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Building a Data Table

Factors to Consider in Identifying a Target Sector 

One of the challenges in identifying your target industry is that all data collection must be viewed holistically, not independently. In other words, for each piece of data available, you need to ask: how does this piece make sense in the context of other pieces?

One way to be able to see all the pieces of the puzzle at the same time is to create a data table that contains the key data on all sectors, all in one place. The following section of the toolkit describes one set of factors, data and methodology for building that data table. You can find other examples and how-to guides for industry analysis here.

A data-driven analysis is an important starting point, but not the ending point. It will be equally important to take a qualitative look at your potential target industries, and there are tools and suggestions for that included in this module as well. And while we’ve laid them out in sequential order, you can and should move back and forth and consider both kinds of data at all points in the process.

Building a Data Table 

The rows of your data table will include all of the 3 or 4 digit NAICS sectors that are represented in your region. In this example, the columns of the table will include five factors, described below. Download this spreadsheet to follow along with the step-by-step development of a sample data table - each step below corresponds to a lettered tab or tabs on the spreadsheet. Be sure to read the comments in the spreadsheet to see how challenges in data collection were addressed.

Data availability and user-friendliness varies considerably from state to state. The "data source" section tells you the name of the name of the data series that has this data. How you get this data may vary. Some states have very easy to use web-interfaces that will generate this data for you. Some do not. In that case, the state labor market information (LMI) office is your friend – part of their job is to provide labor market information for planning purposes, and you may save significant time and effort by asking them to provide you with the data. In many cases publicly available data is only available at the county level, whereas the LMI office may be able to aggregate the data to a higher level, such as a workforce area or a multi-county area you define. Data aggregated at higher levels will be more complete, particularly if your region includes small counties where there may be significant suppression of data to protect employer and worker confidentiality. Unless you are very comfortable with the labor market information resources in your state, you should start by calling your LMI office – in many cases they will be able to send you much of this data directly, and then you can spend your time looking at and analyzing the data, rather than collecting it.

Another option is to use a 3rd party source of labor market information, such as data from Economic Modeling Specialists, Inc (EMSI). These data sources often use a variety of modeling techniques to attempt to give a more complete picture of employment, but these modeling techniques may also introduce errors. If any data looks too strange to be true, it’s worth calling your data provider and asking for an explanation.

Factor 1: Employment

Answers the question: How many people did this industry employ in the most recent year for which data is available?

Why is this important? Size matters. Your largest sectors are likely to be important to the economy of your region, and initiatives in these sectors have the chance to reach large numbers of workers. Even small percent changes in terms of industry growth and decline can translate into thousands of jobs in large employment sectors.

Data source: QCEW (Quarterly Census of Employment and Wages). Collect data from the most recent annual average (data is also collected quarterly, but because of seasonal flows, it can be more consistent to look at annual data). [Tabs A&B]

TabB preview

Factor 2: Wages

Answers the question: What’s the average wage for workers in this industry?

Why is this important? Sometimes industries can employ a lot of workers, but not pay them very much. Considering wages in the equation can help you identify industries where there are good options for career pathways and employee advancement. Alternately, many sector initiatives target low-wage workers, and in that case you can use wage data to identify industries where there may be a lot of those workers. Be aware that wage data are averages, and very high wages for a few workers can mask a lot of low paying jobs.

Data Source: QCEW. Collect data from the same year you are using for the “employment” number. [Tabs A&B]

Factor 3: Historical Growth Patterns

Answers the question: How has this industry performed in recent years?

Why is this important? Growing industries are potential economic drivers. Contracting industries may need help to stay competitive or attract the right workers. Both growing and contracting industries may be good targets for a sector initiative, but that will depend on other factors and the reasons for the industry growth and decline. Beware of growth numbers in very small industries – if an industry has grown from 50 employees to 100 over the last 5 years, they’ll have a 100% rate of growth – but they’re probably too small to be a good target for a sector initiative.

Data source: QCEW. Decide how far back you would like to compare. 3-5 years will give you a good sense of meaningful growth patterns. Collect data from the earlier year, and calculate the percent change from the start of the period to the employment data you collected under “employment” above. [Tabs C&D]

TabD image

Factor 4: Projected Future Growth

Answers the question: How is this industry expected to perform in the future?

Why is this important? Estimates of how an industry will perform are important for the same reasons that you want to look to see how an industry has performed. But remember that projections are just guesses – education guesses – and you should consider the numbers in terms of what else you know about the industry in your region.

Data Source: State specific projections. These are usually developed at the state-wide or workforce investment area level only, so if you are defining your region differently, you may need to look for the closest fit, or combine data from two or more workforce investment areas. Also, they are only developed every few years, so the dates used may not match your employment year – that’s okay. You can calculate a percent change in the same way as you did the historical growth, or your state projections may include some sort of calculation, such as an annualized growth rate. [Tab E]

 TabE image

Factor 5: Location Quotient

Answers the question: In which industries does my region have a competitive advantage? 

Location quotient is a ratio that compares the concentration of employment in a defined area to that of a larger area, such as the state or nation. A location quotient of “1” indicates that the rate of employment in a given industry in a given locality is equal to the rate of employment for that industry at the national level. Location quotients above “1” indicate an industry with a higher percentage of employment in the local area than across the nation. Most economists believe location quotients at or near 2.0 indicate strong competitive employment advantage in a local industry.

Why is this important? A high location quotient indicates an industry that is concentrated in the region. Think automotive manufacturing in Detroit, or software development in Silicon Valley. Such a concentrated industry is likely to be important to the economy of the region, and changes in these region-defining industries can have far reaching consequences.

Data Source: BLS offers a location quotient calculator. Data is available for state, county, and MSA geographies (scroll down to the bottom of the list for MSAs, they are not included in the state-by-state listings). Ideally, you would use the same year for which you have collected your base employment data. Data is available to the 3-digit NAICS level (choose “subsector”). Your state may also have location quotient data available directly from the LMI department. 

If you are using a regional geographic definition that does not correspond to an MSA, you can calculate the location quotient for yourself by following these instructions. [Tabs F-H]

Other Data

Depending on the focus and goals of your sector strategy, you may want to consider other data points. If they are numerical and quantifiable for each potential industry, then you can collect them and include them in your data table. If they are more anecdotal or qualitative, then you may want to hold on to those questions until you’ve narrowed down your list and industries and are looking at them more closely.