Employee Engagement Surveys: Improving your scores without really - - PowerPoint PPT Presentation

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Employee Engagement Surveys: Improving your scores without really - - PowerPoint PPT Presentation

1 Employee Engagement Surveys: Improving your scores without really trying Garry Gelade Business Analytic Ltd 2 Outline How to improve your employee engagement scores without really trying. How not to be so stupid as to think you


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Employee Engagement Surveys: Improving your scores without really trying

Garry Gelade Business Analytic Ltd

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Outline

  • How to improve your employee engagement

scores without really trying.

  • How not to be so stupid as to think you could do

such a thing.

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Managing Employee Engagement

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Annual Survey Develop Action Plans Intervene

Reward Improvements

Departmental level

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Focus the Effort!

4 “One emerging best practice for improving survey effectiveness is to aim follow-up actions more precisely where they are needed rather than across the organization at large. This means making action plans required

  • nly for employee units or teams that perform poorly in key

areas but not for other groups where survey results reveal a generally healthy productive work environment”

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Hopi Rain Dance

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Average rainfall in the month following the dance is higher than in the month preceding the dance. .... ... Because the Indians never perform the rain dance when it’s raining. This gives the false impression that the dance is effective.

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Before Dance After Dance

Rainfall in the Southwest USA [illustrative!]

6 Average rainfall

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www.towerswatson.com/newsletters/strategy-at-work/2830

Engagement Rain Dance

7 “The HR team requests that managers whose scores declined the most or are farthest below regional norms send their impact plans directly to the CEO and Chief operation officer. ‘We have found that by doing this, it’s unlikely for these managers to have low scores again the following year’, says Church. ‘Managers know we take all plans seriously and hold them accountable for executing them”.

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“XYZ’s lowest scoring units received coaching and support last year. Engagement scores improved an average of 14 points in these units (vs 1 point in all other units)”

Bottom 10th percentile has improved an average of 5 points

While the top 10th percentile is “remaining stable”

Engagement Rain Dance with Attitude

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Regression Towards the Mean

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Tall Parents Short Parents Population Mean Children Children Galton, F. (1886). Regression towards mediocrity in hereditary

  • stature. Journal of the Anthropological Institute, 15, 246-263.

Galton: “Regression Towards Mediocrity”

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Plate IX from Galton’s paper.

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Mechanism of RTM

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RTM in Best Companies Results

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http://money.cnn.com/magazines/fortune/bestcompanies/2011/full_list

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The average Top 20 company fell down the rankings by 7.9 places Best Company Survey: 89 of the top 100 US companies in the 2011 assessment also participated in the 2012 assessment The average Bottom 20 company rose up the rankings by12.6 places

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UK retail bank: 495 branches. 5-item engagement scale (Alpha= .94) 3-item Computer Satisfaction scale (Alpha= .79) Year 1 Year 2 difference Engagement

Overall Mean (SD) 3.23 (0.47) 3.25 (0.40) +0.02 Top 50 branches 4.04 3.63

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Bottom 50 branches 2.40 3.00 +0.60 Computer Satisfaction Overall Mean (SD) 3.11 (0.39) 3.59 (0.37) +0.48 Top 50 branches 3.77 3.77 0.00 Bottom 50 branches 2.40 3.62 +1.21

RTM in Engagement Survey Data

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Recognizing RTM and correcting for it

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Recognizing RTM

Mean Score Year 1 Low scoring units improve High scoring units drop

Plot change vs. baseline 18

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Correcting for RTM - ANCOVA

Adjusts each unit’s follow-up (e.g. Year 2) measurement according to their baseline (e.g. Year 1) measurement. where group = 1 for intervention group, and 0 for no intervention group. The coefficient β2 is the estimated treatment effect adjusted for RTM. Twisk JWR. Applied Longitudinal Data Analysis for Epidemiology: a Practical Guide. Cambridge University Press, 2003. 𝐺𝑝𝑚𝑚𝑝𝑥𝑣𝑞 = 𝛾0 + 𝛾1 𝑐𝑏𝑡𝑓𝑚𝑗𝑜𝑓 − 𝑐𝑏𝑡𝑓𝑚𝑗𝑜𝑓 𝑛𝑓𝑏𝑜 + 𝛾2 𝑕𝑠𝑝𝑣𝑞 19

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Correcting for RTM - Mee & Chua

  • 1. Calculate X = Y1-μ
  • 2. Estimate the parameters β0 and ρ from the linear regression model of Y2 on X
  • 3. Estimate the treatment effect by subtracting μ from τ, the estimate of β0
  • 4. Calculate the test-statistic

where s2 is the mean squared error in the regression analysis of variance, Xi denotes the value

  • f X in the i-th case, i = 1,..., n, and is the mean of all Xi
  • 5. Compare t with the appropriate t-distribution with (n-2) degrees of freedom to obtain a p-

value p = p(μ).

Y2 = μ + τ + ρ(Y1 - μ) + ε

Mee, R. W., & Chua, T. C. (1991). Regression toward the mean and the paired sample t test. The American Statistician, 45(1), 39-42.

20 t-test for the existence of a treatment effect in the presence of RTM

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Thanks for Listening. We’re Done.

Any Questions?

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