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Mention the words “open source” and all kinds ideas probably come to mind such as “free”, “agility”, and “speed”. However, with any IT project, it is important to look at business benefits vs. costs in a manner that goes beyond generalizations. One method for benefit-cost analysis for open source big data projects is Net Present Value (NPV).

It’s not unusual to find the IT community excited about the possibilities of open source. And with good reason as adoption of open source big data technologies may provide companies flexibility in charting their own path, ability to innovate faster and move at the speed of business. And yet, it is sage advice to temper some of the frenzy in adopting open source with a financial analysis.

There are plenty of methods to justify an IT project. They range from simple payback to the more complex such as calculating the present value of cash flows. Financial managers use NPV to see if a project will ultimately bring in more money than it costs. NPV is also used to rank projects in priority order when there are competing alternatives.

What exactly is NPV? Investopedia’s definition follows: “Net Present Value (NPV) is the difference between the present value of cash inflows and the present value of cash outflows.” To start an NPV analysis, you will need to determine three things:

• Initial outlay
• Incremental cash flows (for the useful life of the project)
• Cost of capital

The initial outlay is probably not too difficult to find. It’s essentially money needed to get the project started. The corporate cost of capital can be ascertained by asking your corporate finance professional for his/her best estimate (I don’t recommend trying to calculate your company’s cost of capital unless you’re a glutton for punishment—that’s better left to the finance folks).

Now to the tricky part; the incremental cash flows, or “cash” that’s going to come into the business from your big data open source project.

Here’s the process: determine your best estimate for incoming revenues from the proposed project and then subtract out incremental costs including potentially higher utilities as a result of your big data project, additional training, additional overhead and/or salaries, ongoing application maintenance, enterprise support fees, and depreciation (if you’re buying an appliance or commodity hardware). Then subtract out taxes, add depreciation back in, and add in any salvage value of computer equipment if purchased specifically for your project.

This article was originally published on www.forbes.com and can be viewed in full

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