It’s time to stop seeing IT as just a black hole to throw money towards and instead, give back to the business. Often, the lack of proper measurement and standardization are the problem, so how do we address this?

 

We’ve all tried to leverage more funds from the organization to undertake a project. Whether replacing aging hardware or out-of-support software, without the business seeing the value the IT department brings, it’s hard to obtain the financing required. That’s because the board typically sees IT as a cost center.

 

A cost center is defined as a department within a business not directly adding profit, but still requiring money to run. A profit center is the inverse, whereby its operation directly adds to overall company profitability.

 

But how can you get there? You need to understand everything the IT department does is a process, and thereby can be measured and thus improved upon. Combining people and technology, along with other assets, and passing them through a process to deliver customer success or business results is a strategic outcome you want to enhance. If you can improve the technology and processes, then you’ll increase the strategic outcomes.

 

By measuring and benchmarking these processes, you can illustrate the increases made due to upgrades. Maybe a web server can now support 20% more traffic, or its loading latency has been reduced by four seconds, which over a three-month period has led to an increase of 15% web traffic and an 8% rise in sales. While I’ve just pulled these figures from the air, the finance department evaluates spending and can now see a tangible return on the released funds. The web server project increased web traffic, sales, and therefore profits. When you approach the next project you want to undertake, you don’t have to just say “it’s faster/newer/bigger than our current system” (although you should add to your discussion the faster, newer, bigger piece of hardware or software will provide an improvement to the overall system). However, without data, you have no proof, and the proof is in the pudding, as they say. Nothing will make a CFO happier than seeing a project with milestones and KPIs (well, maybe three quarters exceeding predictions). So, how do we measure and report all these statistics?

 

If you think of deployments in terms of weeks or months, you’re trying to deploy something monolithic yet composed of many moving and complex parts. Try to break this down. Think of it like a website. You can update one page without having to do the whole site. Then you start to think “instead of the whole page, what about changing a .jpg, or a background?” Before long, you’ve started to decouple the application at strategic points, allowing for independent improvement. At this stage, I’d reference the Cloud Native Computing Foundation Trail Map as a great way to see where to go. Their whole ethos on empowering organizations running modern scalable applications can help you with transformation.

 

But we’re currently looking at the measurement aspect of any application deployment. I’m not just talking about hardware or network monitoring, but a method of obtaining baselines and peak loads, and of being able to predict when a system will reach capacity and how to react to it.

 

Instead of being a reactive IT department, you suddenly become more proactive. Being able to assign your ticketing system to your developers allows them to react faster to any errors from a code change and quickly fix the issue or revert to an earlier deployment, thereby failing quickly and optimizing performance.

 

I suggest if you’re in charge of an application or applications, or support one on a daily basis, start to measure and record anywhere you can on the full stack. Understand what normal looks like, or how it’s different from “rush hour,” so you can say with more certainty it’s not the network. Maybe it’s the application, or it’s the DNS (it’s always DNS) leading to delays, lost revenue, or worse, complete outages. Prove to the naysayers in your company you have the correct details and that 73.6% of the statistics you present aren’t made up.