Backlog in days (number of items divided by daily efficiency) and its ageing

Backlog indicator – a multitude of applications

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“Backlog in days” is an interesting metric for businesses dealing with a high volume of tasks to be completed, such as an IT HelpDesk, accounting department, or services team. By dividing the backlog by efficiency, you can calculate how many days it will take to clear the queue. This metric allows you to monitor whether the situation is improving, worsening, or stable, and to know how old tasks will be when their time comes. It also helps to identify problematic situations and estimate the magnitude of unresolved issues.


Recently, I spoke with an IT manager who manages a team of specialists responsible for solving problems faced by business users, in other words, a classic IT HelpDesk. His team’s workload was significant, and he said that he managed their Key Performance Indicators (KPIs), not the people themselves. This statement reflects the reality that when dealing with a high volume of tasks to be done, precise and timely information is essential. The solution, therefore, is to use an automated monitoring system to monitor the queue.

Do you know your Backlog?

The tasks waiting to be solved are called backlog. These can be

  • Invoices awaiting posting.
  • IT HelpDesk tickets awaiting resolution.
  • Queue of phone calls in a hotline.
  • Patients in queue for addmission.
  • Sales leads to be contacted by phone.
  • Any other task in any other business process.

Backlog in days

The magic happens when you divide the backlog by efficiency to get the Backlog in days. Use the formula:

Daily capacity can be theoretical, for example, we know that a doctor can spend 15 minutes per patient, which means that during a four-hour shift, 16 people will be admitted. It can also be calculated from historical data – for example, the average daily number of IT Tickets resolved in the last three months.

Backlog in days can be interpreted as follows: 

“if new tasks stop coming in, how long will it take us to clear the queue?” 


“if a new task appears today, in how many days will it be taken care of?”

Some people argue that the backlog will never get reduced because the new tasks are always coming.

But that is not the point.

The purposes of calculating backlog in days are the following:

  • Monitoring whether the situation is improving, worsening or is stable. If more tasks are created than you close the old ones, the backlog in days will increase from day to day. You will have clear indications of a problematic situation.
  • a problematic situation.
  • Knowing how old the tasks will be when their time comes. If your backlog in days is 15 and a new invoice with payment terms of 14 days appears in the queue, you already know that by the time of its booking, it will already be overdue.

Too small is bad

So what is the best level of backlog in days?

A number below one (day) might not be advisable. It means that we will “clear” the queue before the end of the day and there will be no work for the team till end of day…. Of course, this is an ideal opportunity to catch up on emails or personal education. However, if the situation is permanent, it means poor use of resources.

Implement it in practice

You need a live connection to the workflow system or other ticketing tool in which tasks are registered.

Automating the connection is essential. Relying on manual CSV file extractions is not a reliable solution. Each system has a database in the background, and it’s easy to connect to each database with Qlik Sense using drivers. Typically, a connection via Qlik Cloud in-built connectors should be enough.

The next step will be to set up a daily (or more frequent if needed) job for downloading data. The data will consist of a list of queued items (with additional dimensions) and the history of closed items.

Having the data, we build a simple table with the following columns:

  • Team or type of request or Customer.
  • Number of tasks in the queue.
  • Daily capacity.
  • Backlog in days (=Number of tasks in the queue / Daily capacity).
  • Number of new tasks yesterday.
  • Number of closed tasks yesterday.
  • Tasks age broken down by intervals, for example up to 7 days, up to 14 days and above 14 days.

The number of new tasks combined with the number of tasks closed will answer the question: is the situation “getting worse” or “getting better”? If we have high backlog in days, in addition there are more tasks beeing open than being closed – the situation will only get worse.

Next steps

Aging (up to 7 days, 7-14 days, over 14 days) will help estimate the scale of the backlog problem. It is possible that the backlog in days is high, but most tasks are relatively new, say less than 7 days old. This indicates that the situation is still manageable.

However, if the aging of tasks is high, with many tasks remaining unresolved for over 14 days, then there is a problem. For instance, in the case of an accounting department, this could lead to delays in paying invoices on time.

By looking at the number of tasks that were closed yesterday, you can gain valuable insight into the performance of your team. Additionally, it’s often possible to track the number of completed tasks by individual employees. If you encounter any issues, you can speak with team members about any obstacles they may have faced. This can uncover systemic problems that might have gone unnoticed, simply because they didn’t occur to anyone to mention.