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The analytics of critical talent management.

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Introduction

Over the past 20 years, workforce planning has grown in sophistication, moving from staffing plans to employee supply-and-demand gap analysis. This movement looks to create high-impact, effective and efficient models for human capital much the same as in finance, production and engineering. (1) Many experts talk about pivotal, critical or "A" roles as a method of differentiating the workforce. (2) Dr. Jac Fitz-Enz characterizes the evolution of the field as moving from transactional monitoring to performance monitoring, to linking HR metrics with business goals and finally, to predictive analysis. (3) What I term critical talent management arises from current developments in workforce planning.

I discern three key components in critical talent management, each of which involves HR partnering with business leaders and leveraging analytics.

1. Collect production and employee data and conduct in-depth analysis.

2. Gather and analyze information and trends to forecast challenges that your workforce will need to address.

3. Perhaps most important--Use predictive analytics to formulate what I would term talent philosophy.

The data collection and forecasting steps provide a backdrop to dialogue with organizational leaders about the best way to utilize employee talents. I advocate for a positive talent philosophy wherein the business practice includes hiring and developing employees who are nimble enough to address new challenges and use predictive factors of employee success; rather than to terminate employees and reinvent positions as the organization grows, and constantly to turn over the employee pool.

In the following pages, I discuss the basic concepts and practices in critical talent management and demonstrate how it has been used successfully in different sectors of business, especially where a high volume of employees are being managed. Various case studies conducted in diverse sectors will be given as examples of critical talent management application. The three key components in this process--employee information data and analysis, business and workforce forecasting, and predictive analytics--will be described in greater detail in each case study. Let me first briefly describe a few business scenarios and the traditional HR functions.

The Order-Taker in Traditional HR

The following scenarios are familiar to HR practitioners:

* An aerospace supplier wants to know how to recruit the requisite number of design engineers to ramp up business for a new airplane order. Here HR acts as a broker for recruiting services, by securing approvals to fill positions and then administering the hiring process. The focus is on low cost to recruit, short time to fill and as close an experience tit as possible ("Find 30 brake system engineers with at least five years' experience designing brakes for Boeing 737s."). The recruitment picture gets fuzzy when HR discovers that not enough young people want to enter aerospace engineering in college or the job market, and the remaining experienced workforce is preparing for retirement.

* A healthcare organization needs to design a method to transition patient-care providers into managers and hospital leaders when patient demographic shifts are currently very different from the demographics of providers and leaders. HR may turn to hiring managerial candidates from the outside to fill vacancies only to find that external candidates lack organizational knowledge and savvy while out-of state candidates face certification hurdles.

* An automotive manufacturing company seeks to implement a group leader role that will lead lean manufacturing on the shop floor. HR might train the supervisors and crewmembers to use lean manufacturing tools and then evaluate supervisor performance.

Human resource practitioners used to carry out workforce planning in terms of a short-term forecast, creating a staffing plan based on past years' experience. It is a specific view from a recruiting perspective that aims to achieve short-term production and service goals and the elimination of waste. The goal is to avoid having too many employees with idle time, or too few employees sharing the workload, leading to overtime costs and overwork burnout. An example of a staffing plan, long held as an essential management tool, is shown in Exhibit 1 (p. 52).

In Exhibit 1, inputs are workforce demographics: population, age, and percent at or near retirement, terminations and numbers required for business operations. The output is the number of positions that are needed to post and to fill.

From Order-taker to Planning Partner

In the above staffing scenario, HR functions as the order-taker from operations or finance departments. It was a tradition, for example, that production planners on the factory floor would meticulously line up every machine with customer orders and provide employee shift schedules and overtime lists. In the critical talent management paradigm I am proposing, HR is a planning partner in guiding the analysis, the forecasting and a dynamic talent philosophy for today's competitive and fast-moving business environment.

Component I: Collect and Analyze Employee Data

Before conducting any analysis of an organization's internal job structure, HR should first collect information such as job types, employee demographics, termination rates and recruitment strategies. Internal Labor Market (ILM) mapping is one method for processing information that yields the best and most efficient way of creating reliable workforce profiles. Mercer Consulting's Play to your Strengths, by Nalbantian, Guzzo, Kieffer and Doherty is an authoritative reference book on ILM and should be in every HR library. (4) ILM looks at the entire set of employee transactions over time, including attraction and hiring, development, promotion, lateral movement, geographic or functional assignments and retention. ILM creates a compelling visual of employee movement, serving as a platform for workforce forecasting and talent philosophy discussions. Is the level of churn right for the organization, how much does it cost, and is the cost worth it in terms of talent management?

ILM Case Study

The following case study is an example of how a labor market mapping exercise provided the foundation for productive conversations with leadership about talent management. At one global aerospace manufacturing firm I will call "GH," HR used the Mercer model to conduct an external scan, analyze internal production and employee data and create an internal labor market map. There were eight steps in this process, not necessarily in temporal order.

Step 1: Frame the Business Issue. The team, a group of HR and GH line professionals began with defining the issue: How can the business ramp up staffing for a new product line that would need to be designed, tested and manufactured to strict tolerances and with customer and agency oversight? Successful product development depended on the firms' ability to attract, retain and develop top industry performers. Challenges abounded in a recovering market, a shortage of skilled workers, an aging workforce and anecdotal stories about employee turnover. The firm favored employees with very specific educational background, technical skills and industry experience. In addition, GH needed to drive a culture of continuous improvement in a highly unionized environment.

Step 2: Research and Data Analysis. The team researched the internal labor markets and external employment information, and analyzed the quantitative and qualitative data through focus groups and interviews. (5) The resulting ILM maps were presented to the leadership team and stimulated a discussion around how to best use talent. The team developed recommendations that included a strategy designed to retain talented performers within the organization, to develop key leaders and to attract technical and professional candidates.

They conducted further analysis to stratify employee separations by key functions, age group, years of service and levels within the organization. The data naturally broke into patterns as follows:

* Employees with five or less years of service accounted for 68 percent of total separations.

* Employees with 16-plus years of service accounted for 22 percent of total separations. Leadership wanted to incentivize long-service technical and engineering professionals to stay with the firm up to and even past normal retirement. Separations among this group were not generally retirements; these professionals left for other career opportunities.

* High potentials and key business leaders constituted a19 percent turnover rate.

* The core of active employees had five to 18 years of experience. They were the firm's bedrock, stable workers who hold company and industry knowledge. They provided continuity to internal and external customers and knowledge of the design, testing and engineering process--all critical to the firm's business. Leadership wanted to ensure that these employees were engaged and would not become flight risks.

* New hire rates compared with promotions showed that the firm was buying talent at three times the build rate.

* Experienced staff in engineering had little upward mobility, leadership levels being frequently filled externally.

Step 3: External Benchmarking of Turnover, Retirement Risk, and Costs. The team compared GH's data with industry-specific separation rates published by the Department of Labor and by the Bureau of National Affairs, Inc. (BNA), and found that the GH turnover rates were double the national averages. Moreover, the Aerospace Industries Association (6) cited an Accenture study concluding that the two most pressing issues for aerospace in the future are the aging workforce and an increasing lack of technical talent. NASA, for example, had three times as many technicians over the age of 60 as under the age of 30. By 2010, 50 percent of the existing U.S. workforce in GH would be retirement eligible.

On balance, the threat of a retirement onslaught is tempered by a trend to work longer. A survey conducted by the AARP and Towers Perrin (7) concluded that 70 percent of workers who were not yet retired planned on working during their retirement years and approximately 10 percent expected to work into their 70s. Fully 21 percent said they wanted to work full time in their current position past the age of retirement.

Given the aging workers and the trend to retire later, GH's team hypothesized that 20 percent fewer retirement-eligible employees would actually retire than in previous generations, and that the organization will therefore have a greater percentage of workers past normal retirement age. Interviews with retirement-eligible employees validated this assumption. The interviews also stimulated a retention strategy, giving an enhanced role for the experienced workers as a guru, the knowledge holder who passes on the technical know-how to younger professionals.

Step 4: Assessing External Supply. Information was mined on the supply of future aerospace workers. The Bureau of Labor Statistics detailed a survey of 500 U.S. aerospace employees where 80 percent of respondents said that they would not recommend the industry to their children due to lack of employment stability. The aerospace industry thus predicted it would suffer a 17 percent decrease in employees from 2002 to 2012. (8) Fewer entrants into the field were causing aerospace companies to make twice as many offers to fill their vacancies in the recruitment process.

Step 5: Calculating the Costs of Turnover. HR presented the high costs of the voluntary separation and replacement of aerospace engineers in relation to operating income, giving the leadership team a powerful business case to reduce turnover and thereby reduce costs. The team calculated cost of turnover as 150 percent of the exiting employee's salary, using the Saratoga Institute's research. (9) As capital investments increased to gear up for the new aircraft program, the cost of turnover consumed increasingly larger portions of the firm's operating income, from 14 percent to 34 percent. On the other hand, in one critical engineering group, reducing 48 voluntary separations by one third would retain 16 employees, a direct translation into an annual savings of 4 percent operating income.

Step 6: Assessing Internal Movement. The internal labor market research included workforce demographics for the firm's locations in the United States and overseas, covering a three-year period, for all business and technical employees. Data on both voluntary and involuntary separations were examined to identify who was leaving, for what reasons, and from which locations. The team also looked more closely at all movements within the firm. The internal labor maps (10) showed in and out movements that resulted in churn at several key levels.

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Exhibit 2 shows the employee movement for one critical business segment.

This visual chart dramatically highlights employee hiring, promotions and turnover. Read the map from left to right to follow external hires into a job group, current population, and then terminations. A bottleneck shows in the middle grades of engineers and technical employees, where odds were four-to-one against getting promoted. Not surprisingly, the highest turnover rates existed in these grades. The team mapped out each facility and key functional areas, and presented the maps to the leadership team for an in-depth look at what was happening in the firm.

Step 7: Developing Qualitative Data, Why Stay and Why Leave? In-depth exit interviews were conducted of employees who left voluntarily and were considered "regretted exits." Culture and environment factors were most often cited, including communication, definition of roles and responsibilities, morale, vague accountabilities, lack of solid management and lack of personal recognition. The next most often cited category was career growth, including desire for increased responsibility, availability of future jobs and educational opportunities. Salary and location were cited less frequently and only 20 percent cited salary the biggest reason for exiting the firm.

HR conducted a series of focus groups and interviews among incumbents in mission-critical job categories. The data validated that employees were looking for more communication from their managers, career path advice and opportunities to grow within their functions. The relevant findings echo the 2004 Corporate Leadership Council (CLC) survey of 50,000 employees at 59 organizations. (11) The CLC study revealed that internal communication, availability of career advice and career paths, and appropriate roles and responsibilities are the most significant drivers of retention.

Step 8: Developing Action Plan. HR then recommended a retention action plan that included the following:

* Pair employees in key roles for peer mentoring.

* Design special esteemed status for experienced engineers.

* Develop employees to embrace change and foster a passion for continuous improvement, an area that was identified as critical business objective.

* Create formal programs for exposure and development of staff.

* Provide greater access to career planning via open manager-employee communication.

* Reduce overall voluntary turnover by 30 percent.

The actions in these eight steps provided a compelling view of factors affecting employee movement, and contributed to leadership decisions to create a talent management review. In what follows, I have two more case studies illustrating the crucial roles HR played in partnering with leadership over business decisions.

Component II: Workforce Forecasting

Forecasting focuses on key occupations and skills that will drive the company's core service and provide focused talent management plans. A supply and demand formula estimates how many employees with requisite skills are needed in the organization, where and when they will be needed, and if the supply is adequate. It does not help knowing that the organization needs 100 additional scientists over the coming three years when only a few universities in the geographic region have the right degree programs, or that standards for state certification are a barrier to entry for out-of-state grads. Forecast models rely not only on intelligence from employee demographics but also on operations data and qualitative feedback from business managers to construct probability scenarios. (12)

The case in this section involves a situation at Kaiser Permanente Northern California where the question was how the organization can attract medical practitioners and diverse operations leaders given the changing demographics of the region. Kaiser Permanente (KP) is an integrated health insurer, hospital and medical service provider with over 64,000 employees in Northern California alone. KP's efforts to enhance the diversity, cultural competency, and performance of the workforce are world-class. KP's diversity quest is linked directly to the organization goals of providing evidence-based, culturally competent medical care, and to improve the health and satisfaction of their increasingly diverse plan membership. KP's systematic focus to attract, develop, retain and deploy diverse talents has given it a competitive advantage over its rivals. HR plays a critical role in this whole process with forecasting.

Get Focused--The Kaiser Permanente case

In 2007, KP Northern California analyzed customer and employee demographic data and identified a gap between the homogeneous makeup of organization leaders versus the diverse makeup of patient and staff populations. For example, the patient population is 24 percent Latino, whereas 14 percent of providers and only 4 percent of leaders are of Latino origin. The HR, Diversity and Market Research departments partnered on a forecast, drawing upon information from census, and university and private research about the growth and changes in the ethnic, immigrant, gender and age mix of California's population. The forecast recognized that in 2010 the Spanish-speaking Latino population equaled the non-Spanish speaking White population in California, at 39 percent of total population each. Last year, was truly a tipping point toward the new order of "no majority." Analyses of the demographic data has led to both marketing and human resource action plans as further growth in Latino, Asian, Pacific Islander and mixed-race populations are anticipated to 2020. Clearly, having diverse care providers who are culturally sensitive and who are able to flex and communicate with patients from various backgrounds is a must. Similarly, having culturally sensitive and diverse managers and executives will provide rich leadership to the organization.

Following this analysis, HR implemented a strategy to accelerate the development of the next generation of diverse leaders. The Leadership Diversity Development Program (LDDP) was initiated as an 18-month mentoring program aimed at pairing aspiring leaders from diverse backgrounds with seasoned mentors. The program has grown to include training and development events, exposure opportunities with senior leaders and stretch assignments. Measurements of success are promotions, lateral transfers with expansion of areas of responsibility and interim job assignments for the mentees. The program also provides mentors with development experiences to enrich their capacity as KP leaders. Executive sponsors formally recognize mentees and those who act as mentors. This year, the program is in its third cohort and has become a valued leadership development link.

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Supply--Demand Forecasting

In the meantime, KP also developed a comprehensive supply and demand forecast model in collaboration with the Center for Health Professions at University of California San Francisco. (13) The model, shown in Exhibit 3, is designed to be very flexible and to identify and track its critical business drivers to identify a variety of scenarios. The model can be used to track such internal and external forces as process improvements, market growth or contraction, new technology and changes in healthcare delivery.

For example, in a forecast of required pharmacists, which is a pivotal position in healthcare, KP conducted analytics using pharmacy operations data of the numbers of prescriptions filled. The firm made assumptions based on demographics of patient age and acuity, and patient population growth. The pharmacy forecast then factored in trend data about how prescriptions for medications are filled and delivered, in-person versus mailed, big-box store versus hospital or local pharmacy. The firm also factored in improvements in business systems, team staffing and the new mail-order process.

Prior to using analytics at this organization, the metric driving decision making about how many professionals to hire was a recruiting metric called the vacancy rate. The vacancy rate was a function of budgeted slots available, not a reflection of true need and not tied to operations data. After KP presented the analytics to both recruitment and the pharmacy operations leadership teams, it made critical decisions about recruiting pharmacists in strategically important areas. This model is a critical tool for the HR professional and can be amended for a variety of industries and locations. I will next address predictive analytics that involves using analysis to choose the right people with the right mix of skills in the right roles.

Component III: Predictive Analytics

Predictive analytics is relatively new to human resource practice. Dr. Jac Fitz-Enz describes it as "a logical structure to parse out the many variables that can affect human performance." (14) As an example, a global metals manufacturing company I will call, "AW," implemented a lean production system and was searching for a way to add lean production leader roles in its workforce. In the old system, supervisors assigned work, distributed supplies and resolved bottlenecks. Under the new paradigm, lead personnel would transfer much of the problem solving to their teams while serving as coaches and conducting frequent team interactions to ask questions and guide the team in continuous improvements. AW implemented standardized methods of lean management throughout the business unit. Boards were placed at each work group's station to document issues for which the crew was accountable to resolve. And on lights permitted the crew to stop production to resolve problems. A critical question was what makes a person a successful leader in such open airing of obstacles and crew feedback.

Human resources partnered with operations teams to conduct an in-depth analysis of manufacturing results under every supervisor: They measured quality, safety, delivery performance and innovative process improvements. The data yielded a matrix of each shop supervisor and their team's results. Those highly performing supervisors whose results were 150 percent better on all measures were then invited to incident interviews with their leadership. Incident interviews focused on pivotal stages in the manufacturing process where events could hamper quality and productivity goals. They developed a preliminary model that described differentiating factors of their successes, including specific behaviors that were found to be common to all of the successful supervisors. Through feedback from line management, HR and lean team leadership, they also developed and refined a competency model.

The resulting data-based behavioral model focused on three critical behaviors that could predict success in leading a team of lean manufacturing associates: getting started on the job with orientation, setting expectations of team norms and behaviors, and coaching team members in problem-solving and use of lean tools. These critical behaviors depended on the supervisor understanding and using lean tools and knowing how to act as a coach rather than in a directive manner.

Envision the Future

The AW case echoes a recent KP initiative conducted in partnership with the Institute for the Future. The initiative created a 10-year model, "Envision the Future," which looks at the impact of socio-cultural diversity on health and healthcare, identifying winning strategies for healthcare delivery and workforce development. (15) The approach links macro trends such as health-reform legislation and the rapid development of mobile technology to strategic imperatives of the organization. Statistical modeling forms the basis for identifying the trends, for instance, models of newly insured to be expected under health reform, their age, acuity, domicile, income and language. The organization's goal is to build capabilities in the care-delivery system to meet anticipated demand and to champion strategies that improve the well-being of patients.

At KP, we are also looking at the upcoming generation of healthcare providers, administrators and leaders. Much has been written about Generation Y: 80,000,000 strong and currently about 25 percent of the U.S. workforce. (16) Generation Y has grown up with technology and are savvy about adopting new technology platforms and applications. They are a diverse population, 57 percent white, 14 percent black, 19 percent Latino and 5 percent Asian, are more likely to describe themselves as mixed race and are thus generally more tolerant of persons from different backgrounds. It would seem that this generation already possesses some of the critical characteristics that KP has identified for its future workforce.

Our challenge is how to attract and retain Gen Y healthcare employees and leverage their technological savvy. KP is in the early stages of forming a "Business Resource Group" for KP employees who are members of Gen Y. The Workforce Planning department has conducted focus groups that validate that Gen Y employees look for career development and mentoring, and that they are invested in their personal and career growth with the organization. Retention drivers include the quality of their manager and the purpose of the organization. This is a work-in-progress, a stage in the process of managing the future now. (17)

Envisioning is a powerful conceptual framework for anyone who would like to lead HR and business teams in a future-focused and analytical exercise. Envisioning the future brings us full circle in discussing how analytics will impact the practice of workforce planning, or, as I term it, critical talent management.

Conclusion

The three key components in critical talent management--employee information data and analysis, business and workforce forecasting and predictive analytics--have been presented through a number of cases and models. The analytics exemplified in these components allow HR to move from a conventional order-taking position to a dynamic partnering role. Through analytics, people are linked to jobs where critical success factors have been studied and enabled, while the organization reaps the benefit of increased overall productivity and profitability.

HR should seek out members with finance and consulting skills who can conduct a comprehensive workforce profile, assess what skills the business will need in the future, and create forecasts and scenario models. HR will then have the credibility to facilitate discussions with stakeholders about what management decisions would be appropriate for the organization based on the parameters in the prevailing analytics. The challenges and the corresponding opportunities for growth for HR, in my view, have never been greater.

References

Becker, Brian, et al. The Differentiated Workforce Boston: MA Harvard Business Press, 2009.

Boudreaux, John and Ramstad, Peter Beyond HR The New Science of Human Capital, Boston MA: Harvard Business School Publishing Corporation, 2007.

Calhoun W. Wick, Roy V. H. Pollock and Andy Jefferson, The Six Disciplines of Breakthrough Learning, Second Edition, San Francisco: John Wiley and Sons, 2010.

Cappelli, Peter. Talent on Demand: Managing Talent in an Age of Uncertainty. Boston, MA: Harvard Business Press, 2008.

Fitz-Enz, Jac, The New HR Analytics, Predicting the Economic Value of your Company's Human Capital Investments, New York: AMACON Books, 2010.

Johansen, Bob, Leaders Make the Future, San Francisco, CA, Berrett-Kowhler, 2009.

Nalbantian, et al. Play to your Strengths, New York: Mercer Human Resource Consulting, LLC, McGraw-Hill, 2004

http://www.iftf.org

http://futureworkinstitute.com

http://www.aarp.org/work/work-life/info-2005/workers_fifty_plus.html

www.workforce.com/section/news/article/workforceplanning.html

http://www.hci.org/

http://www.humancapitalsource.com/drjac2009/

https://clc.executiveboard.com

(1) Boudreaux, John and Ramstad, Peter Beyond HR The New Science of Human Capital, Boston MA: Harvard Business School Publishing Corporation, 2007

(2) Becket, Brian, et al. The Differentiated Workforce Boston: MA Harvard Business Press, 2009

(3) Fitz-Enz, Jac, The New HR Analytics, Predicting the Economic Value of your Company's Human Capital Investments, New York: AMACON Books, 2010.

(4) Nalbantian, et al. Play to your Strengths, New York: Mercer Human Resource Consulting, LLC, McGraw-Hill, 2004.

(5) Collection of HR data is a burgeoning field with many commercial applications and products. I do not address data collection in detail in this paper; it is the subject for another study.

(6) Dasgupta, Pinaki, "Perfect Storm" of Problems Are Crashing Down on North American Aerospace and Defense Industry, (2005) accessed at http://www.accenture.com/Global/ Services/By_Industry/Aerospace_and Defense/ Services/WorkforceTransformation.htm

(7) AARP: "Workers Age 50+: Planning for Tomorrow's Talent Needs In Today's Competitive Environment", A Report for AARP Prepared by Towers Perrin (December 2005), accessed on-line at http://www.aarp.org/work/work-life/ info-2005/workers_fifty_plus.html

(8) Bureau of Labor Statistics: Aerospace Product and Parts Manufacturing http://www.umsl.edu/services/govdocs/ ooh20042005/www.bls.gov/OCO/cg/cgs006.htm

(9) Joinson, Carla, "Capmring Turnover Costs: In-depth analysis of your organization's turnover may help gain support", HR Magazine, July 2000.

* Direct costs include: last paycheck, accrued vacation, and separation pay, increased unemployment tax, benefit continuation, advertisements, recruiter fees, interview expenses, reference checks, drugs test, contract employee cost, overtime costs, and relocation expenses. Once the new employee is onboard direct costs include orientation materials and training materials.

* Indirect costs include: administrative costs for processing the separation, lower productivity of remaining peers, supervisor and subordinates, recruiter's time, interviewer(s) time, and orientations participants' salaries.

(10) Nalbantian, et ah, Play to Your Strengths, Chapter 5, pp. 80-102

(11) Corporate Leadership Council, 2004 Employee Engagement Survey, accessed at https://clc. executiveboard.com/Members/ResearchAndTools/ Abstract.aspx?cid=7304687&fs= 1 &q=2004+engage ment+survey&program=&ds= 1

(12) Cappelli, Peter. Talent on Demand: Managing Talent in an Age of Uncertainty. Boston, MA: Harvard Business Press, 2008. 135-141.

(13) http://www, future health, ucsf.edu/

(14) Fitz-Enz, Jac, The New HR Analytics, Predicting the Economic Value of your Company's Human Capital Investments, New York: AMACON Books, 2010, p.5.

(15) http://www.iftf.org/about.

(16) Scott Keeter and Paul Taylor, The Millennials, Pew Research Center. December 11, 2009.

(17) Fitz-Enz, Jac, The New HR Analytics, Predicting the Economic Value of your Company's Human Capital Investments, p.5.

By Kathryn F. Shen, J.D., M.B.A, practice leader, Workforce Planning, Kaiser Permanente Northern California

Kathryn F. Shen, J.D., M.B.A, is the practice leader of Workforce Planning at Kaiser Permanente Northern California. Workforce planning engages an internal team of consultants, career specialists and analysts to provide forecasts, business and training plans for hospital, health plan and business function employees. Its mission is to anticipate change, providing a future focus to customer and employee demographic analysis, retirement projections, staffing plans and leadership/ succession planning. Shen joined KP in 2007 after 25 years of work in law, labor relations, human resources and diversity with LTV Steel Company, Alcoa Inc., Goodrich Aerospace, and ITT Industries.
EXHIBIT 1. EXAMPLE STAFFING PLAN

        Age/Retirement
                                     % at or
           Average      % w/in 5     above
           Age of       yrs          retirement    Vol.    Invol.
Location   population   retirement   eligibility   terms   Terms

       1           36         0.0%          2.1%       5        0
       2           45         1.6%          3.2%      11        1
       3           41         5.9%          5.9%       1        0
       4           47         0.0%          7.7%       0        2
 Totals          42.3         1.9%          4.7%      17        3

                                            Expected       Gaps
           Retire   Current      Business   terminations   to
Location   terms    population   need       at 10% rate    fill

       1        0           46         50              5      9
       2        0           63         75              7     19
       3        1           34         45              4     15
       4        0           28         35              3     10
 Totals         1          171        205             19     53

           Open        Need to
Location   positions   post

       1           0         9
       2          14         5
       3           7         8
       4           2         8
 Totals           23        30
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Author:Shen, Kathryn F.
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Date:Jun 1, 2011
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