Truth-telling between Salespeople and their Managers (The Search for a Non-Truth-Telling...
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Transcript of Truth-telling between Salespeople and their Managers (The Search for a Non-Truth-Telling...
Truth-telling between Salespeople and their Managers(The Search for a Non-Truth-Telling Equilibrium)
December 4, 2007
Presentation for: MGT 703: Experimental Economics
Yale School of Management 20071204_In_Class_Presentation.ppt 2
Motivation
Experimental setup
Results from in-class experiment
Critique and Advice– I need your help …
Agenda
Yale School of Management 20071204_In_Class_Presentation.ppt 3
What is the context?
Managers rely on salespeople for this information– What are sales going to be?– Who is buying? (What? How much?)
The manager represents the company– How much should the company produce?– Strong incentives to not over-/under-produce
We see successful sales organizations in reality– Salespeople cooperate with their managers
Salespeople represent the “front lines” of most profit-making companies– Most interaction with customers– Privy to the most information “on the ground”
Yale School of Management 20071204_In_Class_Presentation.ppt 4
Where’s the problem?
Managers do not have the same incentives– Growth of company is very important– Maximize efficiencies– Minimize wasted effort/production (losses)
Sales force has strong incentive to sell more– Salespeople typically receive two-part (or more complex) compensation schemes
- Big bonus incentives for matching/exceeding sales targets- Some bonus part of salary expectations
Managers also have to set targets– Salespeople often have better information– Revealing information can compromise the salesperson’s
bonus
Yale School of Management 20071204_In_Class_Presentation.ppt 5
Motivation for Experiment…
Everyone has an incentive not to cooperate
Salespeople would like to keep information to themselves– Make targets lower– Earn larger bonuses
Managers would like to know more information– Make accurate targets– Run the company most efficiently
- Sales force bonuses are also a “cost”
But, in reality, companies survive Is there equilibrium behavior? What mechanism drives this?
Can we study the problem in a lab setting?
Yale School of Management 20071204_In_Class_Presentation.ppt 6
Experimental Setup: The Base Case
Step 1: Salespeople see a private signal, and generate a sales “estimate” which is provided to their manager
Step 2: The Manager creates a sales target based on that signal – (As well as information observed in prior periods)
Step 3: Payoffs are calculated and observed by both the Salesperson and the Manager
Salesperson's Total Salary $10k
$20 (Actual Sales Sales Target) if Actual Sales > Sales Target
0 otherwise
Bonus
Bonus
| Actual Sales Sales Target |Manager's Total Salary $10k $4k 1
Actual Sales
Yale School of Management 20071204_In_Class_Presentation.ppt 7
Experimental Setup: Advanced Cases…
Used to make the problem more realistic
Case 1: Salespeople allowed to (privately) invest extra effort to grow sales– Potential for increasing bonus
Case 2: In addition to Salesperson’s effort, Manager now allowed to provide “side-payment”– Manager makes (binding) decision up-front– Salesperson receives incentive to tell truth
- “Insurance” against lost bonus- Proxy for other benefits that a manager may bestow in reality
Experiment proceeded in stages– Allow subjects time to understand incentives
(learning)
Yale School of Management 20071204_In_Class_Presentation.ppt 8
Results: Did people get the idea?
0%
5%
10%
15%
20%
25%
30%
35%
Normalized Shading, Adjustment and Effort Exerted(Normalizations relative to Signal, Estimate or relative to Max Allowable Investment - $1k, respectively). N=8
Base Case With EffortEffort &
Side-payment
% Shading (relative to Private Signal)
% Adjustment (relative to Estimate)
% Effort (relative to $1000 max)
Yale School of Management 20071204_In_Class_Presentation.ppt 9
Results: Were results tending to stability?
0%
5%
10%
15%
20%
25%
30%
35%
40%
1 2 3 4 5 6 1 2 3 4 1 2
Normalized Shading, Adjustment and Effort Exerted(Normalizations relative to Signal, Estimate or relative to Max Allowable Investment - $1k, respectively). N=8
Base Case With EffortEffort &
Side-payment
% Shading (relative to Private Signal)
% Adjustment (relative to Estimate)
Tit-for-tat?
Stability?
Outliergroup
No s-p in last period
Yale School of Management 20071204_In_Class_Presentation.ppt 10
Results: Were results tending to stability?
0%
5%
10%
15%
20%
25%
30%
35%
1 2 3 4 5 6 1 2 3 4 1 2
Normalized Shading, Adjustment and Effort Exerted(Normalizations relative to Signal, Estimate or relative to Max Allowable Investment - $1k, respectively). N=8 (N=7 in Effort & Side-Payment Case)
Base Case With EffortEffort &
Side-payment
% Shading (relative to Private Signal)
% Adjustment (relative to Estimate)
Outlier group removed
Yale School of Management 20071204_In_Class_Presentation.ppt 11
Results: No changes in manager accuracy…
0%
5%
10%
15%
20%
25%
30%
35%
1 2 3 4 5 6 1 2 3 4 1 20%
20%
40%
60%
80%
100%
Normalized Shading, Adjustment and Effort ExertedN=8 (N=7 in Effort & Side-Payment Case). Min Accuracy 73%, Max Accuracy 96%.
Base Case With EffortEffort &
Side-payment
Beh
avio
ral
Metr
ics M
an
ag
er A
ccu
racy
Yale School of Management 20071204_In_Class_Presentation.ppt 12
Results: Within-group variations…
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
A B C D E F G H A B C D E F G H A B C D E F G H
Within-group Variation: Shading & Adjustment(Normalizations relative to Signal or Estimate, respectively). N=8
Beh
avio
ral
Metr
ics
Base Case With EffortEffort &
Side-payment
+142%
% Shading (relative to Private Signal)
% Adjustment (relative to Estimate)
Yale School of Management 20071204_In_Class_Presentation.ppt 13
Results: Within-group variations…
0%
10%
20%
30%
40%
50%
60%
A B C D E F G H A B C D E F G H
Within-group Variation: Effort Exerted/Side-PaymentsN=8. Y indicates offer of side-payment in round 1 (of 2). No side-payments were offered in round 2.
With EffortEffort &
Side-payment
$ E
ffort
“In
veste
d”/$
1000 Y Y Y Y Y
Yale School of Management 20071204_In_Class_Presentation.ppt 14
0%
10%
20%
30%
40%
50%
-20% -10% 0% 10% 20% 30% 40%
0%
10%
20%
30%
40%
50%
-20% -10% 0% 10% 20% 30% 40%
0%
10%
20%
30%
40%
50%
-20% -10% 0% 10% 20% 30% 40%
Results: Behavioral Correlation
Shading & Adjustment Between TreatmentsN=8. Red = Base Case; Blue = Effort; Green = Side-Payments (Some data points not on chart).
% A
dju
stm
en
t b
y M
an
ag
er
% Shading by Salesperson
Treatment or learning effects?
Yale School of Management 20071204_In_Class_Presentation.ppt 15
Results: Review
Considerable within-group variation
However, some reason to believe that there is a “stable” outcome– Even in base case, coordination seems to evolve– Very low shading/adjustment in side-payment case
- After excluding outliers
Shading and adjustment are positively correlated– Means that experiment is being understood– Unclear as to whether learning or treatment effects are taking place
Most significant tests are rejected (n too small)
Not enough time for “stable” behaviors to evolve (t too small)
Yale School of Management 20071204_In_Class_Presentation.ppt 16
Critiques and Advice…
Experimental setup– Noise in private signal may not be necessary– Insufficient inclusion of “growth” motive
- Currently “normalized” out – is this an oversimplification?– Random walk DGP
- Would an extra condition (Targett>Targett-1) be more appropriate?
In analysis, I have not (yet) discussed payoffs to either group
Other items?
What am I missing in the experimental setup/analysis?
What mechanism might help sustain ‘equilibrium’ behavior observed in reality?