Indicators, Dashboards, Benchmarks, and Scorecards in Regional Economic Development: Lessons Learned

By George A. Erickcek

States and local economic development organizations are increasingly establishing indicators, dashboards, and benchmarks intended to both monitor economic and social conditions in their region and, less often, track the effectiveness of their programs and initiatives. In this article I will describe some pitfalls, large and small, that can occur in the development of these various performance yardsticks.

Pitfall #1: Stand-alone dashboards
The first pitfall is to allow these statistical efforts to stand alone; they should be a part of a larger comprehensive regional development strategy, which starts with the development of a shared vision for the region. This important step, which is often ignored, provides the necessary direction needed for the development of a comprehensive economic development strategy. Possible vision statements can include the elimination of poverty, achieving full employment, or the development of a fully trained workforce. While the vision may seem unobtainable, it provides direction in defining the goals in the comprehensive strategy.

Once the plan’s goals and strategies have been hammered out, its implementation should establish performance metrics to measure its progress. This is when it gets tricky; since the ideal data series are rarely available, organizations tend to track too many available indicators, hoping that quantity will make up for the lack of quality.

Once a vision and strategic goals are in place, the creation of an effective economic development dashboard, benchmark analysis, or scorecard for a region can play a crucial role in setting strategies and measuring outcomes. The definition of each is provided in Table 1. Two key steps are involved. First, the region’s economic development stakeholders must agree on the general performance measures that should be used to measure the expected outcomes. Typically these include employment growth, growth in per capita income, output growth, or population change. It is possible that the strategy is focused on a certain aspect of economic development, such as entrepreneurship, business retention, or workforce development andtraining. In these instances, the measures are less broad based. For community organizations, the performance measure could be the reduction of the area’s poverty rate.

Table 1 Measurement Tools and Analyses
Regional economic indicators—statistics that track a specific aspect of the regional economy. By themselves, indicators are not very useful; however, they are the building blocks to more useful tools. (See Erickcek et al. [2009].)

Dashboards—a well-designed, easy-to-read layout of key indicators or composite of indicators that track the overall performance of the region and/or the organization’s efforts. It is important to imagine the construction of a car’s dashboard and not that of the cockpit in a plane, with its myriad of gauges and readouts. It should have a small number of community-wide indicators as well as program indicators. (See Eberts, Erickcek, and Kleinhenz [2006] and Erickcek [2007].)

Regional benchmarks—a comparative analysis that contrasts the performance of the region with that of strong-performing communities, that share similar economic, social, and/or demographic characteristics. The key challenge in this activity is to select the right comparison areas. (For rural Michigan comparisons, see Erickcek and Watts [2003].)

Scorecards—a statistical report that tracks the performance of the region on identified key indicators over time and/or across communities.

The next step, identifying factors that drive these performance measures, is much more difficult and has three separate approaches. The first relies on experts’ judgment. An advisory board of economic development experts can be called together to identify key growth factors. However, this can generate concern that it is yet another “top-down” approach that will not reflect the needs or interest of the regional residents. The second way is to obtain community input by organizing town hall meetings where residents and businesses can express their views on the important growth factors. While this approach can build community support and “buy-in” to the resulting strategies, it is highly subjective and can ignore empirically based research findings on what factors are important. The issues that arise from these meetings can be very local—streetscape issues or the redevelopment of an abandoned mill site, for example—or very general, such as poverty reduction.

The third approach to developing an economic development dashboard is statistically based—identifying factors that are statistically associated with the movement of the performance measures. In several studies we have used both factor and regression analyses. First, we separate the factor analysis groups from 40 to 70 indicators into “factors” based on how strongly correlated they are with each other. We typically find that six to eight factors are generated by the analysis, which can “explain” up to 90 percent of the variation of the indicators. Based on which indicators fall into which factor, the factors can be interpreted and labeled. For example, we have found that indicators that monitor the skills of a region’s workforce tend to be strongly associated with each other and are typically grouped into one factor that can be labeled a skilled workforce.

We then run these calculated factors in a regression model to statistically determine if they are associated with the selected performance indicators. In our previous work, we have consistently found that:

• a skilled workforce is strongly associated with per capita income growth;
• business dynamics—the opening and closing of firms and the number of small establishments—is strongly associated with employment growth;
• the region’s industrial legacy—its history of manufacturing—is negatively related to employment growth; and
• social isolation by income or race is negatively associated with employment growth.

Pitfall #2: Believing that more is better
One of the benefits of the statistically based approach is that it identifies a limited number of growth factors, which avoids the pitfall of not appreciating the fact that less is more. Tracking more data does not necessarily generate more clarity if the data are highly duplicative or measure activities that are not related to the goals of the organization. Some studies contain more than 100 indicators and can leave even the most attentive reader in a fog. Often two indicators seemingly tracking the same factor can move in the opposite direction. For example, employment by place of work often goes in a different direction from employment by place of residency in the short run. Too many indicators can only add confusion, lead to inaction, and, in general, do more harm than good. Remember, the resulting dashboard should look more like that found in a car than in the cockpit of an airplane.

Finally, once the performance measures are set and the factors that are associated with them are identified, then the regional economic development organization is set to develop strategies or tactics to address these factors. The key point is that the organization does not develop strategies that directly impact the performance measure, such as create jobs or personal income. Instead, the regional economic development effort is directed at forming more realistic strategies that address the factors associated with the performance indicators, such as creating a small business assistance program, designing customized training programs for area employers, or conducting retention visits with area employers. It is particularly challenging for economic development organizations to implement a strategy because they cannot direct area firms to follow the plan that may call for the adoption of better technology, the provision of workplace training, and the development of new products for expanding markets. Instead, they can only attempt to create an environment that is conducive for these actions, through the use of incentives and technical assistance. At best, economic and community development organizations have only a marginal influence on a limited number of the inputs required to substantially change the economic performance of their communities. 

The lack of direct control over the region’s economic assets, resources, and business decision making can be one of the most challenging aspects of implementing a strategic plan. Therefore, when constructing regional performance measures, it is necessary to control expectations. An excellent economic strategy can be thwarted by a bad economy or by a corporate decision to relocate a major regional operation.

Pitfall #3: Performance measures as net impact evaluations
In fact, this leads to another major pitfall to avoid: using performance measures to evaluate the impact of economic initiatives or programs. Change in regional per capita income is one of the best measures of an area’s economic performance. However, even the most effective economic development program will likely have little or no impact on the area’s per capita income. National, demographic, and industrial factors that are completely outside the influence of local organizations can have a much greater impact on an area’s per capital income. One of the greatest fears I have is that an outstanding economic development program that is costeffective and generates positive results could be terminated because it did not do the impossible: make a noticeable bump in the area’s per capita income or employment statistics. This is why a dashboard or scorecard should include program specific indicators as well as broader growth factors.

To recap, the development of regional performance measures should be part of a comprehensive economic development strategy that identifies the key growth factors that impact the region’s performance measurements. In some respect, the performance measurements—employment growth and per capita income, for example—could be considered a mountain peak, and the dashboard or scorecard tracks the progress of a community up the mountain. The summit may never be reached, but the community’s progress is being recorded.

Pitfall #4: Fixating on one indicator
There are two additional pitfalls that must be avoided along the climb. The first of these is to aim solely at a specific indicator. Indicators are simply that: they indicate if the region is going in the right direction. They provide evidence that the region’s workforce is becoming more skilled or the business environment is more dynamic. The regional economic development strategy should be directed at improving the quality of an area’s workforce or in enhancing the area’s business environment and not aimed at moving a certain indicator. The selected indicators should not become the focus of the strategy. Instead, they simply monitor whether a growth environment is being developed in the region. Although the percentage of residents between the ages of 25 and 34 who have a bachelor’s degree or higher is a reasonable indicator of the quality of the region’s workforce, raising this percentage would prove to be a difficult economic development strategy to articulate. Instead, the strategy could be to increase the number of internships offered to college graduates in the area, promote the area to professional and engineering services, and encourage social and cultural events aimed at young professionals.

Pitfall #5: Mistaking output or inputs for outcomes
The final pitfall is mistaking outputs—or even worse, inputs—for outcomes. The amount of resources utilized in generating activities should not be used as a measurement of the results of these activities. For example, a local economic development effort should not be measured by the number or size of fully serviced, site-ready parcels of industrial space that have been developed (inputs) or the number of brochures or tours generated (outputs). What matters is the amount of investment made in the area due to the availability of the site-ready parcels.

In conclusion, regional economic development strategies depend upon partnerships, the leadership and innovation of their key industries, the attitudes of its citizenry, and, of course, simple luck. Clearly, if a region’s residents do not believe in the importance of education, and if its major companies are not generating new products, its economic development organization cannot simply fire its residents and firms and hire new ones. Thus I believe that economic development organizations should be cautious in the development of economic indicators and dashboards, and be aware that regional performance measures are difficult to move and are impacted by events clearly outside the control of the organization. As with your car, an economic dashboard can show your speed (growth), fuel levels (human and physical resources), and miles traveled (industrial legacy); however, it says very little about the quality of your engine. An economic development organization should, of course, watch all these indicators, but its strategies should focus on improving the quality of its economic engine.

References:
Eberts, Randall W., George A. Erickcek, and Jack Kleinhenz. 2006. “Development of a Regional Economic Dashboard.” Employment Research 13(3): 3–5.

Erickcek, George A. 2007. Economic Dashboard Supplemental Report: Other Social and Economic Indicators. Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

Erickcek, George, Bridget Timmeney, Brian Pittelko, and Brad Watts. 2009. Social and Economic Indicators Typifying the Community’s Health. Report prepared for the Kalamazoo Community Foundation. Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

George A. Erickcek, and Brad R. Watts. 2003. An Economic Development Benchmarking System for Rural Michigan. Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

George A. Erickcek is senior regional analyst at the Upjohn Institute.