The Analysis Exercise on a Real Life HR Data

8/13/2019 The Analysis Exercise on a Real Life HR Data

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2013 Ideal Analytics Limited.

The Analysis exerciseon a real life HR data


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Why is such a behaviour need to be known?Knowing salary movement for a short term and trying to

figure out short term predictions is not enough! A Long term behaviour and value-predictions help long term

budgeting and planning.

Salary is the most crucial component that changes every year and to

manage the entire scheme is a big & full time job, But planning it many a

years earlier and measure the running discrepancies and rectifying

them is another serious research activity.

Objective treatment of Salary has become the problematic all along.

A general case study research for about a decade for a set of

employees would be a respectable data set.


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Why is such a behaviour need to be known?

Our endeavour ->To propose an empirical schema obtained from the data-

Exemplifying that the normal conceptions of regularity in

salary is failing and then to conceive of an idea for an objective

salary function. [ A reasonable approach would be to capture

ten years of data - very effective in traditional productioncompanies where attrition is less but the salary increases per

year are not insignificant] (but for want of data deal here with

this data set of four consecutive years salary values for a

technology company)


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Salary is individual-

based, and yet groupings[dimensions] on the basis of

band,

designation,

department,

skill-set etc

do bring-in very interesting aspects for right decision making.

A level up in interest could be the salary hike justification with

respect to the rating of an employee.

Roll this metric up the hierarchy with different aggregations.

The problematic within Salary management


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This graph computes the total salary growth in four yearsscaled by the skill-set

Depiction1 of the First Set Inference -Examples


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This is salary growth compared with respect to the first years

salary scaled by the tenure of the employee

Depiction 2 of the First Set Inference



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This is the current salary status depicted by the age of the employee.

Depiction 3 of the First Set Inference



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This three-in-a-set gives the general idea of which age-group,

skill-set and retention sector has been valued by the

company.

1. There is a high tendency for the company to get en-streamed in a particular direction and conscious effort to

steer away from that direction or navigate the company

either in another direction or to give it a generalist get-up.

2. What one diagram may not help in these creativedecisions, a combination of depictions may come to aid.

Inference from the First Set



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Add to this another set of depictions that would measure the salary growth by

various dimensions:

This one is quite interesting. The salary growth is weighed up by different skill sets and then they aremeasured against the ratings given to the employee performances. The depiction clearly shows that

some very discerning skill set have received the same rating P4 in that might attract employees with

other skill sets to flock, if that is a welcome issue is to be decided by the project and HR managers with

fair consultation with the highest authorities, strategic management, finance and budgeting and planning

department authorities.

Depiction 1 of the Second Set Inference



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The following ones are actually are to be judged in combination:




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Clearly some locations, some functions, some job family had been benefitted

more than the others. These aspects might trigger different kind of decision

making and those decisions need to get supported by this type of analysis. These

are known analyses that are very essential, basic and most popular.



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Perquisites are a very important aspect within the salary or CTC [cost to

company]. They need to be vetted against the salary and fathomed outwhich particular range are provided what kind of facilities and which kind

need it most.

This is the band wise distribution and shows that some particular mode of

provided-facility goes naturally with some band. These are food for further

decision change.



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The advanced analyses start with calculating the growth

coefficients.We have devised a coefficient as the difference of

salaries between the last and the first year and then

divide it by the current salary.

An alternative coefficient has also been used but could

have very high significance is the average of the salaries

by the current salary- the values would obviously differ but

that is the job of the analyst who would like to see exactly

a specific behaviour.

The average of the salaries would be important forgross and macro considerations whereas the difference in

salaries would focus down on the growth factor with

respect to a reference yearssalary.

AdvancedAnalysis



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Depiction 1 of the Third Set Inference



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This set of depictions show some negative values.This clearly shows that among the three years the salary growth did

not have a monotonically increasing rate.

One year had a high hike and the later years had lower hikes.

This also shows that among the four years that kind of high increase

only occurred once.

Could and should we have captured data for a decade or more we

might have seen more points of inflexion or more modal distribution in

salary increase graph.

In that kind of a scenario more the ups and downs would have been

more would have been the volatility and one had to find the

explanations from external sources like general economy, or generalindustrial scenario.

Inference from the Third Set



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The most interesting depiction has been calculated with a creative formula.

We calculated the first differentials of the salaries of every employee betweenyears, so we got 3 such first differentials out of the four years salary that are

captured.

Then we computed the differentials among the three, we call second

differentials and still did not find a constant rate.

We went up to the last that is the third differential too.

We then compared the average of the second differential with respectto the third differential as per mathematics the average should have

been three times the third differential- the graphs however says a

different story- this immediately infers that the salary increment in any one

year as opposed to the others did not follow a well conceived pattern, there had

been some passionate reasons or some exogenous reasons.

A differential analysis is an almost universally important method in fixed time varyinganalysis of a fact with respect to multi-dimensions.

For huge number of actors in the data set[ in this case employeesindividual salary]

one works smart in moving step wise down from a macro picture to a micro one.

A Creative Formula



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These are some preliminary and fast analyses artefacts showing that an

analyst can run her analysis on ad-hoc and flexibly alternative generating

bases.A business analyst of the line of business is the best candidate for

conceiving her own measurements and depict in dashboards or reports.

Further mathematical calculations are always possible, say for example

we have figured out a first order differentials, second and third order

differentials, with a huge data one can easily set up an objectivepolynomial function and then in turns of incremental data can simulate the

coefficients with error functions.

These objective functions can be made to go through step wise

regression analysis to figure out which dimensions are significantly

effectively in the long term objective salary function.These functions can then be aggregated through ideal analytics [

the Z value] and a macro salary objective function can be obtained to

have a normal benchmark for long term planning and budgeting

purpose.

Conclusion:


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The Analysis Exercise on a Real Life HR Data