The Real Cost of Logging On

How much does it cost a business to wait for users logging on? This question is important but often overlooked and as businesses strive more to monitor costs it would only be practical to measure the costs consumed when users log on’.

I have spent a considerable amount of time researching and putting together a model to understand the cost of logging on within a business. The business that I currently work for, Avanite Limited, are extremely focused on maximising the user experience and logon times are a large contributor to that. I wanted to understand what the real cost of logging on is to the business, so I started my research by looking at what the average logon time was.

Our CTO Peter Jones wrote an article on how roaming web data for Internet Explorer can impact logon times,  "Roaming IE 11 Cookies and...". For the purpose of this research I will be using the data captured for a Citrix Profile Management Solution without streaming enabled, to capture representative data we used "Simulated Browsing: Each user used Internet Explorer 11 to browse 25 random websites in each session from the list of the top 5000 websites according to Alexa from early 2018." (more information on how we gathered data is available via the link above). The subsequent results were an average logon time of 60.02 seconds per user.

Now that I have my data on average logon times I need to look into how to work out the cost associated to this, I used a report from the Bureau of Labor Statistics (BLS) dated 14th December 2018 on "Employer Costs for Employee Compensation" as I wanted to ensure the costs were worked out on a 'cost to business' basis. The average employee cost per hour is $36.63, giving us a 'per-minute wage' of $0.61. I am working on a basis of 3 logons per day on average however this is completely scalable and personal preference.

Let's do some mathematics, for a business with 1,000 users if each logon is an average of 60 seconds*, the 'per-minute wage' is $0.61 and we on average logon 3 times per day, the equation is simple:

($0.61 x 3) x 1,000 = $1,830 per day

That's $1,830 per day we are spending on waiting for machines to logon. Now let's take those numbers and look at scaling that out to different organisation sizes:

To further analyze what that cost looks like on a per-annum basis, worked out with the average work days per year at 251 days:

Taking the above into consideration I think that we can all agree on the same thing, a cost like this does not look good on paper, on the bottom line and for the productivity of our users.

So, what would be the point of an article such as this if I were to not point out a way to cut down the cost of these logons?

This is where Avanite’s WebData Control comes into play. With an average logon time reduction of 60% we are able to cut the cost of logon down considerably. Using just the cost per-annum model, the below shows the new cost based on the 60% logon time reduction and the saving made per-annum with Avanite's WebData Control implemented:

In view of the above costs of logging on, as businesses we need to explore what we can do to improve in these areas and not forget about how this affects our overall user productivity. 

A delayed logon time has become somewhat of an accepted cultural norm, whereby as employees we spend our time waiting to log on talking about how long it is taking, finding ourselves chatting with co-workers about what they did the night before whilst wandering into the kitchen to make ourselves a drink to start the day; all the while taking us out of the "I'm at work" mindset. Delayed logon times don't just affect our business on the bottom line, it affects culture, productivity and mindsets.

Avanite's WebData Control doesn't just improve logon times, we also help to reduce support calls (I'll be looking into the costs of these too!), allow for complete cookie management including tacking and advertising cookies, synchronize user favourites between Internet Explorer, Edge, Mozilla Firefox and Google Chrome,create a series of default favourites which will always appear on a particular browser and much more.