Follow by Email

Sep 4, 2014

Big Data Analytical Services Environment (Success Struggles)


Observations are author's personal views after observing big data space over a period of time, he can be reached at mavuluri.pradeep@gmail for further discussion on this topic.

Jun 3, 2014

Operational HR Analytics - Moving from Manger Centric to Employee Centric

Below figure is depiction of one of those realistic patterns compendium with respect to the industry data which states why organizations should not be 'manger centric'.

Author has worked extensively in the HR Analytics and can be reached at mavuluri.pradeep@gmail for more details.

Mar 9, 2014

Analysis of HR Emails

This study has made an attempt to understand, what HR's in a day dealt with at different working hours, by analyzing their emails from a particular organization. Sample size of the study consists of 7 HRs emails who are located at two different locations of the same organization in a country and for 15 different days that are selected randomly from a quarter.

After sanitizing the data and removing unnecessary characters and punctuation's, data has been prepared and transformed in such a way to get frequency of words used by each hour. A day has been divided into seven categories viz., first hour, second hour, etc. Correspondence analysis has been chosen keeping in the mind for graphical representation of the processed data (below is the output - prepared for presentation purposes). All analysis has been carried out using open source statistical computing tool "R".

Analysis tells us that, 'First' hour of the day's had always been dealt with HR policies, queries, and aspects related to appraisal, roles and productivity (higher number of aspects (5) in first one hour). And, 'Second' hour went completely for addressing leaves and grievances of the employees. Coming to 'Third' the turn of reviews and offers, however, both second and third dealt with less number of aspects i.e. only two. Surprisingly, none of the aspects at the fourth hour. Moving to fifth hour again good number of aspects (4) have been dealt viz., payroll aspects of the employees, diversity and safety in the organization and about interviews. Sixth hour went for addressing training needs and calendar related aspects. Last hours (2.23 hours on average) has been dealt with development, retention and performance aspects.

Author has worked extensively in the HR analytics and can be reached at mavuluri.pradeep@gmail for related discussions.

Jan 13, 2014

Operational HR Analytics - Application to Attrition

As employee attrition continue to be expensive for organizations; businesses demanded increasing flexibility as interest in what can be done with Human Resource (HR) data and intensifying opportune in its preparation/planning are gaining pace, that, directs towards operational HR analytics.

As evident from above figure, reports (basic) are entirely backward looking aspect with less return on investment (ROI). Current phase is result of availability of increase in data across the organization and all-encompassing information technology progress that helps to predict what went wrong and integrate them with future outcomes. Majority of businesses today though uses predictive analytics for their organizations, return on investment had been slowed down and not effective as these analytics are not yet in the stage of adaptive application i.e. real time to the organizational operations/needs.

In current state of human capital management where dynamic workforce requirements, acute competition for talent, rapid technological advances not providing enough time to ingest for adoption and national/natural upheavals in one part affecting overall business in the other parts requires operational analytics that can foresee rising business needs of an organization. My experience with the help of open-source statistical computing environment viz. R, towards developing such environments had been yielding higher return on investment for businesses.

Author has worked extensively in the HR analytics and can be reached at mavuluri.pradeep@gmail for more details. 

Oct 19, 2013

Indian Car Brand Perception Survey Report

A recent survey during current festive season was done on seven different automotive brands and taken there preferred attributes for a purchase/like. The underlying dimensional graph characterize how customers differentiated between attributes+.
Following are key observations: 
It seems people are paying less importance to “price” factor, however, aspects like good value for money, parking space, servicing attributes work towards existing dominant brands. Coming to newer brands, attributes viz., performance, attractiveness, technology, safety, suitability, zippy (quick and energetic) driving their purchase/like. Two other brands are preferred for their sporty, venturous, exterior looks, athletic and stylish nature.
+Survey data comes from a specific Indian City.

Jul 4, 2013

Appropriate Training Objectives for Strong Analytical Foundation

Organizations likes to invest in developing their analytical talent in such a way that they can compete for global competencies, for that training objectives should be appropriately identified and cannot ignore strong foundation. Herein, they should cater for both semi-skilled (graduates of M.S.) who has awareness but lack of domain/practical experience and non-skilled (other graduates). Below are the three important objectives for strong analytical foundation.
  1. Ability to link learned analytical capabilities to real-world situations.
  2. Knowledge of basic analytical concepts, and their applications.
  3. Obtain cognizance to synthesize the constituents of an analytical project and convey the results in a clear manner to whom so ever.
Reach me at for more details. 

May 21, 2013

Time Period for Analytical Positions Recruitment.

Though having rough estimate of how much time each analytical position recruitment takes (i.e. due to experience in the filed); thought of giving a quantitative touch using a real sample. Herein I would like to thank 13 recruitment agencies that provided the requested details. Most of the sample belong to India recruitment only.

Below figure provides average time period i.e. number of months to fill a said position for analytics. Wherever possible we have provided domain (Retail/CPG & BFSI) specific time as our sample has around 30-34% of data for these domains. 

May 18, 2013

R (Web Server) Solutions - Amplifying Artichokes

Every month I see one or more new R based web server solutions coming into the market, sight seeing some of them thought of sharing one of my old architecture map manifested to the client long back in early 2009 (good to see quick spreading of scalable and customizable open source statistical computing tool in the market).

Please feel free to reach me at for more details.

May 16, 2013

Implementing some BootStrap stuff in R

“The bootstrap is a computer-based method of statistical inference that can answer many real statistical questions without formulas”

  (From "An Introduction to the Bootstrap" by Efron and Tibshirani, 1993)