Schneier: Security ROI - it is mostly bunk

ROI is a big deal among IT security vendors but end users shouldn't trust their calculations

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Return on investment, or ROI, is a big deal in business. Any business venture needs to demonstrate a positive return on investment, and a good one at that, in order to be viable.

It's become a big deal in IT security, too. Many corporate customers are demanding ROI models to demonstrate that a particular security investment pays off. And in response, vendors are providing ROI models that demonstrate how their particular security solution provides the best return on investment.

It's a good idea in theory, but it's mostly bunk in practice.

Before I get into the details, there's one point I have to make. "ROI" as used in a security context is inaccurate. Security is not an investment that provides a return, like a new factory or a financial instrument. It's an expense that, hopefully, pays for itself in cost savings. Security is about loss prevention, not about earnings. The term just doesn't make sense in this context.

But as anyone who has lived through a company's vicious end-of-year budget-slashing exercises knows, when you're trying to make your numbers, cutting costs is the same as increasing revenues. So while security can't produce ROI, loss prevention most certainly affects a company's bottom line.

And a company should implement only security countermeasures that affect its bottom line positively. It shouldn't spend more on a security problem than the problem is worth. Conversely, it shouldn't ignore problems that are costing it money when there are cheaper mitigation alternatives. A smart company needs to approach security as it would any other business decision: costs versus benefits.

The classic methodology is called annualised loss expectancy (ALE), and it's straightforward. Calculate the cost of a security incident in both tangibles like time and money, and intangibles like reputation and competitive advantage.

Multiply that by the chance the incident will occur in a year. That tells you how much you should spend to mitigate the risk. So, for example, if your store has a 10 percent chance of getting robbed and the cost of being robbed is US$10,000, then you should spend $1,000 a year on security. Spend more than that, and you're wasting money. Spend less than that, and you're also wasting money.

Of course, that $1,000 has to reduce the chance of being robbed to zero in order to be cost-effective. If a security measure cuts the chance of robbery by 40 percent-to 6 percent a year-then you should spend no more than $400 on it. If another security measure reduces it by 80 percent, it's worth $800. And if two security measures both reduce the chance of being robbed by 50 percent and one costs $300 and the other $700, the first one is worth it and the second isn't.

The Data Imperative

The key to making this work is good data; the term of art is "actuarial tail." If you're doing an ALE analysis of a security camera at a convenience store, you need to know the crime rate in the store's neighbourhood and maybe have some idea of how much cameras improve the odds of convincing criminals to rob another store instead.

You need to know how much a robbery costs: in merchandise, in time and annoyance, in lost sales due to spooked patrons, in employee morale. You need to know how much not having the cameras costs in terms of employee morale; maybe you're having trouble hiring salespeople to work the night shift.

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