Difference between revisions of "AY1516 T2 Team YSR"
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Revision as of 17:42, 12 February 2016
Contents
Project Motivation & Objective
Overview
Ever since the dawn of the Age of Analytics companies have used data to drive decision-making for organizational functions such as operations, sales, marketing, and finance. Human resources, however, has traditionally been an analytical backwater (only 5% of HR decisions are based on analytics). This is being disrupted by a new wave of analytics – people analytics.
Motivation
People analytics is a rapidly growing area of business intelligence and big data technology. It uses various facets of people-related data to optimize business outcomes and solve business problems. The application of people analytics with new techniques such as predictive behavioural analytics has helped organisations to save millions of dollars while improving attrition rates, employee engagement and identify underlying training requirements.
TrustSphere is the widely recognized market leader in Relationship Analytics. TrustSphere enables forward thinking organizations to unlock the inherent value of their own networks using next generation technology. The solutions provide real-time intelligence and insights which help clients across the globe improve salesforce effectiveness, enterprise-wide collaboration and corporate governance.The motivation behind this project is to assist TrustSphere in verifying the effectiveness of their product through other statistical techniques.https://www.crunchbase.com/organization/trustsphere#/entity
Scope
Access to TrustSphere’s datasets will allow the team to build a system from scratch using previously unused raw data to better understand turnover and attrition rules.
The minimum research points we would like to address:
- Understand the number of relationships an employee will have at different periods of time in his or her working life
- Measure the speed of growth at which employee relationships grow in a company
- Correlations between the sizes of internal and external relationships employees have
- Through social network analysis, calculate the likelihood of an employee in an informal group leaving a company upon the exit of another closely tied employee
- Identification of metrics that can help predict the likelihood of an employee leaving
It is important to note that the scope of this project is fluid and can be furthered to address additional questions TrustSphere might have regarding the dataset.
Data
The dataset given to us was pulled from the outlook (mail server used at TrustSphere) database. The data basically is an exchange of emails. The dataset consists of 890,000 email exchanges and 13 variables out of which we found the following 8 to be relevant:
- Date: includes the date and time of a particular email being sent
- Originator: identifies the originator of an email thread
- Direction: indicates the direction of the email sent
- Domain Group: identifies the company to which an email address belongs to
- Inbound Count: number of emails being received from a particular address
- Outbound Count: number of emails being sent to a particular address
- Size: the size of email in bytes
- MsgID: unique identifier of a particular email thread
Methodology
An organization’s real-time communication logs are a rich source of data, which when analyzed can give unparalleled levels of insight into the relationships that its people and their teams cultivate amongst themselves and their clients, stakeholders and suppliers.
We look to create an algorithm that generate scores for each relationship to identify the strength of a particular relationship or group of relationships. Using statistical analysis and advanced social network analytics on this communication data while paying attention to the relationship scores, we look to create the following interactive visual dashboards:
Dashboard 1
Relationship map for single individuals, groups, departments and the entire organization
- This relationship map will categorize relationships of individuals or group of individuals by:
- Relationship strength: a score prescribed to each relationship between individuals or group of individuals based on the number of emails exchanged and the time frame in which the emails were exchanged.
- Relationship speed: a metric that describes the speed at which relationships are formed by individuals or group of individuals in an organization. group of individuals in an organization.
Dashboard 2
A management view dashboard that illustrates important people related information
This dashboard will contain the following information:
- Employees at high risk of attrition
- Status of key relationships
- An assessment of performance of an individual or group based on the strength of their network within and out of their company.
Project Timeline
References
http://www.mckinsey.com/insights/organization/power_to_the_new_people_analyticsa
https://en.wikipedia.org/wiki/People_analytics
https://www.crunchbase.com/organization/trustsphere#/entity
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