Keep 'em or kick 'em out: Evaluating student workforce performance

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Keep ‘em or kick ‘em out Evaluating student workforce performance

description

This presentation summarizes processes in evaluation student workforce performance for the HelpDesk at the University at Albany's Information Technology Services-Client Support Services. I presented this at the 2013 SUNY Technology Conference and the 2014 SUNYLA Empire Collaborations conferences.

Transcript of Keep 'em or kick 'em out: Evaluating student workforce performance

Page 1: Keep 'em or kick 'em out: Evaluating student workforce performance

Keep ‘em or kick ‘em outEvaluating student workforce performance

Page 2: Keep 'em or kick 'em out: Evaluating student workforce performance

BackgroundWhere do I come from?

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HiringWho will help you help others?

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Hiring process

• Post on student job site and notify bye-mail• Technical

qualifications

• Review applications …

Experience using University IT services:

• MyUAlbany portal• UAlbany Mail and Office 365• Blackboard LMS• UAlbanyWiFi wireless service• UNIX services for file storage

or personal web site

General knowledge of:• Windows operating system• Macintosh operating system• Web browsers

(IE, Firefox, Safari, Chrome)• Microsoft Office

(Word, Excel, PowerPoint, Outlook)

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Application review and scoring

First

name

Last

name

Recom. GradDate

(≥5/2015)

Exp

sem

GPA

(2+)

Previous

work

Specific,

relevant skills

Skill

Work

Rel

Assist

Q

Diff

Cust

Q

Why

ITS Q

Writ

Qual

Score

(sum)

Inter

view?

A Z 2016-May 6 2.5 Lifeguard Excel 2 3 1 3 2 18 Perhaps

B Y MNO 2015-May 4 1.7 2 3 2 3 2 16.4 No

C X 2015-May 4 2.8 2 3 2 2 3 15.6 Perhaps

D W 2014-Dec 3 4.0 Retail OS X, Office 3 1 2 2 1 14 NoSem

E V 2015-May 4 2.5 2 3 3 3 3 17 Perhaps

F U 2015-May 4 3.5 2 3 2 2 3 17 Perhaps

G T JKL 2016-May 6 2.0 3 3 3 2 2 23 Yes

H S 2016-May 6 3.6 2 2 2 3 2 20.1 Yes

I R 2015-May 4 3.4 Clerical Malware clean 3 3 3 3 2 19.8 Yes

J Q 2015-May 4 2.7 2 3 3 2 3 16.4 No

K P 2014-May 2 2.9 3 2 3 2 3 13.8 NoSem

L O ABC 2015-May 4 3.1 2 3 3 3 2 20.2 Yes

M N 2014-Dec 3 3.0 3 3 3 3 2 17 NoSem

N M 2015-May 4 3.7 2 2 3 2 3 17.4 Perhaps

O L 2015-May 4 3.9 2 3 3 3 3 19.8 Yes

P J DEF 2014-May 2 2.9 2 1 1 2 2 10.8 NoSem

Q K 2016-May 6 3.3 2 3 2 2 2 19.6 Yes

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Interviews and training

• Student staff panel

• Professional staff meeting

• Discussion and consensus

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Set upWhat do they need to know?

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Set expectations

• Shadowing (probationary and mentoring period)

• Clearly define expectations, rules, rewards, and penalties• Boot Camp

• Student workforce handbook

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Correction

• Corrective actions must be• Instructive

• Flexible

• Timely

• Applied

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ReviewHow are they doing?

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Types of review

• No surprises

• Ongoing, quick (mentor)

• Periodic, detailed• Collect feedback

• Observed impressions

• Performance statistics…

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Performance statistics

• Tickets/interactions recorded

• Net substitute shifts

• Incidence of late or no show

• Project work and KB articles

• Hours worked• Tickets per hour

• Net subs per hour

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Performance metric

Summed semester data Weekly collected data

Fname Lname Metric Busy Slow Temp Perm Projects Late/MIA Busy Slow Temp Perm Projects Late/MIA

A Z -6.75 11 6 -46 -3 0 5 4 -6 0 0

B Y 16 38 3 -26 2 0 2 -5 0 0

C X 55.5 92 1 1 0 3 9 15 0 0 1 0

D W -1.75 3 10 -41 0 0 4 -6 0 0

E V 2 13 1 -16 0 0 2 0 0 0

F U 24.5 35 2 -19 0 3 7 4 0 0 3 0

G T 9.75 26 7 -9 2 1 20 -1 0 0

H S 15.75 45 3 -7 1 0 12 2 0 0 1

I R 18.25 26 0 1 0 1 0 4 1 0 0

J Q 50.25 34 0 39 0 5 2 0 0 2 0

K P 2.25 9 1 35 -3 0 12 4 3 0 0

L O 21.75 16 4 5 0 2 2 0 0 0

M N 16.75 35 0 -69 1 4 6 9 -1 0 1 1

N M 41.5 19 9 51 9 1 5 3 6 3 0

O L 22.75 21 13 6 -2 1 7 8 0 0 0

P J 5 9 13 -35 1 1 13 3 -1 2 1 0

Q K 18 43 5 -29 1 0 3 3 2 0 0

8/3/2012

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Performance highlights

Fname Lname Hours Incidents Inc/hour Net subs Subs/hour Late/MIA Metric

A Z 158.75 17 0.107 -44 -0.277 5.00 -5.50

B Y 221.75 41 0.185 -11 -0.050 2.00 19.25

C X 276.25 93 0.337 -1 -0.004 9.00 50.00

D W 178.75 13 0.073 -35 -0.196 3.00 0.50

E V 151.25 14 0.093 -16 -0.106 2.00 2.00

F U 112.25 37 0.330 -17 -0.151 7.00 10.00

G T 62.00 33 0.532 -4 -0.065 20.00 10.50

H S 197.75 48 0.243 -6 -0.030 10.00 17.25

I R 52.00 26 0.500 -2 -0.038 0.00 17.50

J Q 320.25 34 0.106 37 0.116 2.00 39.75

K P 129.00 10 0.078 29 0.225 12.00 1.50

L O 190.75 20 0.105 4 0.021 2.00 21.50

M N 215.75 35 0.162 -67 -0.311 5.00 12.75

N M 191.50 28 0.146 47 0.245 4.00 36.75

O L 260.75 34 0.130 3 0.012 7.00 22.50

P J 160.25 22 0.137 -34 -0.212 13.00 -1.50

Q K 247.75 48 0.194 -21 -0.085 2.00 20.50

By Mwtoews [CC-BY-2.5 (http://creativecommons.org/licenses/by/2.5)], via Wikimedia Commons

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ToolsWhere do we get the data?

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Data sources and analysis

• Ticket tracking reports (FootPrints)• Interactions recorded

• Scheduling notifications (ConPortal, Outlook)• Substitute shifts (via e-mail)

• Late or no-show (via e-mail)

• Hours worked

• Excel for computation and summary

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Questions and discussionWhat more do you want to know?

What do you do?

Andrew [email protected]