Anyone in a technology organization can relate to a certain frustration. You know that adopting a certain tool or practice would help you. So you charge forward with the initiative, looking for approval. But then someone — a superior most likely — asks you to justify it. “Give me the business case for it,” they say. And then, flummoxed a little, the gears start turning in your head. Today, I’d like to talk about that very issue in the specific context of log analysis tools.
If you have significant operations of any kind in production, you’re almost certainly generating logs. If not, you should be. You’re also probably monitoring those logs, in some fashion or another. And if you’re consuming them, you’re analyzing them in some fashion or another. But maybe you’re doing this manually, and you’d rather use a tool for log analysis. How do you justify adopting that tool? How do you justify paying for it?
ROI: The Basic Idea
To do this, you have to veer into the world of business and entrepreneurship for a moment. But don’t worry — you’re not veering too far into that world. Just far enough to acquire a skill that any technologist ought to have.
I’m talking about understanding the idea of return on investment (ROI). Follow the link and you’ll see a formula, but the idea is really dead simple. If you’re going to pay for something, will that something bring you as much or more value than what you paid? When the answer is “yes,” then you have a justifiable decision. If the answer is “no,” then you can’t make a good case for the investment.
So, for log analysis tools, the question becomes a pretty straightforward one. Will your group realize enough cost savings or additional revenue generation from the tool to justify its cost?
Employing Back-of-the-Napkin Math
When you’re asked to justify purchasing a tool, you might wonder how much rigor you must bring to bear. People working with technology tend to have an appreciation for objective, empirical data.
When making a business case, if you can back it with objective, empirical data, that’s great. You should absolutely do so. But that’s often hard because it involves making projections and generally reasoning about the future. We humans like to believe we’re good at this, but if that were true, we’d all be rich from playing the stock market.
So you need to make some assumptions and build your case on the back of those assumptions. People sometimes refer to that as “back-of-the-napkin math” and it’s a perfectly fine way to build a business case, provided you highlight the assumptions that you make.
For instance, let’s say that I wanted to spend $50 on a text editor. I might project that its feature set would save me 20 minutes per day of brainless typing. I’d highlight that assumption and say that, if true, the investment would pay off after less than a week, given my current salary. These are the sorts of arguments that bosses and business folks appreciate.
First, the Cost of Log Analysis Tools
To make a business case and a credible projection of ROI, you need two projected pieces of data: the cost (i.e., the amount of the investment you’re looking for a return on) and the savings or revenue benefit. I’ll dedicate the rest of this post to talking about how log analysis tools can save companies money or even add to their bottom line. But first, let’s take a look at their costs.
The most obvious cost is the sticker price of the tool. That might be an initial lump sum, but in this day and age, it’s usually going to be a recurring monthly subscription cost. So when making your case, be sure to take that into account.
There’s also a second, subtler cost that you should prepare yourself to address. Installing, learning, and managing the tools takes time from someone in the IT organization. You can (and should) argue that it winds up saving time in the end, but you also must acknowledge that investing employee time (and thus salary) is required.
Once you have those costs established, you can start to reason about the benefits.