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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.

APM

Hot Topics

The Latest

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...

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A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...

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Cisco

The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...