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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

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...