Banish_Office_Politics3.pdf

Banish Office Politics – HR
Analytics
Dr. Manish Gupte

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About Dr. Manish Gupte

PhD Economics (contract theory – Labor economics), Purdue
University, 2009

BE Computers, Pune University, 1999

8 HR interventions and/or advanced discussions – Banish
Office Politics

Inter-disciplinary work in biostats, dual use warefare,
audio/video tech, cryptoanalysis, econometrics, time series,
prediction markets, analog computing, old science

Peer and Subordiate appraisals –
language groups

This intervention was at Gauri Technologies, Pune. The mgmt
actively involved and we analyzed their appraisals data. Earlier
mgmt was saying they use peer appraisals only for developmental
purpose but deceptively used it for pay and promotion. So, sauve
employees succeed and hard workers suffered

Analysis showed employees inflated peer rating s if both were
Marathi or both were non-Marathi

The bias was more in ‘knowledgebility’ (difficult to verify
intelligence) than in ‘timeliness’ (easy to see project plans tracking)

language groups

We first did t-test and made sure the bias was not a
result of random data and it was systematic

We pulled out the names of raters who had most
bias. The mgmt remembered interactions with those
‘suspects’ and verfied

Then the director gave a speech to all employees
and said this is not right, this is not our culture

language groups

Then we conducted 1-on-1s. The mgmt did not tell what info they
had and caught employees lying like hidden cameras catch
theives. The employee does not know what manager knows so
when he lies, sometimes the manager has a clearly different
observation and he gets caught

Then employees realized this and made event when they said
‘pls give us old trust system we will not lie’ and productivity
improved lots

We made working paper out of this

Compete and Cooperate

Again at Gauri tech after we realized ppl were not completely honest with incentives
and ratings we said competition could be meaning giving less useful feedback

So we rewarded ppl who gave useful feedback about others (which resulted in
demonstrated improvement of peer) and on other dimensions the employees
continued to compete – we got compete and cooperate

In 2003 I analyzed companding and bands for performance pay – if bands are too
narrow then no helping and going up in pay is there (no help to pull peer down), so
bands should be made so that there is no incentive to not help

Narrow bands mean no helping, very wide bands mean no effort by employees as
all get pay, optimal bands mean helping and effort

Village folks forming big group and
wasting time

This was done in a IT company in Hinjewadi

Employees were just ‘partying all day’ and mgmt wanted
to put surveillance

I recommended record keeping – planned time for task
and actual time take for task

First employees finished task, found actual time and then
simply copied that to planned time. Zero delay claim !

Village folks forming big group and
wasting time

So, we said we will give training based on inadequecies
based on this planned/actual time data. We will find
better performers

Some ppl gave data but again same syndrome

Then we said we will round off delay to half hour or one
hour and not go after every minute – then all employees
gave data and we avoided heavy surveillance

Talent not valued only output

Again same Hijewadi company

There is standard effect in labor economics – better
talent pretends to be dull to avoid hard work. The mgmt
knew this and also if we encourage talent then ppl claim
to be smart and avoid work. So mgmt was giving value
only to output. So ppl were not using talent. After I said
give some weight to talent also as you consider output,
the productivity improved

MIS system

At 2 of my clients, mgmt got an automated MIS system and all
tasks had to be done from that only. So time taken on tasks
was recorded

My client went after every minute and started monitoring lunch
and coffee break times and ‘put a pistol to employees head’

I said consider little humane approach. Give them targets
which are 10% better than current and every week keep
adjusting targets based on previous week

MIS system

Also we found out who is good at what task and
where he or she needs training

Earlier, only few employees worked hard, but after
this humane approach everyone’s productivity came
to same level – the average level of all employees –
the average handling time. Going after every minute
only hurt, but winning hearts is easy

World cup like tournament

In this advanced discussion, the client was saying
their employees complain only ppl with big
university, big past experience, big name, big
sponsor, etc get promotions

So, we said two employees will work on same
task – 2 components of same task and we will
record quality, timeliness, innovation, initiative, etc

World cup like tournament

As both employees had same task both did well if task
was easy and both did bad if task was hard

But the difference of the two records show how much
was employee’s role in the output. We could remove
project uncertainity and find out employee contribution.
Again all ppl happy and work hard. Then records like
world cup and comparision before appariasals

Middle manager probs

In this advanced discussion, the mgmt was
saying middle managers have to affinity to
company so they create problems and care
only for self and do politics. So no middle
managers. They give pay to
employees/associates only when the company
gets project and money. No desk pay

Middle manager probs

I then asked him are associates able to handle this
level of stress and uncertainty

He said all are very experienced and satisfied
employees who are not after big money

He then said yes, he will screen more for this
trait/previous experience as pure employees will
get stress and leave

Attrition

This was for Mumbai MNC

They gave details of ppl who left the company

Cox proportional hazard survival model showed ppl with high
market value left, all other factors were general to industry

Ppl who have better outside value leave. So mgmt said they
will take outside option into account. Policies cant always be
employee by employee and there is range for pay but attrition
has to be considered in this calculation

Attrition

This was for Pune MNC

They gave details of ppl who left the company. Mgmt
feared top talent was leaving

Again survival model analysis showed employees
completed their average time and left

This time was industry standard only, nothing
company specific

Employee satisfaction survey
analysis

This was for Mumbai MNC

Analysis of employee engagement survey data
– I dont remember much, long time ago. Mostly
all wanted some better training

Thanks a lot !!!



Banish_Office_Politics3.pdf

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