ILA 2023 Annual Conference

ILA 2023 Annual Conference

October 03, 2023

Keith Herndon, Kate Hester, Brittany Adams-Pope (2023). “Quantifying Innovation: An Empirical Index for Informing Communities and Empowering Community Leaders.” Interactive poster presentation accepted for the International Leadership Association annual conference, Vancouver, Canada, Oct. 12-15.

Quantifying Innovation: An Empirical Index for Informing Communities and Empowering Community Leaders

Keith Herndon, Kate Hester and Brittany Adams-Pope


This project presentation explores how the U.S. Economic Development Administration’s Innovation Intelligence Index, an online empirical tool, can be used as a resource for informing communities and empowering community leaders as they seek to understand their region’s strengths and weaknesses in a highly competitive economic development landscape. This project is part of an ongoing collaboration between Grady’s Cox Institute for Journalism Innovation, Management and Leadership and UGA’s Fanning Institute for Leadership Development.

As community leaders seek to improve their regions by attracting new business, creating new jobs and growing the population (Banyai, 2009), they are responsible for building on their regions’ strengths while mitigating their weaknesses. In 2018, a paper presented at the International Leadership Association’s annual conference proposed using the U.S. government’s productivity data as an empirical tool for understanding industry leaders and laggards and recommended industry trade groups and other organizations could use productivity data to help determine where to focus training resources (Herndon & Kor-Sins, 2018). Building upon that recommendation, this paper suggests the Innovation Intelligence Index is an ideal tool for journalists seeking to inform their communities and for empowering the leaders of those communities as they either launch or refine their economic development plans. This index provides users with analytic tools for exploring data and understanding a region’s potential. It will allow journalists to easily interpret and translate the data into digestible informative articles. Simultaneously, the insights gleaned from this tool and these articles are necessary for community leaders to reach “a strong consensus on regional strategic direction” (Slaper et al., 2016, p. 15). The tool can help them to better understand their region’s potential in the short term. Understanding this potential will empower community leaders to take action instead of maintaining stagnation to avoid possible risks. They can also use the insights gleaned from the data to create strategic plans focused on addressing identified weaknesses (Slaper, 2021).  This paper is intended to equally demonstrate how the Innovation Intelligence Index can be used by journalists as a source for informing communities about their innovation strengths and weaknesses and by community leaders to evaluate innovation capacity relative to competitive regions.

Explaining The Index Tool

The Innovation Intelligence Index helps quantify innovation in the U.S. and provides data-driven insights to assist community leaders with economic development (Slaper & Rogers, 2017). Dr. Timothy Slaper from the Indiana Business Research Center led the development of the tool with EDA funding. It can be found online for free at It provides users with innovation rankings and supporting data for four geographic levels: counties, metropolitan statistical areas (MSAs), economic development districts (EDDs) and states (Driving Regional Innovation: Supplemental Report for Innovation Intelligence, 2021).

The Innovation Intelligence Index uses data from a variety of sources to quantify the concept of innovation thereby allowing leaders to see their communities holistically in relation to other communities. Slaper et al. (2010) said the index is meant to “assist economic development practitioners to develop regional development strategies and to make public investments that yield the highest economic and social returns” (p.1). The index was created for these economic development practitioners (EDPs), specifically those in rural communities who may lack the resources needed to track their region’s performance consistently within the context of a constantly changing global economy (Slaper et al., 2010).

The index gives EDPs and other community leaders the “ability to assess their economic strengths and challenges, in addition to their capacity for innovation” (Slaper & Rogers, 2017, para. 2). Using this tool allows leaders to see their ranking within the index and compare their communities to their peer communities. The tool allows its users to drill down into the underlying data to look at their region more closely and determine the impact specific metrics may represent.

The Index data is derived from many proprietary and public sources including the U.S. Census Bureau, the U.S. Bureau of Labor Statistics, the Federal Communications Commission and the U.S. Department of Agriculture (Slaper et. al, 2010). An assessment is reached by measuring the inputs, human capital and knowledge creation, business dynamics, business profile, and outputs, employment and productivity, and economic well-being, of a region (Innovation Intelligence User Guide).

The current Innovation Intelligence Index is the third iteration of the tool. Slaper (2021) said the first version was rather simple in how it interpreted innovation relying mostly on patent data and technology occupations in a region.  The second version added measures to analyze to include “knowledge spillovers” from universities and investments in new production facilities (Slaper, 2021, p. 2). The third iteration has further refined the underlying data by including more statistics on broadband infrastructure and adoption and introducing a measure of latent innovation (Driving Regional Innovation: Supplemental Report for Innovation Intelligence, 2021).

Goetz and Han (2020) introduced latent innovation into the tool, a concept that measures locally occurring innovation that results from the spillover of ideas and insights across different firms and industries. This is done by, “considering both spatial proximity of firms as well as the flows of information that accompany exchanges of goods, services and funds among industries” (Goetz & Han, 2020, p. 1). This measure is an improvement on conventional measures of innovation, such as patents, research and development spending, and employment of science, technology, engineering, and math workers, because it tracks innovation which is often essential to raising productivity or improving products such as improved production processes or new product flavors (Goetz & Han, 2020).

Data Example

To illustrate data that can be extracted from the tool, this paper compares the Innovation Index rankings for 10 counties in Georgia. Using data from the U.S. Bureau of Labor Statistics, the state’s five counties with the lowest unemployment rates and the five counties with the highest unemployment rates for 2021 were selected.

Table 1 presents the data for the five counties with the lowest unemployment rates. The five lowest rates range between Oconee County at 2.2% and Banks County at 2.6% (U.S. Bureau of Labor Statistics, 2022). Oconee County received an innovation rating of 142.1, a high relative innovation capacity and a rank of 40 compared to all other counties in the country. Even though Oconee County has a very low unemployment rate, they still have a high capacity for innovation meaning that they have room to accept more businesses, create new jobs and attract more people to their county. Jackson County and Forsyth also have a high relative innovation capacity while White County and Banks County have moderate relative innovation capacities.

Table 1. Georgia Counties with the Lowest Unemployment Rates for 2021

County Unemployment Rate Innovation Rating Relative Innovation Capacity Rank
Oconee 2.2 142.1 High 40
Jackson 2.4 139.3 High 85
Forsyth 2.5 142.2 High 39
White 2.5 118.2 Moderate 1,044
Banks 2.6 108.5 Moderate 2,045

Source: U.S. Bureau of Labor Statistics, Innovation Intelligence Index

The top five counties with the highest unemployment rates range from Clayton County with 6.5% to Clay County with 10.2%. Clayton County, Dooly County, Crisp County and Clay County were all rated as moderate for relative innovation capacity. This means that there is some room for innovation within their economic development plans. Community leaders could use that space to attract new businesses and create new jobs, potentially lowering their unemployment rates. Telfair County received an innovation rating of 94.2, a low relative innovation capacity and rank of 3,031 out of 3,110 counties. In this case, it would be useful for Telfair’s community leaders to use the comparison feature of the index to examine the differences between their county and one with a better relative innovation capacity. For instance, they could compare themselves to Clayton County which ranked just above Telfair for unemployment but received a ranking of 534 on the Innovation Intelligence Index. They could reevaluate their economic development plan based on the plan of Clayton County.

Table 2. Georgia Counties with the Highest Unemployment Rates for 2021

County Unemployment Rate Innovation Rating Relative Innovation Capacity Rank
Clayton 6.5 126.4 Moderate 534
Telfair 7.2 94.2 Low 3,031
Dooly 7.3 105.5 Moderate 2,355
Crisp 8.6 108.2 Moderate 2,076
Clay 10.2 109.0 Moderate 2,002

Source: U.S. Bureau of Labor Statistics, Innovation Intelligence Index

Defining Innovation

Innovation drives productivity and is a key attribute for communities seeking growth (Demircioglu et al., 2019). Innovation is necessary for communities to adapt and grow, especially in uncertain economic times. Innovation becomes a catalyst for economic growth and performance. It increases competitiveness and raises the living standards and prosperity of citizens, resulting in lower unemployment (Demircioglu et al., 2019).

Innovation is often present in communities where the economy is adaptable and can readily move resources from lower value-added activities to higher value-added activities (Slaper et al., 2010). However, just because a region’s economy has not been adaptable historically, does not mean it cannot become adaptable (Simmie & Martin, 2010). Leaders in communities where innovation is lacking are responsible for helping to transform their economies (Hanna, 2018).

Today America is deep into the entrepreneurial revolution, something that is quickly becoming even more powerful to the twenty first century than the industrial revolution was to the twentieth century (Kuratko, 2007). As the entrepreneurial revolution progresses communities with fewer resources may fall behind. One way to prevent this is to innovate within the structure of the community and rewrite their economic development plans accordingly. This job falls to community leaders as economic development is often a primary goal (Banyai, 2009).

Defining Leadership

The concept of innovation is about coming up with an idea to fulfill an unmet need (Gutsche, 2020). Leadership plays an important role in innovation because change is something that is hard to accept. New ideas can be awkward, many times there is a lot of discomfort that can come from something new and barriers that block its potential (Gutsche, 2020). It is the role of the leader to have patience and to walk their population through the new idea to the potential. It is also their job to listen to the concerns of the population to understand what works and what does not work about a new idea.

Leadership is a process of interactive influence that occurs when a group of people accept someone as their leader to achieve common goals (Silva, 2016). Community leaders are both elected and appointed. Regardless they are leading the development of their communities and making decisions about the construction and implementation of successful activities in that community (Banyai, 2009). They define a vision for their community and identify the public economic development tools needed to accomplish that vision (Pagano & Bowman, 1997). They also control the amount of local government intervention in that process as it sometimes has certain funds and programs in place to assist with economic development (Pagano & Bowman, 1997). Community leaders do not have unlimited power, but they often have discretion to allocate funds that influence economic development activities. For example, they can decide whether to implement non-market, local government sponsored development in a vacant space rather than allowing a new business to fill it (Pagano & Bowman, 1997).

In today’s world, such decisions need to spring from an entrepreneurial mindset, but not every person has an entrepreneurial perspective. However, an entrepreneurial perspective can be developed (Kuratko, 2007). An entrepreneurial leader is adaptable but also effective and efficient. A leader is effective by ensuring that the right things get done and they each contribute to the success of the enterprise (Skripak, 2018). They are efficient by ensuring that these activities were performed in the correct way using the fewest possible resources (Skripak, 2018).

Fang and Slaper (2022) said there are two important aspects of a community: place and people. The place-based approach for development focuses on improving the physical environment to spur social interactions and exchange ideas while the people-based approach focuses on cultivating human capital. Entrepreneurial leaders must evaluate each of these aspects to get a full picture of their community before implementing new practices. Entrepreneurial leaders will use each of these aspects to their advantage. They can also combine these two ideas with the concept of community capacity. Community capacity is “the interaction of human capital, organizational resources, and social capital existing within a given community that can be leveraged to solve collective problems and improve or maintain the well-being of that community” (Banyai, 2009, p.3). An entrepreneurial leader can steer this interaction in the right direction for their community.

Using the Index for Informing

The American Press Institute says that the purpose of journalism is to “provide citizens with the information they need to make the best possible decisions about their lives, their communities, their societies, and their governments” (American Press Institute, 2023). When making a decision the best possible choice is often found by looking at the data available. Many journalistic pieces provide citizens with hard data that has been dissected and simplified to make it easy to understand. This type of journalism is referred to as data journalism. Data journalism is a rapidly evolving field as many newsrooms have a dedicated data team and others are striving to create one (The State of Data Journalism, 2022).

The field of data journalism came from blending together “different data sources, analysis tools and visualizations to create powerful stories” (The State of Data Journalism, 2022). The Innovation Intelligence Index itself is also a blend of these three pillars. However, online search has revealed no instances of the data provided by the innovation intelligence index cited in the general press. Raw data itself is not always the easiest thing to understand but data journalists are trained to explain data in a way that is easy to understand. The other side of a data journalist’s job is to actually find that data to explain. (The State of Data Journalism, 2022). The index itself is a wealth of information and even the smallest bit of data it provides could be used as the foundation for a powerful story.

Datasets such as the Innovation Intelligence Index could soon be used in connection with Artificial Intelligence (AI) to assist journalists in making sense of the material. As Seth (2023) explained, AI “plays a crucial role in detecting trends or patterns” when used in connection with large datasets, and AI can be used use to create visualizations to make the data easier for audiences to understand. Journalists are already adopting AI tools into their processes (Lopez, et al., 2023) and rich datasets such as this should be among the material used as AI adoption in newsrooms continues. Moreover, using reputable datasets such as the Innovation Intelligence Index become imperative as newsrooms wrestle with trustworthiness issues associated with content generated through AI interfaces (Opdahl, et al., 2023).

Using the Index for Empowering

Empowerment, as a theory, was created by Freire (1973; 2005) to develop a plan to liberate oppressed people globally. In more recent times, empowerment has been used to justify and support local, grassroots community-based initiatives (Hur, 2006). Hur (2006) suggests that for individuals, groups, or communities, empowerment can be a fluid process that may change over time but can also be a tangible and measured outcome. Slocum, Wichhart, Rocheleau, and Thomas-Slayter (1995, p.4) define empowerment through the community lens as “a process through which individuals, as well as local groups and communities, identify and shape their lives and the kind of society in which they live.” Using this definition, we believe the index can be an invaluable tool for community leaders to enact the change their communities need.

Just as the data provided by the index can be used by journalists to inform the public, community leaders can also use it to affirm their decisions and community initiatives. As an example, if an economic development project receives pushback from the community, supporting data from the index could be included in press articles and or community meetings to explain the expected positive outcomes. Having a unbiased data to share with community members will assist with transparency from community leaders as to why they are supporting new initiatives but also can assist leaders in transforming their current models and processes to become more innovative and efficient. Instead of community members be asked to “just trust us” by community leaders, they can analyze the index themselves and make more informed decisions.


When the index was introduced, its creators predicted the data resource would only become richer over time (Slaper et al., 2010). Over ten years later, this has proven true. With each iteration more data has added, complied and cleaned giving users a clearer picture of their region. As communities grow and evolve the data changes making the index a potentially endless source of information for journalists to pull from when working to inform their readers. The tool also allows community leaders to see which drivers of innovation matter most in their regions. This knowledge can help policy makers, as well as practitioners, to design more effective economic development initiatives (Slaper et al., 2010).

The Innovation Intelligence Index allows community leaders to compare innovation at the county-level (Slaper et al., 2010). Community leaders can use the index find and compare their county to a county they aspire to emulate. They can organize their results into a SWOT analysis, which Kelly (2015) describes as a list of strengths, weaknesses, potential opportunities and threats. This would be an excellent activity in a community leadership development program as it would help leaders to organize the information and define the right goal. It will also show leaders exactly where they should be applying their resources.

Another recommendation based on this research would be for community leaders to take a hard look at the internet access in their area. Communication is a driver of innovation and communication has never been easier thanks to the internet, “access to high-speed Internet allows businesses and individuals to share new ideas with others from virtually any location” (Slaper et al., 2010). The index’s new measures of broadband infrastructure and adoption and broadband adoption barriers signify broadband’s positive impact on innovation. Through comparison with other counties leader may find that they have excellent internet access or that their neighbors have better alternative to their current plan.

Finally, community leaders should strive to be entrepreneurial. This does not mean that they need to go out and come up with the next big idea every other day. Instead leaders should make an effort to embrace change. Gutsche (2020) advised to “master change and you will be in a position to better spot new ideas, act on opportunity, and know how to convince others about your wonderful new vision” (Gutsche, 2020, p.1).



Banyai, C. (2009) Community Leadership: Development and the Evolution of Leadership in Himeshima. Rural Society, 19(3), 241-261, DOI: 10.5172/rsj.19.3.241

Demircioglu, Mehmet A., Audretsch, David B., Slaper, Timothy F. (2019). Sources of innovation and innovation type: firm-level evidence from the United States, Industrial and Corporate Change, 28(6). 1365-1379.

Driving Regional Innovation: Supplemental Report for Innovation Intelligence. (2021). Stats America.

Indiana Business Research Center. (2016). Driving Regional Innovation: The Innovation Index 2.0. Stats America.

Fang L. & Slaper T., (2022). Nowcasting Entrepreneurship: Urban Third Place versus the Creative Class. Sustainability. 14(2).

Freire, P. (2005). Freire: Education for critical consciousness. New York, NY: Continuum.

Goetz, S. J. & Han, Y. (2020). Latent innovation in local economies, Research Policy. 49(2).

Gutierrez Lopez, M., Porlezza, C., Cooper, G., Makri, S., MacFarlane, A., & Missaoui, S. (2023). A question of design: Strategies for embedding AI-driven tools into journalistic work routines. Digital Journalism, 11(3), 484-503.

Gutsche, J. (2020). Create the future: Tactics for disruptive thinking and the innovation handbook. Fast Company Press.

Hanna, N. (2018). A role for the state in the digital age. Journal of Innovation and Entreprenureship.7(5).

Herndon, K.L. & Kor-Sins, R. (2018). Labor Productivity: Proposing the Economic Metric as an Empirical Leadership Proxy. Presented at the International Leadership Association conference, West Palm Beach, FL, October.

Hur, M. H. (2006). Empowerment in terms of theoretical perspectives: Exploring a typology of the process and components across disciplines. Journal of community psychology34(5), 523-540.

Innovation Intelligence User Guide. (2021). Stats America.

Kelly, S. (2015). The Entrepreneurial Journalist’s Toolkit: Manage Your Media. Taylor and Francis.

Kuratko, D. (2007). Entrepreneurial leadership in the 21st century. Journal of Leadership and Organizational Studies, 13(4), 1–11.

Opdahl, A. L., Tessem, B., Dang-Nguyen, D. T., Motta, E., Setty, V., Throndsen, E., … & Trattner, C. (2023). Trustworthy journalism through AI. Data & Knowledge Engineering, 146, 102182.

Pagano, M. A., & Bowman, A. O. M. (1997). Cityscapes and capital: The politics of urban development. JHU Press.

Seth, N. (2023). Understanding The Role of AI in Big Data [and Vice-versa]. Analitix Labs, May 31.

Silva, Alberto. (2016). What is Leadership? Journal of Business Studies Quarterly. 8(1).

Simmie, J. & Martin, R. (2010). The economic resilience of regions: towards an evolutionary approach, Cambridge Journal of Regions, Economy and Society. 3(1). 27–43,

Skripak, S. J. (2018). Fundamentals of Business. VT Publishing.

Slaper, T., Hart, N. R., Hall, T. J., and Thompson, Michael F. (2010). The Index of Innovation: A New Tool for Regional Analysis. Economic Development Quarterly. 25:1,36-53

Slaper, T., Walton, T., & Harmon, K. M. (2016). Business dynamics and economic performance in the Midwest. Indiana Business Review, 91(3), 1-15.

Slaper, T. & Rogers, C. O. (2017). Innovation 2.0 – What’s in your wallet? Indiana Business Review, 92(1).

Slaper, T. (2021). The dark energy and matter that drives economic performance. Indiana Business Review, 96(1), 1-11.

Stats America. Innovation Intelligence Index. Retrieved from

Slocum, R., Wichhart, L., Rocheleau, D., & Thomas-Slayter, B. (1995). Power, process and participation: tools for change. London, UK: Intermediate Technology Development Group (ITDG) publishing.

The American Press Institute. (2023). What is the purpose of journalism? The American Press Institute.,their%20societies%2C%20and%20their%20governments.

The State of Data Journalism. (2022). Data Journalism.

U.S. Bureau of Labor Statistics. (2022, April 15). Local Area Unemployment Statistics. Retrieved from