In the last 8 months of 2016, Chemistry and Physics IT resolved over 6.4 tickets per workday.
See also
Goal
Identify all resolved tickets in time-period.
Notes
MAJOR
TBD
MINOR
"Assigned Group" is what we see as the assigned group when we open a Remedy ticket. Confirm if this is the field Remedy reports in their "Assigned Group" header, as is likely the case.
- Reason for question: CIT's HelpDesk practice is to "take" tickets from us, changing the "Assigned Group". There is apparently another (hidden?) field that is the group which created the ticket, regardless of how "Assigned Group" subsequently gets changed.
- For tickets "born" in Chemistry/ Physics, that other field is the one to use, regardless of which group/ person closes it. In our report, would show as closed, but not by one of us (one more line).
- For tickets "born" elsewhere but ended up in Chemistry/ Physics, the normal "Assigned Group" field is the one to use, along with our staff member who closed the ticket. That's happening now.
Process
I wrote to Frank 1/14/16 to request report from Greg Christofferson. Excerpt:
- Thanks for discussing Remedy reports with me this morning, inspired by Greg Christofferson’s <gc88> recent referral to me. Greg thought he was already sending you the report data that I had discussed with him I wanted for our group.
- What you and I discussed is if we could start with getting data for one month, to start. Get data for each of the 4 full-time staff members in Chemistry IT/ Physics IT with how many tickets we resolved in the Chemistry queue. Once we nail down a report with the right info we can broaden the time, include student staff, and pull in data from our other 2 queues (Chemistry 2 and Physics).
Details
This provides us with a measure of volume, to compare with our monthly snap-shots of outstanding tickets.
Process idea: Do for each month (or quarter), starting with the past 6 months (or 2 years).
Implementation ideas
Example 1: Spreadsheets
Rolled-up summaries, useful to detect variability or trends
Time period | Chemistry: Average tickets per month | Chemistry: Average tickets per day | Physics: Average tickets per month | Physics: Average tickets per day |
---|---|---|---|---|
July 2017 | 87 | |||
May 2017 | 92 | 4.2 | 13 | 0.59 |
April 2017 | 100 | 5.0 | 15.0 | 0.75 |
8 months: 04/01/2016 to 01/01/2017 | 123 | 6.3 | 15.5 | 0.8 |
Tickets resolved in July 2017
- From Frank, 8/15/17
Assumptions for analysis portion
- Since JUST the month of July, simply counted the work days, taking into account staff holidays this month (Tues. 7/4: Independence Day): 20 work days.
- See prior analysis if care to have numbers for average number of work days over several months.
Total flow summary: There is an average of over 4.85 tickets resolved by our group each workday, for both Chemistry and Physics.
- We had 97 resolved tickets this month for both Chemistry and Physics.
- At 20 workdays this month: 97 / 20 = ~4.85 resolved tickets per workday.
Chemistry, for this 1 month period:
Flow summary: 87 tickets per month averages to 4.35 tickets resolved per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Lulu Zhu | 2 | 8 | 10 | 0.45 | 11.5% |
Michael E Hint | 28 | 25 | 53 | 2.65 | 60.9% |
Oliver B Habicht | 10 | 14 | 24 | 1.2 | 27.6% |
All others: | 0 | 0 | 0 | - | - |
Total | 40 | 47 | 87 | 4.35 |
Physics, for this 1 month period:
Flow summary: 10 tickets per month averages to about 0.50 tickets per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Kelly Brower | 1 | 3 | 4 | 0.20 | 40% |
Lulu Zhu | 1 | 0 | 1 | 0.05 | 10% |
Michael E Hint | 1 | 4 | 5 | 0.25 | 40% |
Oliver B Habicht | 0 | 0 | 0 | - | - |
All others: | 0 | 0 | 0 | - | - |
Total | 3 | 7 | 10 | 0.50 |
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Tickets resolved in June 2017
- From Frank, 7/13/17
Assumptions for analysis portion
- Since JUST the month of June, simply counted the work days, taking into account staff holidays this month (none): 22 work days.
- See prior analysis if care to have numbers for average number of work days over several months.
Total flow summary: There is an average of over xx tickets resolved by our group each workday, for both Chemistry and Physics.
- We had 117 resolved tickets this month for both Chemistry and Physics.
- At 22 workdays this month: 117 / 22 = ~5.32 resolved tickets per workday.
Chemistry, for this 1 month period:
Flow summary: 100 tickets per month averages to 4.54 tickets resolved per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Lulu Zhu | 3 | 11 | 14 | 0.64 | 14.0% |
Michael E Hint | 37 | 24 | 61 | 2.77 | 61.0% |
Oliver B Habicht | 10 | 14 | 24 | 1.1 | 24.0% |
All others: | 0 | 1 | 1 | 0.04 | 1.0% |
Total | 50 | 50 | 100 | 4.35 |
Physics, for this 1 month period:
Flow summary: 10 tickets per month averages to about 0.50 tickets per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Kelly Brower | 1 | 3 | 4 | 0.20 | 40% |
Lulu Zhu | 1 | 0 | 1 | 0.05 | 10% |
Michael E Hint | 1 | 4 | 5 | 0.25 | 40% |
Oliver B Habicht | 0 | 0 | 0 | - | - |
All others: | 0 | 0 | 0 | - | - |
Total | 3 | 7 | 10 | 0.50 |
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Tickets resolved in May 2017
- From Frank, 6/2/17
Assumptions for analysis portion
- Since JUST the month of May, simply counted the work days, taking into account staff holidays this month (Mon. 5/29: Memorial Day): 22 work days.
- See prior work if care to have numbers for average number of work days over several months.
Total flow summary: There is an average of over 4.77 tickets resolved by our group each workday, for both Chemistry and Physics.
- We averaged 105 resolved tickets per month for both Chemistry and Physics.
- At 22 workdays per month: 105 / 22 = ~4.77 resolved tickets per workday.
Chemistry, for this 1 month period:
Flow summary: 92 tickets per month averages to 4.2 tickets resolved per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Lulu Zhu | 2 | 7 | 9 | 0.41 | 10% |
Michael E Hint | 34 | 25 | 59 | 2.7 | 64% |
Oliver B Habicht | 10 | 13 | 23 | 1.04 | 25% |
All others: | 1 | 1 | 0.04 | 1% | |
Total | 46 | 46 | 92 | 4.2 |
Physics, for this 1 month period:
Flow summary: 13 tickets per month averages to about 0.59 tickets per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Kelly Brower | 4 | 2 | 6 | 0.27 | 46% |
Michael E Hint | 2 | 1 | 3 | 0.14 | 23% |
Oliver B Habicht | 3 | 1 | 4 | 0.18 | 30% |
All others: | 0 | 0 | 0 | - | - |
Total | 9 | 4 | 13 | 0.59 |
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Tickets resolved in April 2017
- From Frank, 5/2/17
Assumptions for analysis portion
- Since JUST the month of April, simply counted the work days, taking into account no staff holidays this month: 20 work days.
- See prior work if care to have numbers for average number of work days over several months.
Total flow summary: There is an average of over 5.75 tickets resolved by our group each workday, for both Chemistry and Physics.
- We averaged 115 resolved tickets per month for both Chemistry and Physics.
- At 20 workdays per month: 115 / 20 = 5.75 resolved tickets per workday.
Chemistry, for this 1 month period:
Flow summary: 100 tickets per month averages to 5 tickets resolved per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Lulu Zhu | 2 | 7 | 9 | 0.45 | 9% |
Michael E Hint | 36 | 23 | 59 | 2.9 | 58% |
Oliver B Habicht | 13 | 18 | 31 | 1.55 | 31% |
All others: | 1 | 0 | 1 | 0.1 | 2% |
Total | 52 | 48 | 100 | 5 |
Physics, for this 1 month period:
Flow summary: 15 tickets per month averages to about 0.75 tickets per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Kelly Brower | 4 | 3 | 7 | 0.35 | 47% |
Michael E Hint | 2 | 3 | 5 | 0.25 | 33% |
Oliver B Habicht | 0 | 3 | 3 | 0.15 | 20% |
All others: | 0 | 0 | 0 | - | - |
Total | 6 | 9 | 15 | 0.75 |
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From Frank, 1/30/17, "Resolved Time Summary per Assignee: 04/01/2016 to 01/01/2017"
Assumptions for analysis portion
- In a year, 52 weeks * 5 workdays = 260 workdays/yr. Assume staff have 3 weeks vacation, and 2 weeks University Holidays, so 5 weeks * 5 days = 25 workdays. Thus 235 workdays per year (=260-25).
- 19.6 workdays per month (=235/12). This represents the available FTEs.
Total flow summary: There is an average of over 6.4 tickets resolved by our group each workday,.
- We averaged 138.5 resolved tickets per month.
- Per above assumption, 19.6 workdays per month: 138.5 / 19.6 = ~7.1 resolved tickets per workday.
Chemistry, for this 8 month period:
Flow summary: 123 tickets per month averages to 6.3 tickets resolved per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Lulu Zhu | 38 | 53 | 91 | 11.4 | 9% |
Michael E Hint | 285 | 247 | 532 | 66.5 | 54% |
Oliver B Habicht | 132 | 104 | 236 | 29.5 | 24% |
All others: | 66 | 58 | 124 | 15.5 | 13% |
Total | 521 | 462 | 983 | 123 |
Physics, for this 8 month period:
Flow summary: 15.5 tickets per month averages to about 0.8 tickets per day.
| Resolved within 1 day | Resolved in more than 1 day | Total | Oliver's analysis: Avg. per month | Oliver's analysis: Percent of volume |
Lulu Zhu | 2 | 1 | 3 | - | - |
Michael E Hint | 34 | 35 | 69 | 8.6 | 56% |
Oliver B Habicht | 21 | 14 | 35 | 4.4 | 28% |
All others: | 9 | 12 | 21 | 2.6 | 17% |
Total | 68 | 56 | 124 | 15.5 |
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In the Month of Sept 2015, ChemIT (Assigned groups: Chemistry and Chemistry (L2)) and PhysIT (Assigned group: Physics) resolved x number of tickets. The are as follows (in a spreadsheet):
Assigned Group, Summary, First Name, Last Name, Contact Type, Reported Date (Why are there two? Do they differ?), Responded Date, Last Resolved Date, Closed Date, Last Acknowledged Date, Last Modified, Re-Opened Date, Service, Status (is either resolved or (auto-)closed, depending on query date), Assignee, Resolution, Customer Building Name, ID.
From Frank, 4/25/16, "Resolved tickets for 3-1 thru 4-12-16":
|
| Resolved within 1 day | Resolved in more than 1 day | Total |
Chemistry | Lulu Zhu | 2 | 8 | 10 |
| Michael E Hint | 41 | 32 | 73 |
| Oliver B Habicht | 9 | 8 | 17 |
| Roger W Garnett | 16 | 8 | 24 |
| Total | 68 | 56 | 124 |
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From Frank, 3/16/16: For January 2016:
Assigned Group | Assignee | Incident Closed/Resolved |
Chemistry | Lulu Zhu | 14 |
| Michael E Hint | 55 |
| Oliver B Habicht | 14 |
| Roger W Garnett | 18 |
| Sub-Total | 101 |
Chemistry | Total | 101 |
Note: Frank's data had a column for "Hours Captured". We used to put down hours since never got reports with this data, so for this time-period, it's labelled as "No Effort".
Example 2: Pie charts
Pie chart for ChemIT and separate pie chart for PhysIT showing tickets completed by staff member. Annual snapshot?
- Similar to the Library's Desktop Services "DS Resolved Incidents 2014" and "DS Resolved Incidents 2015" web reports.