Centre for Market and Public Organisation

Smarter Task Assignment or Greater Productivity: What Makes a

Difference in Team Performance?

Simon Burgess, Carol Propper, Marisa Ratto, Stephanie von Hinke Kessler Scholder, Emma Tominey

PRELIMINARY RESULTS. PLEASE DO NOT QUOTE

All Staff Frontline Staff

Overall Team 1 Team 2 Control Overall Team 1 Team 2 Control

Gender 0.47 0.39 0.44 0.52 0.46 0.39 0.44 0.52

Age 43.8 45.6 45.3 41.9 44.3 45.4 45.1 43.0

Job band 5.9 6.2 6.0 5.6 6.0 6.2 6.0 5.9

Years in job band 9.1 10.0 10.4 7.8 9.5 10.3 10.4 8.6

Years at C&E 15.6 18.7 11.3 16.3 16.4 18.8 11.3 18.0

Annual pay 20260 20909 20415 19788 20369 20896 20426 20018

Gross monthly pay 1595 1645 1629 1545 1605 1643 1632 1565

Gross monthly pay + o/t 1595 1649 1622 1547 1606 1648 1626 1568

Overtime per month 0.22 0.36 0.21 0.15 0.23 0.37 0.21 0.16

Part-time marker 0.18 0.16 0.12 0.22 0.15 0.16 0.12 0.17

PT hours per week 24.6 24.0 25.0 25.0 24.7 24.0 25.3 25.1

Days of sickness 1.4 1.0 6.6 1.3 1.4 1.0 6.4 1.3

Days in scheme 260.2 258.8 261.5 X 261.6 260.2 263.0 X

Potential bonus 360 686 681 X 377 692 686 X

Team staff mean characteristics

Officer level regressions: diff-diff results. PRELIMINARY RESULTS. PLEASE DO NOT QUOTE

Time Yield Positive yield Negative yield ProductivitySpecification 1Both teams 16.662 862,226.531 879,553.131 -17,326.599 382.772

(12.538) (652,598.418) (653,435.097) (12,221.249) (3,608.746)Team 1 -4.922 136,162.869 145,919.115 -9,756.246 239.004

(12.373) (98,686.498) (98,767.889) (7,560.350) (470.589)Team 2 37.894 *** 978,548.109 1,001,806.908 -23,258.800 271.321

(14.520) (860,264.244) (860,344.116) (21,407.965) (408.845)

Specification 2Both teams 14.010 435,750.800 453,579.263 -17,828.463 40.633

(12.902) (412,809.891) (414,757.543) (12,356.234) (144.382)Team 1 -4.581 47,088.951 57,081.507 -9,992.555 166.134

(12.420) (42,239.992) (43,773.840) (7,575.689) (249.878)Team 2 37.937 *** 896,445.946 919,626.879 -23,180.933 58.324

(14.541) (860,973.361) (860,979.605) (21,053.030) (151.494)

Specification 3Both teams 24,517.457*** 24,629.887*** -633.594*** 28.494

(5,292.030) (5,838.805) (226.192) (23.125)Team 1 25,815.132*** 25,696.292*** -562.030** 70.981**

(7,004.909) (7,864.822) (218.070) (32.555)Team 2 29,781.494*** 28,954.846*** -899.411*** 26.951

(6,927.112) (7,314.759) (297.831) (22.341)

Specification 4Both teams 22,360.027*** 22,154.517*** -585.759** 32.439

(5,254.457) (5,842.350) (236.258) (23.020)Team 1 25,180.406*** 25,583.105*** -549.367** 70.908**

(6,873.621) (7,827.547) (219.232) (32.484)Team 2 28,775.089*** 28,803.199*** -879.165*** 27.019

(6,879.612) (7,288.997) (296.545) (22.287)

* significant at 10%; ** significant at 5%; *** significant at 1%

Strategic task allocation PRELIMINARY RESULTS. PLEASE DO

NOT QUOTEP r o d u c t i v i t y i s d e f i n e d a s t h e s u m o f y i e l d ( 9 m t h s ) o v e r t i m e ( 9 m t h s ) , w e i g h e d b y s h a r e o f t i m e s p e n t

p e r T G :

TGm

TGiTG

mTGi

mTGi

mTGi

i time

time

time

yieldtyproductivi

,

,

,

,

# E f f i c i e n t o f f i c e r s f o r e a c h t e a m r e s p e c t i v e l y : 2 8 ( o u t o f 1 2 9 ) , 2 9 ( o u t o f 1 2 4 ) , 3 5 ( o u t o f 1 9 7 ) . ( T o t a l = 9 2o u t o f 4 5 0 )

I n c e n t i v i s e d T GA l l t e a m s T e a m 1 T e a m 2 C o n t r o l t e a m

E f f i c i e n t o f f i c e r s 1 3 1 . 9 4 8 7 . 1 2 2 7 5 . 9 1 4 8 . 5 1O t h e r s 5 6 . 8 9 3 5 . 0 2 9 8 . 8 4 4 5 . 9 2

t = 2 . 9 8 1 6 t = 1 . 4 9 5 8 t = 3 . 4 6 1 6 t = 0 . 0 6 4 1

S i g n i f i c a n t a t 1 % S i g n i f i c a n t a t 1 0 % S i g n i f i c a n t a t 1 % N o t s i g n i f i c a n t

N o n - i n c e n t i v i s e d T GA l l t e a m s T e a m 1 T e a m 2 C o n t r o l t e a m

E f f i c i e n t o f f i c e r s - 6 3 . 5 6 2 9 . 3 1 - 1 2 2 . 1 7 - 8 9 . 2 9O t h e r s 2 6 . 0 4 5 4 . 0 5 - 8 . 3 1 2 8 . 7 3

t = - 4 . 3 0 7 0 t = - 0 . 7 4 1 0 t = - 2 . 6 6 0 2 t = - 3 . 7 4 7 7

S i g n i f i c a n t a t 1 % N o t s i g n i f i c a n t S i g n i f i c a n t a t 1 % S i g n i f i c a n t a t 1 %

Results (taking out the highest yield in team 2 (180,000,000): PRELIMINARY RESULTS. PLEASE DO NOT QUOTE.

Team 1 Team 2 Control Team

n 102 109 117

A (change in time spent) 10,500,514 19,785,364 4,330,667

B (change in productivity) 3,445,083 1,378,579 752,514

A+B 13,945,597 21,163,943 5,083,181

A as % of the change in yield 75.3 % 93.5 % 85.2 %

B as % of the change in yield 24.7 % 6.5 % 14.8 %

Total yield on M-TGs, period 1 (Change as percentage of original yield)

26,462,188 (99%)

25,001,128 (99.98%)

19,384,152 (95%)

Total yield on M-TGs, period 2 (Change as percentage of original yield)

40,407,784 (87%)

46,165,072 (86%)

24,467,332 (84%)

Change in yield (yr2 - yr1) (Change as percentage of original yield)

13,945,596 (73%)

21,163,944 (74%)

5,083,180 (60%)

Total yield in original dataset, M-TGs, period 1 26,662,859 25,005,142 20,510,915

Total yield in original dataset, M-TGs, period 2 46,238,637 53,553,637 29,049,560

Change in yield in original dataset, M-TGs 19,575,778 28,548,495 8,538,645

Diff between original and decomposition dataset, period 1 200,671 4014 1,126,763

Diff between original and decomposition dataset, period 2 5,830,853 7,388,565 4,582,227

% obs lost in period 1 (# obs.) – level: officer, TG, period 6.7% (12) 5.3% (10) 11.2% (25)

% obs lost in period 2 (# obs.) – level: officer, TG, period 30.4% (73) 27.7% (69) 31.6% (92)