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How to Use IT Metrics?
devopsMarch 2, 20264 minutos de lectura

How to Use IT Metrics?

With a massive presence of customers in the digital landscape, more and more data is available to companies. But that's where the main challenge begins: how do you get the most out of all this information?

How can you use data strategically? First of all, you need to perform an internal analysis of the company's current situation, and the objectives defined in the business strategy. At this point, it's important to consider, beyond the goals, the risks and potential failures, so that companies are prepared for various scenarios.

To manage IT, you need a macro strategic view of the company in order to understand the paths and factors that must be considered.

Methodologies for Managing IT Metrics

To manage IT metrics, several methodologies are available. Check out some of them below:

OKR

Created at Intel by Andrew Grove and popularized by Google, it is one of managers' favorite methodologies. Through resources such as Objectives and Key Results, it enables the customized definition of the objectives of the business or of a specific project.

With this, through performance indicators, it is possible to analyze whether the process is running according to the goals or not. The recommendation is that the deadline for completing the defined objectives be up to 3 months, being renewed over time according to need.

Balanced Scorecard (BSC)

Widely used for the macro management of companies, this methodology is very useful for long-term objectives. Its approach is divided into 4 perspectives:

  • Financial
  • Customers
  • Internal processes
  • Learning and growth

Objectives are defined in each of these perspectives, which are broken down into goals that can be analyzed through indicators to build the company's strategic map.

SMART

This methodology is based on a strategy built around the answers to the following questions:

  1. Is your objective specific? (Specific)
  2. Can you measure your progress toward the objective? (Measurable)
  3. Is your objective achievable? (Achievable)
  4. How relevant is the objective to the organization? (Relevant)
  5. What is the time limit for reaching the objective? (Time)

The answers will be the pillars that guide all actions within the company's strategic planning.

IT Metrics

Which metrics can I use to measure my business?

Let's divide them into two very common realities: Software Factories and SaaS:

Software Factory

A software factory is a set of resources, processes, and methodologies structured in a way similar to those of traditional industries, using best practices for software development, testing, and maintenance.

Here we can analyze through indicators based on Agile Methodologies for project management, which basically determine the profitability, speed, and productivity of the teams.

SaaS

And what if the focus is on a digital SaaS product? What is your product strategy? Some options might be increasing users, the time spent navigating your digital environments, and the level of customer satisfaction. To carry out this analysis, we can measure accesses, daily users, usability, NPS, CSAT, etc.

Here we focus on the product and how it is used and solves the problem. There is an interesting debate about metrics in development teams, between those who say it is important to measure and demand productivity, fast deliveries, expected vs. actual, and those who say it is more effective to track the performance metrics of each delivery, the level of customer satisfaction, the tool's usage rate, business volume, etc.

Obviously, there are no magic formulas; each company and each area has its own reality and, above all, its own strategy.

Conclusion

If you have a well-aligned strategy and measurement process, your metrics will tell you things that people may not be noticing. Therefore, it is not uncommon for companies to resist implementing a data culture.

Perhaps the metrics are telling you that your business is not viable, that the idea is not so innovative, and that you have basically failed. And no one likes to fail, right? My final advice is to keep this in mind and consciously avoid this kind of behavior, and make the most of the potential of data analysis to increase the scalability of your business.

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