The Tickets Take Too Long Report identifies the clients and ticket types for which you're spending significantly more time than for other clients. Then, it shows you the hours, revenue and % of EBITDA this excess time represents.

This report allows you to find for which clients and ticket types you're less efficient, an insight which you can use to make business decisions that will save you time and resources.

Filters are a key part of this report, as selecting them right will allow you to see the most significant clients and ticket types, who will have the highest impact on your business. Here are the available filters and what each of them does:

1. The date range determines the time period of the tickets we will be looking at. You might want to do a Monthly, Quarterly or Yearly analysis, so you can either directly select the starting and ending months or use the quick select tool to use a pre-selected time frame.

2. The Board filter allows you to only look at tickets from a specific board. You can choose among boards who have tickets in the results of this report (with current filters). To have more boards available, you can change the other filters.

3. The Type/Subtype/Item allows you to only look at tickets from a specific Type/Subtype/Item. This can be used to compare underperforming clients who have the same type of tickets. Similarly to the board filter (2) you can choose among Ticket Types/Subtypes/Items who have tickets in the results of this report (with current filters).

4. The Minimum Number of Tickets filter allows you to only show ticket categories who have been submitted by the client more than X times  during the selected date range. This is used to filter out clients who have had a small number of tickets who took too long but were not significant. Keep in mind that the longer date range you're selecting, the higher the number of tickets will be.

5. The Minimum Monthly revenue filter hides the clients who's revenue was less than the amount selected. This is useful if you only want to look at your larger clients.

6. The Minimum EBITDA % Gain filter is key to the amount of results you will see in this report. It hides the Clients and Ticket types where the % of EBITDA opportunity is below the selected number, allowing you to only see the clients and ticket types who represent the largest opportunities.
It's important to note that this number is highly dependent on the size of your company. The larger your total EBITDA is, the lower the EBITDA % opportunities will be for each client.

Here is what each column of the Results table means

1. Client Name. This is the client for which the Ticket Type/Subtype/Item is underperforming.

2. 3. 4. 5. Board, Type, Subtype & Item. These are the ticket subcategories that we identified as underperforming for the client.

6. Client Hours per Ticket. How many hours are you spending on tickets of these subcategories (2. 3. 4. & 5.) for this client (1.)

7. Company Hours per Ticket. How many hours are you spending on tickets of these subcategories (2. 3. 4. & 5.) across all of your clients (1.)

8. Excess Time. How many more hours are you spending on this client per ticket from these subcategories compared to all of your clients.

9. Ticket count. How many tickets of these subcategories have been created by this client in the selected date range.

10. Hours Opportunity. How much Excess Time (8.)  has been spent on tickets of these subcategories in the selected date range.

11. Revenue Opportunity. Considering your effective rate, how much revenue does this Hours Opportunity (10.) represent. (How much you would get if you were to re-sell these hours)

12. What % of your EBITDA does this Revenue Opportunity (11.) represent.

The goal of this report is to give your operations team action points, ticket types that are underperforming for some clients, that they can fix.

Let's take the table above as an example. By looking at this report you'll notice that the ticket Item "Line of Business App" is highly underperforming for Client 894. It takes on average 4.47 hours to fix it for client 894 while it only takes 1.11 for an average client.

This means that each time a ticket of this type/subtype/item was submitted by this client during the date range, it took 3.34 more hours to fix compared to the average client. This underperformance, when applied to the 7 "Line of Business App" tickets submitted in this time frame, represents a 23 hours opportunity.

With the current Effective Rate that this company has, those 23 hours could have been re-sold for $4,713, which is 0.12% of their EBITDA.

Once you've identified ticket types + clients that are underperforming, you can ask your Operations team to look into them and try to fix them, as this will result in better operational efficiency, and in the end, a better bottom line.