Predicting Employee Churn: A Data-Driven Approach Project Presentation
Analytics
1. • Analytics is computational analysis of data or
statistics.
•It is used for discovery, interpretation and
communication of meaningful patterns in data.
•It also entails applying data patterns towards effective
decision making.
•It can be valuable in areas rich with recorded
information; analytics relies on simultaneous
application of statistics, computer programming and
operation research to quantify performance.
2. •Personalize customer experience: Business collects
data from different channels including physical retail, e-
commerce and social media, businesses can gain
insights into customer behaviour to provide more
personalized experience.
•Inform business decision making: Entrepreneurs
can use data analytics to guide business decisions and
minimize financial losses. Predictive analysis can
suggest what could happen in response to changes to the
business, and it helps in indicating how business should
react to such changes.
3. Streamline operations: Organizations can improve
operational efficiency through data analytics.
Gathering and analyzing data about the supply chain
can show where production delays or bottlenecks
originate and help predict where future problems may
arise.
Mitigate risk and handle setbacks: Risks are an
integral part of business, data analytics can help an
organization in understanding risk and take
preventive measures. Business can also use data
analytics to limit losses after setback occurs.
4. Enhance security: All businesses face data security
threats. Organizations can use data analytics to
diagnose the causes of past data breaches by
processing and visualizing relevant data. For instance,
the IT department can use data analytics applications
to parse, process, and visualize their audit logs to
determine the course and origins of an attack. This
information can help IT locate vulnerabilities and
patch them.
5. TYPES OF ANALYTICS
Marketing analytics: Marketing analytics consists of
both qualitative and quantitative, structured and
unstructured data used to drive strategic decisions in
relation to brand and revenue outcomes. The data
enables companies to make predictions and alter
strategic execution to maximize performance results.
6. Web analytics: They allow marketers to collect
session-level information about interactions on a
website using an operation called sessionization.
Google analytics is an example of a popular free
analytics tool that marketers use for this purpose.
People analytics: People Analytics is using
behavioural data to understand how people work and
change how companies are managed. People analytics
is also known as workforce analytics, HR analytics etc.
HR analytics is the application of analytics to help
companies manage human resources.
7. •Portfolio analytics: Portfolio Analysis is the process of
reviewing or assessing the elements of the entire portfolio
of securities or products in a business.
•Risk analytics: It helps take the guesswork out of
managing risk-related issues by using a range of
techniques and technologies to extrapolate insights,
calculate likely scenarios, and predict future events.
8. Digital analytics: Digital analytics is a set of business
and technical activities that define, create, collect,
verify or transform digital data into reporting,
research, analyses, recommendations, optimizations,
predictions, and automations.
Security analytics: Security analytics refers to
information technology (IT) to gather security events
to understand and analyze events that pose the
greatest risk.
9. PORTFOLIO ANALYSIS
Portfolio Analysis is the process of reviewing or
assessing the elements of the entire portfolio of
securities or products in a business.
The review is done for careful analysis of risk and
return.
Portfolio Analysis conducted at regular intervals helps
the investor to make changes in the portfolio
allocation and change them according to the changing
market and different circumstances.
10. Advantages of portfolio analysis:
1. Evaluation of firm’s business by top management
2. It helps to assess company’s attractiveness.
3. Raises issues related to cash flow availability.
4. It helps to assess the competitive strength of the
company with respect to market share, contribution
margin etc.
5. Communication is facilitated.
11. Portfolio analyst also known as financial or
investment analyst. Core duties or responsibilities of
portfolio analyst are:
1. Conduct investment analysis: Portfolio analyst
will evaluate the performance of client’s investment
and help these clients increase the assets and help
them in making financial decisions.
2. Track Economic trends: It is up to a Portfolio
Analyst to keep track of trends that will affect the
performance of various types of investments.
12. Create Investment Reports: Portfolio Analysts will
generate reports regarding investment values,
performances and trends and present this material to
clients on a regular basis. These reports can be
generated monthly or quarterly. These reports might
include details about investment risks, product pricing
and rate changes.
13. Portfolio analyst need to focus on the following things:
1. Preparing portfolio analysis reports
2. Recommending the best to the organization and
customers based on the performance.
3. Understanding the risk associated with the investing.
4. Maintaining knowledge of market and economic
trends.
5. Knowing various investment types like mutual funds,
stocks and bonds.