The purpose of the graph set is to use QWIs to “tell a story” about an industry at the local level. It introduces the industry’s employment movement (or “flow”) generally, and then breaks down that information through the use of the more detailed elements of the LED data. This approach is designed to show how LED QWIs can be used to better understand general trend information. The text that appears on most of the graphs is meant to summarize what we feel is significant about the data shown.

Modifications have been made to some of the LED terminology to give it more meaning to audiences who may not work with this type of data regularly. For example, the QWI ‘Net Job Flow’ is now shown as ‘Net Job Gain & Loss’ (Graphs 1 and 2), and ‘Job Creation’ and ‘Job Destruction’ are shown as ‘Gross Job Gain’ and ‘Gross Job Loss’, respectively (Graphs 3 and 4a-4c). Additional changes modifications of this nature are anticipated as we begin to get feedback from local customers on the sample products.

Graph 1: Net Job Gain & Net Job Loss Trend in Health Care

This was chosen as “Page 1” of the story in that it appeared to be the most basic indicator of industry growth or decline. That it shows a sharp decline in such a consistently healthy industry such as health care made this is a good test for the value of breaking down the data in more detail.

Graph 2: Net Job Gain & Net Job Loss Trends in Health Care Industry Groups

In showing three selected Industry Groups (we are considering the term “sub-cluster” to replace this official NAICS term), we are attempting to answer the question “Why?” that would likely come after looking at the first graph. In Graph 2, we see that the recent Net Job Loss in Health Care is essentially due to the activity in Medical & Surgical Hospitals alone, and not reflective of an industry-wide downturn. 

Graph 3: Gross Job Gain & Gross Job Loss Trends in Health Care

It is important to note how job opportunities can still exist in times of heavy job loss. This graph underscores that by showing that the highest Gross Job Gain in the period reported occurred during the quarter with the highest Gross Job Loss. Feedback from state LMI personnel in Maryland felt this was significant for local Career Center staff, who were often focused on Gross Job Loss, because job seekers they serve are coming from that side of the action.

Graphs 4a-c: Gross Job Gain & Gross Job Loss Trends in Health Care Industry Groups

Using the same three industry groups, we see the job opportunity gain and loss in several types of businesses. The Medical & Surgical Hospitals impact is minimal for a time, showing real stability until the decline in the most recent quarters. Physicians’ Offices and Nursing Care Facilities show a great deal more volatility.

Graph 5: New Hire Trend in Health Care

Similar to Graph 3, this shows the opportunity that can be present even during times of overall job loss. The period graphed mirrors that of the increase of Net Job Loss shown in Graph 1. In the second quarter of 2002, the number of New Hires was nearly eight times the total of Net Job Gain. However, as the Net Job Loss increases dramatically over the next three quarters, the number of New Hires remains relatively stable, indicating significant churning or turnover.

Graph 6: New Hire Trends in Health Care Industry Groups

Here we see a great deal of variance in New Hire trends among Industry Groups in Health Care. The New Hire total for Medical & Surgical Hospitals peaks in the 1^st quarter of 2003. This, along with other indicators of growth shown previously, leads us to believe that the dramatic job loss shown in Health Care (particularly Medical & Surgical Hospitals) in that period is due largely to a major “event”, such as a hospital closure, as opposed to a general economic or industrial trend.

Graph 7: New Hire Trends in Health Care by Gender

In this graph we begin to look at the factors that represent a major strength of the LED program. The graph indicates a consistent domination by women of the hiring occurring in the industry. For local workforce development decision makers, this can be looked at in different ways. Health Care could be viewed as an industry that holds the most opportunities for women, or it could be assumed by this disparity that there are opportunities in the industry for men that are simply not being taken advantage of.

Graph 8: New Hire Trends in Health Care by Age

As with gender, the ability to break out data by age is a key feature of LED. This graph shows that New Hires in Health Care are primarily in the 25-54 age groups, and far less hiring of younger and older workers occurs. Local workforce development decision makers can look at this information in various ways, similar to that in the previous graph, from the standpoint of where the opportunities are for workers of different ages.

Graph 9: New Hire Earnings in Health Care by Age and Gender- 1^st Quarter, 2003

The last two graphs show the dramatic effect of age and gender on earnings trends in Health Care. In the first, we see how the male earnings gap over females increases dramatically in the 25-54 age groups. While inequitable hiring practices could contribute to such a trend, we assumed that the type of organization or work that male and female New Hires were engaged in was a more significant factor. The next graph underscores that idea.

Graph 10: New Hire Earnings in Health Care Industry Groups by Age and Gender- 1^st Quarter, 2003

In the last graph, we see even more dramatic disparities between men and women within the Physicians’ Offices Industry Group, reinforcing our belief that the type of work being done is most significant in explaining such gaps. For instance, we can assume that there are more male employees in Physicians’ Offices that are actual physicians, as compared to females who may continue to dominate other positions in that Industry Group. However, the virtual leveling of female earnings in the 25-54 age groups may also suggest that women are making choices with regards to family care responsibilities, such as part-time hours, which would reduce monthly earnings regardless of position.