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Time is Money

Robin Lyon

Time is an important measurement of IT service, especially if we use transaction time. Time is well understood and begins to answer some of the fuzzy questions such as slowness and what is performance. Of course there are other great questions in IT and one of the most dreaded is: "How much does this application cost?" This question creates countless man hours of work quickly running into the diminished returns of hours spent vs. accuracy.


Here is an enumerated example:
 
1. The cost of the actual application (license, lease etc.) + depreciation as appropriate.

2. The cost of maintenance agreements.

3. The cost of the man power supporting the application (often fractions of various head count.)

4. The cost of the dedicated hardware supporting the application.

5. The proportion cost of shared hardware and software such as Databases and SAN space.

6. The proportion cost of network equipment + and then network support hours.

7. The cost of data center space + power + environment.

8. The proportional cost of management.

9. The cost of shared services such as backup and monitoring.

10. …

As you can see this becomes quite a long list and rapidly becomes time intensive. I remember one organization that spent days deciding how to divide the data center power bill into the application numbers. The humorous or sad reality is thousands of dollars of time in meetings was used to shift increments of hundreds of dollars between the applications. What was disturbing is at the end of weeks of work by most of IT, a reasonable number was returned but what it didn’t show was one of the greatest and most forgotten costs of an application, that of user time. There are good reasons for this such as "user time is not part of the IT budget" or "how could we possibly calculate that number to any accuracy?"
 
Now that we have a method to understand transaction time, we can understand the cost of slow application. A simple formula is (the number of transactions) x (the average transaction time) x (the cost of loaded headcount per time).

This is not perfect, nor do I want to make perfection the enemy of good. It is reasonable to say if a user waits more than a minute for a result, they start multitasking. This can be corrected by ignoring transactions longer than one minute for this simple formula. There are other exceptions and all can be corrected for, but let’s take an example application and figure out some numbers.

We have an application that 600 users use 60 times a day with an average transaction time of 10 seconds. That comes out to 36,000 transactions or 360,000 seconds or 100 hours. HR tells us that our loaded headcount is 40 dollars an hour so we have $4,000 per day of lost time spent waiting for application response. This is a shocking number; it often exceeds the total cost from the tedious exercise of calculating an application cost. Other ways to think of this number are $88,000 per month or 12.5 people doing nothing but waiting every single day.
 
Fortunately, with information comes opportunity. There are several beneficial ways to use this discovered cost. One way is it may help reluctant organizations understand the importance of IT and good systems. When the cost is presented to the application owner, they might want to invest in improving application performance. Assume when looking at the application performance we find most the time is spent in the database. After a bit of testing we can see a 25% increase of performance by moving to a DB cluster and the cost of doing this is $100,000. Using our $88,000 cost of time per month we calculate the DB improvement pays for its self in 5 months ($88,000 x .25 x 5 = $110,000) in increased productivity.
 
This number is also a key management number. During the year end budget and priority cycle there are several ways to decide how to assign the all too few resources given to IT. Other than compliance and obsolescence, a strong argument is improving what will gain the most productivity, and money is the understandable measure to use.
 
Businesses run by understanding costs. Application management allows IT to start speaking the same language as rest of a company – one of dollars and cents. An old basic business adage is you can’t manage what you don’t measure.

Robin Lyon is Director of Analytics at AppEnsure.

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Time is Money

Robin Lyon

Time is an important measurement of IT service, especially if we use transaction time. Time is well understood and begins to answer some of the fuzzy questions such as slowness and what is performance. Of course there are other great questions in IT and one of the most dreaded is: "How much does this application cost?" This question creates countless man hours of work quickly running into the diminished returns of hours spent vs. accuracy.


Here is an enumerated example:
 
1. The cost of the actual application (license, lease etc.) + depreciation as appropriate.

2. The cost of maintenance agreements.

3. The cost of the man power supporting the application (often fractions of various head count.)

4. The cost of the dedicated hardware supporting the application.

5. The proportion cost of shared hardware and software such as Databases and SAN space.

6. The proportion cost of network equipment + and then network support hours.

7. The cost of data center space + power + environment.

8. The proportional cost of management.

9. The cost of shared services such as backup and monitoring.

10. …

As you can see this becomes quite a long list and rapidly becomes time intensive. I remember one organization that spent days deciding how to divide the data center power bill into the application numbers. The humorous or sad reality is thousands of dollars of time in meetings was used to shift increments of hundreds of dollars between the applications. What was disturbing is at the end of weeks of work by most of IT, a reasonable number was returned but what it didn’t show was one of the greatest and most forgotten costs of an application, that of user time. There are good reasons for this such as "user time is not part of the IT budget" or "how could we possibly calculate that number to any accuracy?"
 
Now that we have a method to understand transaction time, we can understand the cost of slow application. A simple formula is (the number of transactions) x (the average transaction time) x (the cost of loaded headcount per time).

This is not perfect, nor do I want to make perfection the enemy of good. It is reasonable to say if a user waits more than a minute for a result, they start multitasking. This can be corrected by ignoring transactions longer than one minute for this simple formula. There are other exceptions and all can be corrected for, but let’s take an example application and figure out some numbers.

We have an application that 600 users use 60 times a day with an average transaction time of 10 seconds. That comes out to 36,000 transactions or 360,000 seconds or 100 hours. HR tells us that our loaded headcount is 40 dollars an hour so we have $4,000 per day of lost time spent waiting for application response. This is a shocking number; it often exceeds the total cost from the tedious exercise of calculating an application cost. Other ways to think of this number are $88,000 per month or 12.5 people doing nothing but waiting every single day.
 
Fortunately, with information comes opportunity. There are several beneficial ways to use this discovered cost. One way is it may help reluctant organizations understand the importance of IT and good systems. When the cost is presented to the application owner, they might want to invest in improving application performance. Assume when looking at the application performance we find most the time is spent in the database. After a bit of testing we can see a 25% increase of performance by moving to a DB cluster and the cost of doing this is $100,000. Using our $88,000 cost of time per month we calculate the DB improvement pays for its self in 5 months ($88,000 x .25 x 5 = $110,000) in increased productivity.
 
This number is also a key management number. During the year end budget and priority cycle there are several ways to decide how to assign the all too few resources given to IT. Other than compliance and obsolescence, a strong argument is improving what will gain the most productivity, and money is the understandable measure to use.
 
Businesses run by understanding costs. Application management allows IT to start speaking the same language as rest of a company – one of dollars and cents. An old basic business adage is you can’t manage what you don’t measure.

Robin Lyon is Director of Analytics at AppEnsure.

Hot Topics

The Latest

Outages aren't new. What's new is how quickly they spread across systems, vendors, regions and customer workflows. The moment that performance degrades, expectations escalate fast. In today's always-on environment, an outage isn't just a technical event. It's a trust event ...

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...