03.11.04
 By Tom Pisello and Bill Quirk
Quantifying the cost of downtime can help you gain funding for technologies
that enhance performance and mitigate downtime risks. Yet most organizations
have a difficult time calculating the losses associated with downtime
because of its complexity.
Sometimes, downtime can cause a loss of productivity for a single
user or a workgroup. Other times, the scope is more serious and affects
a core application, business process or department, such as a call
center or brokerage desk.
Duration is also a critical factor. A loss of a few minutes to an
individual or group easily can be made up if employees stay late,
but when downtime stretches to hours or days, the loss is more permanent.
Whenever downtime impairs business transactions, the length of the
outage carries serious consequences. Transactions might be queued
automatically during short periods of unavailability, or perhaps clients
will call back. But when the event lasts hours, transactions can be
invalidated or clients permanently lost. |
To
quantify downtime there are two primary factors: productivity losses
and business losses. Productivity losses affect individual or workgroup
productivity, while business losses affect transactions or cause customer
losses. Calculating both reveals wasted expenses and lost revenue.
For productivity losses, calculate the downtime based on the effect
to users - usually using burdened salary figures. Burdened salary
includes user compensation, estimated at $24 per user per hour in
the U.S., plus the burden of taxes and benefits, typically 26% or
higher than the base salary, according to U.S. Department of Labor.
The downtime productivity loss calculation is typically represented
as:
Number of users affected multiplied by the percent effect on productivity
multiplied by the average burdened salary per hour multiplied by the
duration of downtime equals downtime impact.
For business applications or groups, the calculations become more
difficult. There are two basic methods for the business impact calculation:
Number of users affected multiplied by the percent effect on productivity
multiplied by the average profit per employee hour multiplied by the
duration of downtime equals downtime impact.
Number of transactions per hour multiplied by the percent of affected
transactions multiplied by the average profit per transaction multiplied
by the duration of downtime equals downtime impact.
Consider this real-world example that illustrates the effect of downtime.
Accidental changes to Active Directory brought down Internet access
for a large financial services firm's trading desk. As users logged
on, they could not access vital information or mission-critical applications.
Some users who had not logged off the previous day were not immediately
affected. However, as the policies refreshed, more users became subject
to the errant Internet settings.
As a result, the service desk received increasing numbers of calls
during the day as the propagation of the unintended change increased.
After eight hours, the problem was traced to an accidental change
made by the Active Directory administrator, and the proper settings
were restored. The trading desk was affected, and this incident cost
the company millions of dollars in productivity and lost business.
To justify best practices, tools or infrastructure that help reduce
the risk of snafus that affect availability use a probability equation
similar to insurance risk analysis. To predict the effect, estimate
the probability that one of the risks will be realized, and estimate
how long the downtime will be. The downtime costs can be predicted
as:
Predicted downtime costs equal probability of event (percent) multiplied
by the estimated duration in hours if the event occurs multiplied
by the cost per downtime hour.
Once the predicted downtime costs for all the various types of scenarios
are estimated, the cost of the people, process and technology improvement
to reduce the downtime risk can be compared against the probability
and cost of the risks to help justify the solution and assure that
benefits can be derived from the assurance investment.
System ups and downs
By decreasing downtime, IT departments could reduce productivity losses
by millions of dollars.
About the Author:
Pisello is president and CEO of Alinean, a consultancy that helps
clients assess and articulate the business value of IT investments.
Quirk is consumer relations director of enterprise management software
vendor Full Armor. They can be reached at tpisello@alinean.com
and bquirk@fullarmor.com.
Read this newsletter at: http://www.itmanagementnews.com/2004/0311.html |
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