At what point is the survival of your company at risk? 40% said 72 hours, 21% said 48 hours, 15% said 24 hours, 8% said 8 hours, 9% said 4 hours, 3% said 1 hour, 4% said within the hour. (Source: 2006 Cost of Downtime Survey Results, 2006.)

How to quantify downtime

 Calculating downtime's drag on productivity and profit can help make the case for network improvements. 

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.  

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.