Bi hrm presentation - Using Business Intelligence for improving Human Resources Management

Using Business Intelligence for improving Human Resources Management
Vispi Munshi
Founder - ERP India
vmunshi@erp-india.com
http://www.erp-india.com
Proprietary and Confidential © ERP India – Vispi Munshi – erp-india.org 1

Today’s Agenda
- Introduction
- What is HRM (Human Resources Management)
- HRM Functions
- What is Business Intelligence
- Data Analytics
- Applying BI to HRM: Examples
- HR Metrics
- HR Intelligence System
- HR Analytics Demo
- Conclusion, Q&A

Ground Rules
- Please turn mobile ringer to SILENT MODE
- If you have to take a call, please leave the room and then start talking
- Questions can be asked any time
- Before asking question, raise your hand
- No talking with each other
- Disagreements allowed, but no disrespect
- Timeframe awareness
- Lets learn from each other and increase our knowledge

Introductions
- Full Name
- Where do you work (Company/Consultant/Student etc)
- Your job designation and responsibilities
- Any BI tool you have already used?
- Any HRM experience?
- Expectation from this workshop

What is Human Resource Management
HRM is about management of people such that organizational
goals are supported by aligning individual goals and if required
with additional people/contracts.
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Org Goals: Profits, Growth, Social responsibilites
Individual Goals: Security, Belonging, Respect, Achievement

What is Human Resource Management
Employee Productivity – Tools and know-how or skills to perform
Employee Motivation – Willingness to perform
Challenging Employees – Using creativity and innovation to further
increase motivation

Key HRM functions
- Human Resource Planning (forecast)
- Recruitment (staffing)
- Organization (managing grades and promotions)
- Training and Development
- Payroll and Benefits Administration
- Performance Appraisals
- Communications and Arbitration (Conflicts management)
- Industrial Relations (Unions)
- Alumni Relations
- Knowledge Management

What is business intelligence?
Business Intelligence is a term generally
used to identify a class of Information
System applications useful for supporting
operational, tactical and strategic decision
making of a organization.
BI deals with producing (and presenting)
Accurate, Relevant and Timely (ART)
INFORMATION from integrated data.
Not Accurate: Users loose faith in system
Not Relevant: Users ignore the system
Not Timely: Users find alternatives to the
system

Benefits
- Sales Optimization
- Cost Reduction, Planning and Budgeting
- Inventory Optimization
- Purchase Optimization
- HR Optimization
- Production / Manufacturing Optimization
- Demand Forecasting
- Market Competitive Analysis and Customer Relationship Optimization
- Supply Chain (Sales and Distribution) Optimization
- Most Important is ART Information to support all levels of Decision Making
- Aim is to replace/reduce Excel based Analysis

BI System Anatomy
BACK-END
Data Collection and
Integration Tools
Forecasting,
Mining
ERP
Ecomm
CRM
Files
….
Data
Mart
PRESENTATION
FRONT-END
Analytics, Visualization,
Dashboards, …
DISTRIBUTION
Alerts, Email, Mobile,
Intranet ….

Backend BI Tools: Used for collection, integration and consolidation
of data from various sources.
Intermediate BI Tools: Allows users to create forecasts and identify
trends (data mining) from the data.
Frontend BI Tools: Provides users with a interactive and intuitive
interface to view the information generated.

Data Analytics (New Age Decision Support Systems)
- Based on multi-dimensional view of data (cubes)
- Pivot Table demo
- Features for drilling in and across data
- Slicing and dicing of data
- Graphics capabilities
- Similar to Excel
- Exception reporting
- Data Analyst would use such tools and create Reports/Analysis/Graphs (objects)
- These objects would be supplied to Executives using Dashboards, Alerts etc.

Multi-dimensional Data

Data Analytics Tools in Market
High-end: Business Objects, OBIEE, Microstrategy, …
Open Source: http://en.wikipedia.org/wiki/Business_intelligence_tools

Dashboards and Alerts
- Dashboards are collection of reports/analysis/graphs
- Alerts are specific events that the system finds and sends a email/sms etc to
the executive
- Key Performance Indicators (KPI’s) can be set and linked to alerts
- Linking across objects provides executive with ability to go through the
generated information in a very intuitive manner

Data Mining
- Also known as KDD (Knowledge Discovery in Databases)
- Involves use of large data sets
- Involves uses of Statistical Methods, Database Systems and Artificial Intelligence
- The objective is to discover patterns or knowledge from existing data
- Involves four step process: Data Preparation (classification), Hypothesis (user provided
guidance), Discovery (of knowledge) and Validation (of discovered knowledge against
hypothesis)
- Techniques: Classification, Clustering, Association Rules, Regression
- Predictive Analytics
- High end tools: SPSS, SAS, …
- Open Source: http://en.wikipedia.org/wiki/Data_mining

HR Metrics
- Headcount by various dimensions like demographics, location,
function, grades etc
- HR Costing by function, location etc
- Benefits Costing
- Costing of HR functions (recruit, train)
- Skills by location, function, grade etc
- Employee Performance by function, demographics, location etc
- Employee Turnover by function, demographics, location etc
- Equity holding by employees

Using BI for HRM
- Example 1: Predicting which Employees are likely to Perform
Well.
- Example 2: Predicting which Employees are likely to leave
(turnover)
- Example 3: Recruiting Intelligently based on Performance
Records
- Example 4: Forecasting Staff Requirements based on Organization
Goals, Turnover Prediction, Staff demographics

Using BI for HRM : Predicting which employees are likely to Perform Well
Past Employees Records
-Demographics
- Education, Location
- Skills, Trainings
- Duration, Grade etc
Past Performance
Records
Current Employees Records
-Demographics
Current Performance
Records
Create Model
(Association Rules,
Clustering
Prediction
Algorithm
(Classification)
Performance Model
(Decision Tree,
Neural Network)
Performance
Predictions
Analytics

Using BI for HRM : Predicting which Employees are likely to leave (turnover)
Past Employees Records
-Demographics
- Skills
- Salary, Benefits
Past Employees
Records
Current Employees Records
-Demographics
- Skills
- Salary, Benefits
- Duration, Grade etc Prediction
Create Model
(Association Rules,
Clustering
Turnover Model
(Decision Tree,
Neural Network)
Algorithm
(Classification)
Turnover
Predictions
Analytics

Using BI for HRM : Recruiting Intelligently based on Performance Records
Employee Profiles
- Location
- Demographics
- Education, Skills
Employee
Performance Records
Create Model
(Association)
Model (Decision
Tree)
Shortlisting

Using BI for HRM : Forecasting Staff Requirements based on Organization
Goals, Turnover Prediction, Staff demographics
Consolidation
Organization Goals
Turnover
Predictions
Staff Demographics
Staff
Requirements
Predictions

HR Intelligence System
BACK-END
Data Collection and
Integration Tools
ERP,
HRM
Industry
data
….
HR Data
Mart
HR Planning
Recruitment
Training/Skills
HR Costing
Knowledge
Management

HR Analytics Demo

Q&A
Thank You
vmunshi@erp-india.com
98250 11489

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