SERVICE MANAGEMENT
23 November

The US Elections and the real IT Experience

Last week I was watching one of the discussions around the polls for the elections in the US. All polls, except one, showed that Hillary Clinton would win the elections. But she didn’t as we all know. Only LA times had it right. Why?

While I am not political in any way, I can’t help but observe with interest the political process itself, and how this process has been affected in so many ways by the use, misuse and timing of data.

The problem with finding accurate and random samples of voters to poll has plagued polling since cell phones became the new standard and this seems to cause the issue. Prior to this technological development, landline telephones made it very easy to find random and representative samples, as pollsters could just pick random names out of phone books, call potential voters, and talk them through interviews, which supplied the kind of rich context and human understanding necessary for properly analyzing their responses.
The problem with the rise of Millennials using only cell phones, not even owning landlines anymore, is that cell phones are not usually publicly-listed, making it harder and harder to find representative samples. Result is that the landline polls are wrong. The wrong audience, the wrong user experience, resulting in a wrong prediction.

Time has changed around utilizing advanced statistics. Using machine-learning, and creating models that are based on voter rolls and age, are better ways to improve the underlying assumptions of polls. In short, collecting and combining data from the voter perspective in an innovative way will be the solution for accurate polls and predictions in the near future.

Why is it so important to scan big data correctly; the real experience?

You probably think what can we as IT support learn from these elections? Well, what if you are collecting the wrong data to predict customer satisfaction? We all monitor many servers, and make sure their availability is 99% and more. Still we have unhappy end users. They still face issues that IT is not yet aware of.

Let’s take an example; one of the application/services we offer to the end users is SAP. We monitor the server that SAP is installed on and that particular server has 99.9% uptime. We as IT measure in our reports that SAP is available. We even over performed on our SLA. Well done!!! 

Now, when we ask the end user, the consumer of the SAP application, they might quickly tell us that they are not happy about the use of SAP and that they even can’t consume the service. So the users experience isn’t that good as we expected, based on our poll on the server. We missed our Experience Level Agreement (XLA).

In today’s complex infrastructure we have many more components related to the delivery of the service. Our traditional way of monitoring individual components is not enough to make sure we match our XLA with the consumers of the services we deliver. So we need an innovative way to collect and combine data from the end users' perspective to improve the end users' satisfaction. Nexthink can help you do so.

Let’s check some details by checking the service consumed by a user through the use of Nexthink. We see 48 devices, facing this issue, 78,1% of failed web requests facing by several users in Paris, Zurich and London while we as IT still think SAP is consumed perfectly as the traditional monitoring tells that the SAP server is up and running.

We notice that (from left to right) devices in a certain location, connect via Internet explorer, via port 80 to a proxy to finally reach the SAP environment. 
Based on the Failed Web Requests we can look into the details and we see that the EU-Proxy is causing an issue here

In summary, with Nexthink we can see the real time User Experience of IT consumption. With that data we handle pro-active problem management, have faster mean time to repair and quicker investigation times to find the root cause. All resulting in a much better user experience and more useable input to create meaningful reports based on the SLA but also the XLA.

Check out Nexthink on our website to learn more.