The Direct Impact Of People Data Commerce Essay

Published: Last Edited:

This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

HR analytics is like demonstrating the direct impact of people data on important business outcomes, the reality is that organizations already spend significant dollars on employees. In the business today If HR wants to become a strategic partner in the organization it needs to develop measure how human capital decisions affect the business and vice-versa. HR Analytics is an entirely new class of systems that aggregate not just HR but company-wide data, including financial, customer, and supplier information, for exploration, analysis, and presentation. HR analytics supports rapid, fact-based decisions backed by quantifiable, accurate information and defensible forecasts.However despite the strong theoretical backing to support its benefits organizations today face several challenges in its implementation . Issues range from culture to individual mindset to technology space and top management involvement. The key to all this is to change the organizational mindset both at the broad and the individual level.

Many vendors have emerged in this space given the tremendous growth potential in this space each competes with cutting edge technology. However it has been observed that newer players for example the HR consultancies are revamping the analytics approach beyond metrics sores to value propositions which defines the next gen HR.

However the broad agenda is to explore whether or not organizations today are ready for the change though the topic in question is specific to HR but unless the organization adopts an analytics approach in all its spheres mere department wise implementation can never get a strong foothold in the workspace.Furthermore what is critical is whether the organization has the right talent to execute and apply the change better technology raises the pressure on HR to hire more skilled employees to cope with the technology.


Human Resources Analytics provides organizations with a comprehensive analysis on HR initiatives and workforce performance. It integrates data from across the organization value chain changing silos of information into actionable insight.

For example, with HR analytics managers can improve their understanding of the impact of compensation on employee performance by correlating total compensation with performance metrics and turnover metrics. All users receive relevant information directly through customized metrics, and alerts. It is a modular component of Business Intelligence Applications-pre-built analytic solutions to provide robust financial information across the value chain to enhance strategic analysis.

HR functions are found to collect data on their efficiency only and not on the business impact of their interventions. If HR wants to become a strategic partner in the organization it needs to develop measure how human capital decisions affect the business and vice-versa

HR analytics is like demonstrating the direct impact of people data on important business outcomes, the reality is that organizations already spend significant dollars on employees (Bordeau and Ranwiad, 2001). The problem isn't that senior executives are not willing to invest in people. The problem is that those investments are not backed by quantifiable data to justify their worth.

Identifying the need for HR Analytics

Many recent studies argue that HR needs to become a strategic partner. Recent research suggests, however, that HR is not making much progress toward becoming a strategic partner despite the belief by HR professionals that it should (Lawler. & (2003a). Because of the growing importance of human capital in determining organizational effectiveness, HR can play a key role in developing and implementing corporate strategy and become a high-value-added part of organizations (Lawler.E.E. (2003)).

HR as a Strategic Partner

HR as a function if it can perform strategic analytics is most likely to be positioned as a strategic partner. Having analytic data about the strategy of the organization is a powerful way to achieve the tag instead of maintaining a record of the HR function alone . Thus it appears that "all" HR has to do to become a strategic partner is to develop better HR metrics and analytics with respect to organizational effectiveness and strategy.

Accommodate evolving organizations

To become a strategic partner HR must be able to analyze information in ways not discussed or looked into previously. For instance, "How many employees do we have enterprise-wide?" , "How many employees are on a sabbatical/Medical leave" , are insufficient questions for analysis. What HR Analytics does it pulls this information from all sources, summarizing the information, and combining it in a way that accurately and comprehensively reflects a true headcount. In the virtual era where organizational spread goes beyond the geographical office space a robust data set which gives all required information within no time on a mouse clickcan help HR make decisions strategically rather than reactively.

Build business cases supported by metrics

Effective HR analytics helps to analyze metrics against ad hoc analysis as well as pre-defined measures. For example, one may want to compare turnover as it relates to voluntary and involuntary separation, and churn. One may then want to calculate the frequency of occurrence of each type of turnover based on employee demographics. With this kind of metric-based analysis, it becomes easier to determine how one can become the employer of choice, motivate best efforts, inspire employee loyalty, and strategically achieve world-class customer service. This also helps to measure the financial effectiveness of ongoing HR interventions and major projects, such as restructuring or mergers/acquisitions.

Anticipate and respond to changes

Anticipating changes one of the most difficult challenges organizations face. Traditional accounting methods that focus on what happened in the past to predict the future cannot be relied upon in a rapidly changing economic environment. HR analytics enables organizations to build models that statistically validate behaviors as well as look for unusual patterns in data.

Taking one of the most common issues facing HR: voluntary turnover. This unforeseen turnover imposes a tangible increase in recruiting and training costs plus the intangible costs associated with the loss of knowledge capital. For these reasons, it is important to measure and predict turnover, understand factors attributing to it, and design programs for controlling and preventing it within targeted talent/knowledge levels gives the organization a strategic edge.

HR analytics can deliver reports that measure turnover and simultaneously portray relationships among certain employee characteristics and the eventual voluntary termination. Once the behavioral characteristics of those employees most likely to leave have been identified and established, it becomes feasible for the department to accurately anticipate changes and adopt plans to prevent the same. Succession planning can also be made more effective.

Compete through HR

Competitive pressures are reaching HR departments, but how does the organization know where it stands, unless they regularly, frequently, and objectively measure organization´s performance against competitors´ benchmark data? This information is essential for proactively managing employee relationships - particularly for the top talent that is most likely to be poached. The metrics are customized to suit company´s own unique requirements, but often they may include some of the following common measures: turnover rate , return on investment (ROI) per employee, cost-per-hire and other similar performance indicators to support strategic business decisions. The ability to compare internal HR metrics with the external benchmarking sources further enhances the value of workforce planning and how HR executives can validate the contribution of HR to corporate goals.

Bottom Line value of HR Analytics

An irony of the Internet age is that although on the surface it pretends to reduce our dependence on Humans deep inside it actually refurbishes the need for irreplaceable talent to manage the same. It has been noted that nowadays an organization´s real value resides in the willingness and ability of its people to share their intelligence, skills, collective experience, attitudes, and abilities. Employee costs often exceed 40 percent of corporate expenses, this carries significant implications for human resources executives. Technology initiatives in the HR sphere have largely focused on the mere automation of clerical and administrative functions such as self-service benefits administration payroll, resume scanning and filtering and succession planning. These systems have delivered measurable value however the big question is that larger challenges remain. As organizations undertake the strategic step to evolve from automating HR management to managing their human resource, HR professionals face an increased and critical strategic set of requirements. It is essential to establish a clearer picture of how human capital management interventions and processes add value to the organization in order to accelerate those that add the most value towards profitability. This requires HR Analytics which involves not just HR but company-wide data, including customer, financial and supplier information, for exploration and analysis, and presentation. HR analytics supports fact-based decisions backed by quantifiable, accurate information and justifiable forecasts.

This represents a breakthrough for the HR division as a critical function. Other areas of the enterprise such as manufacturing and marketing have previously used the power of analytics to streamline supply chains or identify profitable customers and efficient inventory management. Now, that same potential would be exhibited by HR professionals. It has been observed that while working with human capital information, 80 percent of time is spent acquiring, and manipulating data, leaving merely 20 percent of the time for the much needed value-added analysis. Human capital analytics on the other hand flips this 80/20 ratio helping HR professionals identify essential insights which enable organizations to proactively apply the derived strategic human capital initiatives to meet corporate objectives.

In many respects the "Holy Grail" for the HR function is ultimately the ability to show the bottom-line impact of their activities. This is indeed a powerful way to increase HR's influence on tactical and strategical business decisions.

Kinds of Metrics

Organizations can collect three different kinds of metrics to understand and evaluate the impact of HR activities and influence business performance namely efficiency, effectiveness, and impact.

The first kind is easiest to collect and concerns the efficiency of the HR function-in particular, how well the HR function performs its administrative tasks. The metrics that can be collected in order to assess HR efficiency include productivity and cost metrics for the HR function such as lime to fill open positions. HR headcount ratios, and administrative cost per employee. A comprehensive set of metrics can be produced to evaluate HR's administrative activities that in effect evaluates it as a stand-alone business. A key issue in evaluating the data gathered with respect to HR administration concerns normative data. Multi-company databases now exist that make it possible for organizations to compare their metrics data with those of other companies. Organizations with good metrics and normative data can make a good assessment of the performance of their HR function.

The second kind of HR metrics uses on effectiveness: whether HR practices have the intended effect on the people or talent pools toward which they are directed. In the case of training and development true effectiveness metrics should offer information on whether employees build needed skills not just on participation in training programs but also on employee and management satisfaction with the training provided. Measuring only participation in HR programs offers no insight into program effectiveness. While satisfaction surveys can be a useful tool for gauging the alignment between HR services and the opinions of HR's customers, they fall short of providing the needed insights into the real impact of HR programs and practices. A potentially meaningful set of effectiveness metrics for the HR function concerns talent and talent management. In most organizations HR has the lead responsibility for acquiring, developing, and helping to deploy talent. In order to assess how well organizations are carrying out this responsibility, measures of talent quality, talent development, and talent deployment are needed. Typical metrics in this area include measures of the strategic skills and core competences embodied in the work force, as well as metrics that classify how well pivotal jobs are filled and the type of development activities that are taking place for critical talent (Becker & Hustled 1998).

Business strategies that make incorrect assumptions about the ability of an organization to staff critical jobs and develop new areas of expertise that support the strategy are expected to fail. Similarly, organizations that are not staffed with the right talent will have great difficulty implementing new strategies and organizational changes.

Finally, metrics have developing and optimizing the capabilities and the core competencies of the organization can be collected in order to measure the impact of HR programs and practices (Lawler. 2003). Impact in this case means demonstrating a link between what HR does and tangible effects on the organization's ability to gain and sustain competitive advantage. Operational effectiveness impact metrics might focus on changes in the performance of business processes (e.g. reduced defects, frequent innovations) that occur when the quality of talent or HR processes are improved.

HOW HR ANalytics works

For any organization, one of the key elements in the effective leveraging of human capital is the successful management of turnover. Figure 1 gives the workflow of an analytics summary report At a glance, the analyst can see the turnover trends. Since turnover has increased, the logical concern is ―why are people leaving? The user can drill into detail in the radar chart to see the reasons. Then, rather than look at everyone, the analyst can discover which groups are affected, quickly find the group with a disproportionately high number of employees, and see that their salaries are well below the mid-point of the competitive range. The user can drill down further to actual employee job summaries to see compensation and how it compares to peers. From this information, the analyst can begin to understand whether individual salary actions are needed, or perhaps that an overhaul of the compensation program is required. By taking suitable action, the supervisor is able to effect a change in the organization for the better.

Figure 1: Snapshot of Results : OracleHR Analytics

With its tight integration between the business intelligence environment and the transaction system Oracle HR Analytics enables organizations to close the loop of this issue by enabling action through the action framework. Oracle HR Analytics supports the organization all the way from insight to action with pervasive integration of workforce, financial, and operational data sources and guided analytical workflows. Each part of an analytical workflow is supported by pre-built reports and navigations that allow users to easily drill to further levels of detail to answer questions. Workflows capture information at the transaction line level so that users can easily drill from the summary information to the most detailed level of information required. Ultimately this allows users to not only monitor progress on addressing an issue at a high level but also to easily navigate to the right information, so that in the end any required corrective action can be proactively taken and recorded back into core systems as appropriate.

What HR Analytics Is Not

Before I proceed it is important to put a halt to some of the misconceptions about analytics

HR analytics is not the following:

Efficiency metrics/scorecards

For some, HR analytics have come down to tracking more efficiency metrics around HR activities. It is assumed that tracking efficiency metrics on a big HR scorecard is analytics. .More metrics don't add business value; tracking is merely score collection and nothing more.

Alignment Tool

HR leaders often quote that they are aligned to the business. If the sales function is hiring, then HR helps the sales function. That is mere alignment which does not need any analysis nor does it replicate a cause-effect relationship with increased sales to say that HR is aligned.

Gap analysis

It is important that we consider how we look at data. Identifying gaps in the actual and desired scores or gaps acroos inter-department scores does not add business value and hence does not come under the purview of the definition of HR Analytics.


Correlating people data and business data is definitely a step in the right direction. It shows the organization that they are able to establish important connections. The downside is that correlations do not assist in critical decision making with respect to investments alternatives.- because correlations may only represent coincidences in the relationship between people data and outcome data. Presenting a correlation analysis to a senior team with a moderate level of statistical expertise will result in a definite disapproval of the analysis.


Benchmarking is an important metric and valuable however it fails to establish a direct link to business outcomes of beingahead or behind on benchmarks and the actual ROI on spending money to improve on a certain benchmark. It is yet again a way of looking at data, but benchmarking is not analyzing data or showing its business value.

Recommendations: PART A

Methodology for Analysis

The suggested recommendations have been arrived at using the following sources:

1. Primary Research: I gained a perspective on the need , implementation and challenges with respect to analytics faced by organization through interviews and discussions with HR managers from reputed organizations and students who have recently interned in this field.

2. Secondary Research: a) Published sources like research papers, journals and books cited as the references at the end of the report.

b) Blogs and websites maintained by HR Experts across the world across different industries.

Maximizing Success : Implementation best practices

The benefits of HR Analytics are plenty and unending however the whole exercise fails if the process change is not implemented effectively. Some of the best practices for successful implementations identified are as follows:

Invest in data clean-up to correct or remove inaccurate data. The volume of data used is large and organizations have multiple sources for this data collection.The organizations should thus ideally have one system or software to record data. Clean data will further lead to good results

Focus data and analysis on business results. It is important to first focus on key metric that are critical to the business and hen analyze on similar lines to generate the maximum benefit.

It is important that the end users of these metrics understand the scores and the complete application workflow. The vendors must train the HR of the client side to be able to use the software in the prescribed manner

To institutionalize the process a more complete technology environment will be needed. It is imperative to develop a technology blueprint that includes everything- reporting, presentation warehouse, analytics, through dashboards, and notification and distribution along with the integrations needed to customer-facing data, financials and operational data sources.

Plan for incremental deployment. The initial setup will be small which should be capable of a scale up eventually as analytics evolve. It is important to build in build in the flexibility to face a dynamic demand market.

Manage change. If the organization is not already governed by numbers, metrics and analytics, getting to that level will in turn be major a shift in itself , for all : technical and functional experts and operational managers. Cost of change management to be considered for successful deployment.

Enablers & Inhibitors

Data Access: Through research it has been observed that organizations with access to centralized data could conduct analyses to interpret how factors such as operational efficiency, leadership and customer and financial outcomes are interrelated. Those without such access cannot because of system limitations lack of in-house resources and lack of suitable data to analyze and interpret the information. Clearly, organizations without any such limitations have an advantage.

Field training: Training HR users is a critical enabler for analytics success. Hands-on use is the preferred way of training as working with data directly wil alow users to hone the required skills detecting patterns , correlations , interpreting results and communicating the same across the organization. Support from the senior management adds credibility and weight to the entire exercise along with upgraded technology which is yet another enabler in the process.

Organizational barriers: Many line managers and front-line HR generalists are not yet comfortable discussing about HR in terms of testing, evidence, trial-error basically quantifying the traditional people related behaviours. Establishing faith in how numbers can now better represent human behavior is a challenge ahead.

Culture: A culture that endorses HR analytics at the top levels, and communicates this widely across the ranks,provides a supportive environment for executives to experiment and test in real workforce situations. On the other hand, if the culture does not support HR analytics it subtly indicates its employees will be wary too.

Multiple challenges among working groups:

Managing data from multiple countries

Lack of incentives for others to share data across functions

Inability to match data across sources

Tailoring and communicating findings to different levels of the organization

Data credibility concerns, perhaps caused by limited manpower resources, privacy and security

issues, legal and financial constraints, old data, employee-driven entries.

The challenge for HR analytics is not data - it is the mindset

This particular tool requires a strategic mindset to master it. The challenge lies not with the software part or the people in HR Analytics. People do care about data manipulation and using the right data to extract useful information to justify decisions. The real challenge as I perceive it is with the mindset particularly of the HR executives in question.

Potentially the suggested system deals with the conversion and use of raw data into meaningful information using metrics scores which can yield a direct business impact. This essentially involves a thorough understanding of the business and strategy more than before when the HR function was silo focused. To learn about the primary workforce drivers behind delivering on the strategy and to understand how to extract information and convert it into a strategic deliverable followed by an action plan. This ability or mindset rather is not present in most cases.

This must essentially come from within the HR function and the best way is to establish it in a top-down fashion. The idea of analytics implementation is fancy enough to blind the senior executives and they fail to see the true worth or why exactly they need it, what to expect out of it. So, someone in the analytics team within HR must have this mindset to ask the right questions guide the group and deliver on the promise of value added analytics.


The present leaders in analytics are Oracle and SAP. They have the most sophisticated and integrated analytics solutions. In terms of smaller vendors, SumTotal Systems and PeopleFluent appear as front runners.It is also seen that there are several niche HR analytics vendors whose products can be integrated with talent management systems for companies that would like to significantly ramp up their analytics capabilities.

Challenges of Customization

Know where the HR data is

Even with the more accessible self-service technology, there are a number of factors to consider before getting started. Of top priority is identifying the types of HR data required for the analytics as well as where the data might reside in an organization.Besides this what is important is that the results of any analytics software may not add value to the business if the data quality is not upto the standards . Often vendors face the issue of aligning the data storage and recording process before implementing the analytics technology.

Know the HR dashboard user

Making sure HR dashboards are simple, highly visual and specific to an individual's role can also promote widespread acceptance and use. A sales leader may need to see his group's retention data stacked up against another sales area for competitive reasons, but that same dashboard may not be applicable to someone in HR. "It's important to look at the role of the user and what information they need. They might need different dashboards because their goals are different. One might be looking at hiring, while someone else is more concerned with cutting costs. Given that the business requirements vary and so will the demand for metric scores.The vendors need to establish a concrete base upon which they can make quick amendments to incorporate different expectations from different clients.

Vendors in the Market

Technology experts

IBM Cognos 8 workforce performance

Metric type measures from Adaptive Warehouse model that are organized into groups

The various metric types allow accounting for virtually any type of data that business would want to measure

Flexibility features allow modification of highly customized metrics

Workforce performance model objects are prepackaged with the tool

Accenture's Dashboard / Analytics

It offers advanced reporting functionality of the Oracle solution that creates HR reporting dashboards which gives decision makers a concise view of KPIs

Executives can quickly assess the current state of the workforce, and see forecasts that highlight potential future gaps and shortcomings

Consultancy space

Mercer's iknow application

Mercer iknow is a cloud-based analytical platform, designed to analyze data from a wide variety of sources and empower business leaders with actionable, data-driven decision support

The iknow technology platform is enriched with Mercer's proprietary content from surveys and research.  For example, benchmarking data from Mercer's compensation surveys enables immediate analysis of company data against benchmarking data at different levels 

Pre-defined metrics are also bundled into the iknow offering, spanning areas such as workforce structure, performance and accountability, capability and sourcing, rewards and recognition, leadership, and others.

Towers Watson's metrics that matters

Key metrics calculated automatically - no manual intervention required

Employee outcomes, such as turnover rates, visible across the organization and at the business unit level for direct internal comparisons

Customized scorecards, easy to create

Easy access to external benchmarks for predetermined regions and industry group, hence no need for time-wasting internal or external data searches


Vendors or Service Providers today are focusing on different variations in the standard module to gain a competitive edge while pitching to prospective clients. One such tactic as adopted by most consultancies is to use their existing database of compensation, performance, attrition etc. figures to further the use the scores derived on various metrics' in order to benchmark one`s performance with competitors .Each metric is broadly divided into different sub-headings depending on the particular aspect of HR Planning they correlate with further the vendors would relate a value proposition for each of these metrics to help the client better understand and interpret the value of the metric score for strategic decision making. Given below is a laundry list of the value proposition pitch by certain consultancies.

Table 1: Interpreting Metrics Scores


Metric Type

Value Proposition of the Metric

Internal hire ratio

Effectiveness Measure

This ratio helps to determine how is to invest in building the talent pipeline. Also as a hypothesis we know that for a high growth company the ratio will be lower vis-à-vis a company who is in divesting or in a restructuring mode.

Turnover rate from different sources

Efficiency Measure

This metric will give the organization a brief idea about the performance of different sources used for recruitment; if tracked regularly.

Cost per hire ( at all the levels)

Efficiency Measure

The metric will be useful in determining the most efficient source for hiring. Also it will help the organizations to compare it with previous year data and also can be compared with similar type of company and to keep a tab on the overall cost incurred per hire

Performance of recruits hired through external sources

Efficiency Measure

The metric would be one the measures to help the organizations to zero down on the most efficient external source

% HiPos with 'A' performance in continual

Effectiveness Measure

The metric reflects if the right environment has been provided to the HiPos to remain HiPos

Diversity Measures

Effectiveness Measure

The metric measures the ability of the company to innovate & ability to hire & integrate people from diverse background

New hire satisfaction score

Effectiveness Measure

The metric indicates the ability to integrate talent from outside


Methodology for Analysis

The suggested recommendations have been arrived at using the following sources:

1. Primary Research: I gained a perspective on the need , implementation and challenges with respect to analytics faced by organization through interviews and discussions with HR managers from reputed IT organizations , consultants in the HR domain and students who have recently interned in this field.

2. Secondary Research: a) Published sources like research papers, journals and books cited as the references at the end of the report.

b) Blogs and websites maintained by HR Experts across the world across different industries.

How to compete on Analytics: Organization-wide Perspective

Technology today is no longer a sheer tool to support your work it has now emerged as a strategic weapon to master the business. Today all firms in the industry offer similar products,use comparable technologies what differentiates them is their business processes and human talent and analytics help organizations gain from these differences. Although many companies are embracing HR Analytics only few have been able to achieve the proficiency required. The following attributes are crucial to the success of companies that compete with HR Analytics :

Widespread use of Modeling and Optimization

The goal is to move beyond descriptive statistics which talks about measuring efficiency through average revenue or profit per employee but to use these for predictive modeling of investment avenues which will give highest return. Leaders in HR Analytics experiment with metric scores to design an intervention which will yield the maximum positive results. The idea is to move beyond scores into predictive analysis using these scores to extract the most from the analytics tools.

An Enterprize approach

In traditional companies every individual department manages its own analytics without much inter-department coordination - number crunching functions use their own tools train their own people - this leads to chaos. To establish HR as a strategic partner it is essential to first integrate it with all departments and get rid of the silo department approach towards analytics.

Senior executive advocacy

An organization wide embrace of analytics requires a change in processes , culture, behaviour and skills for many employees and this transition has to be facilitated by the top management. A background of statistics is not necessary among the leaders but what is important is that they must understand the use, applications and its limitations to set realistic goals for the transition.

Potential sources of strength

Organizations which adopt HR Analytics commit to more than simple number crunching. They need to direct their energies towards finding the right focus, build the required culture and hire talent which can use the metrics to churn appropriate strategies.

Right Culture

Culture in the organization must be transformed to promote respect for hard facts.Employees should be urged to follow quantitative data and base decisions after testing , measuring and quantifying evidence. The employees starting with senior executives must exhibit the hunger for facts and analysis. Also it is essential that all departments support the initiative by adopting a transparent mechanism for recording and sharing data with the HR team.

Right People

The orientations of people hired for positions within the HR department must be analytically driven with a keen interest in interpreting hard facts to justify decisions.The ideal combination is one with a good mix of Analytical , Relationship and Business talent.The idea is to look for people who can think beyond the traditional role of an HR manager to focus on the business impact of the proposed peoples strategies.

Self-education is key for building analytical skills

Given that the talent requirement in the field of HR is undergoing a change this change has been manifested in the aacademic programs at Business schools. However for the existing pool of HR professionals self-education is the key.It is recommended that HR professionals must involve themselves in reading and discussions with peers to learn about HR Analytics and how it can be implemented.

Simultaneously before undergoing a mass transition to incorporate analytics it must ensure that all employees have sufficient knowledge of the same and finer nuances for senior executives. Hosting and participating in nation-wide HR conferences on this topic can be of much value add.

"The future of HR is going from the generalist role to the people strategist. Those who do not move ahead to adopt the role of the `Strategist` are bound to be left behind.

Appendix 1

Case study: PricewaterhouseCoopers

Methodology: This case elaborates a talent management and retention challenge faced by PricewaterhouseCoopers. It is an original case developed previously and the extensive details hve been describd in in Levenson,Fenlon and Benson (2010). Here, at my end in this report I present the key issues and focus on the use of analytics to address the problems adoptem by PwC.

Case: PwC had a relatively high turnover for a certain key talent pool i.e. among senior associates, the second stage in the career ladder that starts at entry level and ends at partner. A proposed option was to consider deferred compensation as a solution under consideration to improve retention: as it was to offer the promise of greater pay in the future for those who stayed longer with the firm. The firm also had evidence that people who left the firm at later career stages had better career outcomes in the long run, such as achieving the position of a CFO, compared to those who left at earlier career stages. Eventually now what the firm needed was evidence on whether a deferred compensation plan as proposed , would work as a retention tool, and if more accurate data driven information on career outcomes of individuals after leaving the firm might cause people to stay voluntarily without the added incentive of a deferred compensation program.

PwC initiated data collection by surveying current and former employees on their experiences at the firm and, among those who left, career progression ladder and deployments outside the firm. Some of the major challenges in the project included identifying the right set of people to survey among the former employees, getting them to respond, and checking which response was best to be uses for the analysis-none of which required doing any advanced statistical analysis. To start with the analysis required sound knowledge of the firm's culture and relationships with former employees. This helped in starting by identifying offices representative of the firm's business that had strong networks among the former employees. It also needed the skill or ability to get the former employees to be responsive i.e. by appealing to their ongoing goodwill with previous relationships and to former employees' satisfaction with their developmental achievements. These experiences were experienced in terms of real world simulations.

PwC used statistical techniques to estimate the total number of former employees on various survey parameters , based on typical responses rates for comparable surveys, and to determine which response or the trend in the market to use in the analysis. The final analysis sample eventually focused on former employees who had left the firm recently (within the prior 15 years), because their response rates were quite highe and more representative and because their recollection of their experiences at the firm was subject to less recall bias(versus those who had left more than 15 years prior to the survey). Advanced statistical techniques-multivariate regression -was used to compare the following:

career outcomes among former executives who left at different career stages;

work-life balance for former v/s current employees at almost comparable career stages

drivers of retention for current employees.

For all of the analysis, multivariate regression enabled a direct comparison by controlling for factors that might otherwise have led to perceived differences among the groups and between individuals with greater level of education, whether the person had a CPA or other professional certification, office location, total years of work experience, gender, race, and the line of service in which the person worked at PwC before leaving. For the retention models, multivariate regression further enabled an analysis of which factors were important in driving employee decisions to leave the organization; this was essential to identify non-compensation factors, such as work-life balance, that figured prominently in the process. The combined efforts of the analysis and retention initiatives by the firm had a foreseen impact. The analysis revealed that the idea of adding a deferred compensation program would not have had the desired affect. Infcat a much smaller impact on retention when compared with the practice of addressing work-life balance and concerns about career development and progression. The actions the firm took strengthened relationships within the organization, providing new tools for leaders and HR to manage workload balance issues and simultaneously focusing on coaching and development of new talent.

The end result was a marked decrease in the voluntary turnover in the firm that met the firm's operational and strategic goals.