In the part 1 of their series (Determine the Operating System Support for an application - Part 1), I started with the discussion about the various Operating Systems that product teams could support, and some of the complications that come about in the decision making for deciding the Operating System support. In this post, I will talk about some of the other issues that help decide what the operating system support should be.
One simple factor that determines what older versions of Operating Systems you should support include determining the customer impact if you drop a version. In today's day and age, you would be hard-pressed to find a user who has Windows 95 or Windows NT on their machines or an equivalent older version of the Mac OS. Even if you did find somebody like that, the number of people who are actually on such Operating Systems would be very small, and you should be able to afford such users. The tricky park comes with Operating Systems that are closer to the current version, such as Windows XP. Now Windows XP has had 3 newer versions of the Windows Operating Systems that have been available after that, namely Windows Vista, Windows 7, and Windows 8. But, a number of people (especially older people) do not make their software upgrade decisions based on whether a newer version is available. If a newer version is available, and if their existing version provides the functionality that they are comfortable with, you will find a significant % of people will not upgrade their Operating Systems or their machines. I personally know numerous people who heard bad stuff about Windows Vista, decided that their Windows XP installation was fine, and refused to upgrade. If your expected customer base has people who are like this, then it would be foolhardy to do an upgrade unless you are sure about your figures. And this is where things get tricky. You have to do data reporting and data analysis to get enough information to take a decision.
Now even inferring from the data analysis may not be fairly straight-forward. How do you decide the data collection technique ? You would want to know from 2 sources - one would be the current users of the application, and the other would be potential users. None of these are easy methods.
Suppose you want to get this data from current users ? The ideal way would have been to have a mechanism within the application that connects on a regular basis to your computers and provides some information about the computer of the user, including the Operating System and Service Pack version of the software application. If you were getting this information from all your users, then it is very easy to consolidate this information and quickly determine how many of your users are on the Operating System on which there is a query about whether you should continue to support it. Suppose you have set a benchmark of 10% being the limit above which you will continue to support an Operating System, then this data will easily help you make a decision. At the same time, keep in mind that building such a system in the application is not easy. In this day and age of security and privacy considerations, you would need to ensure that such a mechanism passes legal and privacy guidelines. Further, keep in mind that some of your users may not be connected to the internet on a regular basis and hence the data you get is only from those people who are connected to the internet. As always, when you get data, you need to make sure that this data is an accurate as you can verify. The method used for data collection, the logic used for the data interpretation both need to be accurate and verified, else you will commit the grave mistake of taking a decision based on either wrong data or wrong analysis of data, both of which can cause grave problems.
This is it for this post, will continue in this series in the next (Determine Operating System Support - Part 3).
One simple factor that determines what older versions of Operating Systems you should support include determining the customer impact if you drop a version. In today's day and age, you would be hard-pressed to find a user who has Windows 95 or Windows NT on their machines or an equivalent older version of the Mac OS. Even if you did find somebody like that, the number of people who are actually on such Operating Systems would be very small, and you should be able to afford such users. The tricky park comes with Operating Systems that are closer to the current version, such as Windows XP. Now Windows XP has had 3 newer versions of the Windows Operating Systems that have been available after that, namely Windows Vista, Windows 7, and Windows 8. But, a number of people (especially older people) do not make their software upgrade decisions based on whether a newer version is available. If a newer version is available, and if their existing version provides the functionality that they are comfortable with, you will find a significant % of people will not upgrade their Operating Systems or their machines. I personally know numerous people who heard bad stuff about Windows Vista, decided that their Windows XP installation was fine, and refused to upgrade. If your expected customer base has people who are like this, then it would be foolhardy to do an upgrade unless you are sure about your figures. And this is where things get tricky. You have to do data reporting and data analysis to get enough information to take a decision.
Now even inferring from the data analysis may not be fairly straight-forward. How do you decide the data collection technique ? You would want to know from 2 sources - one would be the current users of the application, and the other would be potential users. None of these are easy methods.
Suppose you want to get this data from current users ? The ideal way would have been to have a mechanism within the application that connects on a regular basis to your computers and provides some information about the computer of the user, including the Operating System and Service Pack version of the software application. If you were getting this information from all your users, then it is very easy to consolidate this information and quickly determine how many of your users are on the Operating System on which there is a query about whether you should continue to support it. Suppose you have set a benchmark of 10% being the limit above which you will continue to support an Operating System, then this data will easily help you make a decision. At the same time, keep in mind that building such a system in the application is not easy. In this day and age of security and privacy considerations, you would need to ensure that such a mechanism passes legal and privacy guidelines. Further, keep in mind that some of your users may not be connected to the internet on a regular basis and hence the data you get is only from those people who are connected to the internet. As always, when you get data, you need to make sure that this data is an accurate as you can verify. The method used for data collection, the logic used for the data interpretation both need to be accurate and verified, else you will commit the grave mistake of taking a decision based on either wrong data or wrong analysis of data, both of which can cause grave problems.
This is it for this post, will continue in this series in the next (Determine Operating System Support - Part 3).
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