach to support
multiskilled issues: It is necessary
to have forecasting algorithms that
calculate requirements in a multiskilled environment directly, while
avoiding repetitive analytical simulations. A single-forecasted set of
requirements should be generated
for all interwoven-skilled activities,
regardless of the type of work being
offered. Recognizing secondary skills
and accounting for call overflow to
available secondarily skilled agents
will help eliminate overstaffing.
3. collecting enough historical data:
It is imperative to maintain detailed
data for several years in order to
produce an accurate forecast. Many
workforce-scheduling systems store
no more than 16 weeks of historical inbound-call data to generate a
forecast, and most fail to gather information on marketing campaigns,
by under- or overstaffing.”
Historical trend analysis also incorporates pattern recognition for
special events like promotional
mailings. Each time an event reoccurs, the forecasted volume is
adjusted to reflect the increase or
decline in incoming work, based on
past occurrences.
Forecasting tools
When you’re selecting a forecasting
tool, keep these tips in mind to maximize accuracy.
1. beware of averages: While forecasting averages is a safe bet, it is not
likely to be the most accurate.
2. give the forecaster some data: The
more data, the better. If the tool
cannot process more than a few
weeks of data, its accuracy will be
compromised.
3. have realistic expectations: The
tool’s predictions can only be based
on what has happened historically
and on what it is told will happen in
the future.
4. understand how your forecasting
tool works: This is in terms of the
volume of data it can store, how
it recognizes seasonal trends and
special events information, etc.
The key is to ensure that the forecasting tool has as much information as
possible about what happened in the
past and what you expect in the future,
and that it will allow you to input this
information and make proper use of it.
Variability and predictability
The volume of work flowing into a
mortgage-company contact center — in
the form of calls, e-mails and so on — is
quite variable. Some even may consider
it unpredictable. Indeed, if we look at a
history of work arriving in a typical contact center, this belief may appear to
be true. The volume of work changes
throughout the day, from one day to the
other and week over week, which may
give the impression that it is impossible
to accurately forecast future work.
In reality, using the right tools can
help eliminate unpredictability. Variability should not be confused with unpredictability. Once you take charge of
the predictable load — which is much
of the workflow in itself — you’ll be able
to avoid the consequences of inaccurate forecasting.
The risk of the understaffing is that
a high number of callers may abandon
you and possibly go elsewhere; you
simply end up losing business. This
amount of lost revenue can be significant, particularly in a sales environment. Consider the average revenue
generated per sales call — then multiply this by the number of abandoned
calls that you recorded last month. The
answer would probably justify the cost
of a good forecasting tool on its own.
• • •
Mortgage companies today do not
have the luxury of making investment
mistakes. Ensuring that your work-
force-management system produces
accurate forecasts is a top priority. If
you decide to invest in a system, make
sure it can perform critical functions,
accommodate future needs, and main-
tain enough past call data to generate
accurate forecasts. •
Getting it wrong
There are two simple effects of getting
the forecast wrong:
Getting it right
A mortgage company has several ways
to make sure that its staffing is correct.
• validating historical data: New incoming data should be compared
against a previously validated set of
historical data. With the right report,
a mortgage company can easily spot
inaccurate or missing data for the
forecast tool to ignore.
• recognizing events: It is important
to recognize events that have an effect on the amount, and possibly
the pattern, of work arriving in the
contact center. For example, a look
into the data on a Thursday that precedes Good Friday should indicate a
downward trend in call volume. Besides holidays, other events may include billing cycles, mail or catalog
drops, advertising promotions, new
Bob Webb is vice president of sales for Pipkins
Inc., a worldwide supplier of workforce-management software and services to the
call-center industry. Pipkins’ Vantage Point
product lets managers solve the complicated
operational issues in today’s multifaceted call-center environment. Pipkins’ systems forecast
and schedule more than 300,000 agents in
more than 500 locations across all industries
worldwide. The company is headquartered in
St. Louis. For more information, visit pipkins.
com or call (800) 469-6106.
