August 8, 2011 at 14:58Admins-per-server ratio - observations from my own experience
I have been asking myself this question for a long time - what “N” number of admins is needed to service M number of servers? Or how many support staff need for a certain number of workstations. As it turned out, there is no definite answer to this question. Let me shorten the title of the article to an APS rating. The indicator depends on:
Nevertheless, the general approaches to the definition of this relationship are indicated in the following sources:
If we make some generalizations (for example, removing data center values that are clearly non-standard for medium-sized Russian businesses, with a ratio of 1 / 300-1 / 1000), then the picture is as follows (for comparison, I additionally gave values for my activities):
David Cappucci (2) proposed the following division of users into groups:
To determine which group the users of my organization belong to, I used this particular model, with the predominance of group B. In this case, the scope of the APS rating is extended from 1/80 to 1/120. I have 1/99.
In addition, using data from the application system, I was able to analyze user applications for 2010 and the 1st half of 2011.
Total applications received:
- for the 1st half of 2010 - 1118 (of which, 781 requests for change and 337 failures)
- for the 1st half of 2011 - 1282 (of which 843 requests for change and 439 failures)
those. the total growth in the number of applications amounted to 14.7% compared to last year. For the subsequent analysis, it is important to know that we are operating with two time values characterizing each application - the time of actual closing (i.e., from the moment when the user opened the application until the moment when the IT employee closed this application) and the time spent by the IT employee to complete this application . These time intervals may vary by time. This situation (the difference between the actual execution time and labor costs) occurs in the following cases:
It should also be noted that in the 1st half of 2011, the number of IT employees was 9 (of which 4 were directly involved in support) people, in the 1st half of 2010 we were 8 (3 support employees). Accordingly, with the old number (8), for six months of 2010 we managed to reach the average actual closing time of 1 application in 79.4 minutes. In 2011, when the number was already 9 people, the actual average time for closing an application was 52.6 minutes. In fact, we improved our indicators by 33.7% compared to the previous year, increasing the staff by 12.5%. Interestingly, the IT employee’s labor costs per application decreased by approximately 1.3 minutes (i.e., improved by 2.5% compared to last year).
What conclusions can be drawn? For example, it seems clear to me that 3 IT employees to support 395 users are clearly not enough (this is evidenced by at least a 33% improvement in the time spent on an application after increasing the number of support employees to 4).
About the company-consumer of services: wholesale and retail sale of electronics, system integrator with a developed branch network
- server uniformity
- nature of tasks
- operating system
- application software
- and even "advanced" users
Nevertheless, the general approaches to the definition of this relationship are indicated in the following sources:
- How Many Administrators are Enough?
- Know The Types: Sizing up Support Staffs
- Improve staffing ratios
- Is there best practice for a server to system administrator ratio?
If we make some generalizations (for example, removing data center values that are clearly non-standard for medium-sized Russian businesses, with a ratio of 1 / 300-1 / 1000), then the picture is as follows (for comparison, I additionally gave values for my activities):
- ratio of the number of administrators to the number of servers from 1/10 to 1/20 (1/25)
David Cappucci (2) proposed the following division of users into groups:
- Group A - users at the forefront of progress (traders, developers and programmers), require (or want) the latest and fastest equipment. APS rating - 1/30!
- Group B - users with a common set of software on computers, use the tools of group work and analytics. however, stopping these users is tantamount to stopping the business. APS rating from 1/60 to 1/100
- Group C - users with a standard set of software, without critical impact on the business. APS Rating - 1/125
To determine which group the users of my organization belong to, I used this particular model, with the predominance of group B. In this case, the scope of the APS rating is extended from 1/80 to 1/120. I have 1/99.
In addition, using data from the application system, I was able to analyze user applications for 2010 and the 1st half of 2011.
Total applications received:
- for the 1st half of 2010 - 1118 (of which, 781 requests for change and 337 failures)
- for the 1st half of 2011 - 1282 (of which 843 requests for change and 439 failures)
those. the total growth in the number of applications amounted to 14.7% compared to last year. For the subsequent analysis, it is important to know that we are operating with two time values characterizing each application - the time of actual closing (i.e., from the moment when the user opened the application until the moment when the IT employee closed this application) and the time spent by the IT employee to complete this application . These time intervals may vary by time. This situation (the difference between the actual execution time and labor costs) occurs in the following cases:
- when the processing of the application is related to the transportation of equipment. For example, in the case of a geographically distributed network (for example, we have the northernmost unit in Khanty-Mansiysk ~ 900 km from the head office, there are no IT specialists there), with regular delivery once a week;
- when connected with an order for hardware / software that is not in stock . For example, they order expensive and piece equipment, which only arrives from Moscow to the head office in 4 weeks
It should also be noted that in the 1st half of 2011, the number of IT employees was 9 (of which 4 were directly involved in support) people, in the 1st half of 2010 we were 8 (3 support employees). Accordingly, with the old number (8), for six months of 2010 we managed to reach the average actual closing time of 1 application in 79.4 minutes. In 2011, when the number was already 9 people, the actual average time for closing an application was 52.6 minutes. In fact, we improved our indicators by 33.7% compared to the previous year, increasing the staff by 12.5%. Interestingly, the IT employee’s labor costs per application decreased by approximately 1.3 minutes (i.e., improved by 2.5% compared to last year).
What conclusions can be drawn? For example, it seems clear to me that 3 IT employees to support 395 users are clearly not enough (this is evidenced by at least a 33% improvement in the time spent on an application after increasing the number of support employees to 4).
About the company-consumer of services: wholesale and retail sale of electronics, system integrator with a developed branch network