21 Jun You need to describe the organization and indicate how its operation, management, or functioning can benefit from spatial analysis through GIS. 2. What are the
in Business & Finance
1. you need to describe the organization and indicate how its operation, management, or functioning can benefit from spatial analysis through GIS.
2. What are the sources you recommend of GIS data?
3. How do you recommend that the GIS and its data be organized?
4. What spatial analysis can be done?
5. What are the prospective benefits and costs of the GIS application?
6. How do you justify that the application offers competitive advantages?
7. You are encouraged to bring in some relevant information systems concepts from BUSB 333 (Business Information Systems).
8. One example of such a concept from BUSB 333 is Michael Porter’s Five Forces framework for competitive IS
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Do not distribute except to students using the book in a course.
Table of Contents
Chapter 1. Fundamentals of Location Value 8
Chapter 2. Fundamentals of Spatial Technology 23
Chapter 3. Fundamentals of Location Analytics 43
Chapter 4. Growing Markets and Customers 63
Chapter 5. Operating the Enterprise 87
Chapter 6. Managing Business Risk and Increasing Resilience 106
Chapter 7. Enhancing Corporate Social Responsibility 120
Chapter 8. Business Management and Leadership 138
Chapter 9. Strategies and Competitiveness 156
Chapter 10. Themes and Implications for Practice 173
Technology and Location A quarter-century ago, Frances Cairncross (1997) proclaimed the “Death of Distance”
and a future not bound by location but connected via the electronic revolution. In the ensuing decades, it has undoubtedly been the case that individual lifestyles, the economy, and the world have been transformed by ongoing digital transformations.
But, alas, 25 years later, location is not dead, but deeply intertwined with technology. We live in a global economy, but that economy varies widely by region and location. We live in a high-tech world that allows for unparalleled virtual connections, and yet these high-tech companies tend to cluster in certain regions of the world. We live in a world where shopping can be done entirely online, but these products are sourced through intricate supply chains that deliver the product to one’s doorstep.
Location intelligence is embedded in these contemporary dynamics—that is, businesses need to know where to source, where to operate, where to market, where to grow, and so forth. This book is intended to inform business professionals as well as business students about this new world of location intelligence and how to utilize this intelligence to achieve business success. It also aims to inform geographic information system (GIS) professionals and students about how location analytics can be considered and utilized within business functions and strategies. Indeed, the book unites these domains (business, GIS) into a sphere we call Spatial Business.
To support business progress in this expanding space, the geospatial industry is growing in its capacity to support location analytics, GIS, web and cloud-based processing and display, satellite and drone imagery, LIDAR scanning, and navigation and indoor positioning tools. The total size of the geospatial industry is estimated to be $439 billion (US) by 2024 and at a compound annual growth rate of 13.8% (GMC 2019).
With this level of location digitization and growth, location intelligence has become foundational to business in its marketing, operations, services, risk management, deployment of assets, and many other functions. Through location analytics and location intelligence, a firm can leverage location information to make better-informed decisions and ultimately create value to the business and often to society as well. There are numerous examples of companies that have successfully built-up location analytics capacity and have been able to use the ensuing insights to better serve consumers, operate more efficiently, and achieve competitive advantage. What has been needed is an integrated perspective on these developments and that is the aim of this book.
Spatial Business Organization This book seeks to provide a contemporary foundation for understanding the business
and locational knowledge base to solve spatial problems, support location-based decision-
making, and create location value. Our approach is to do so can be seen in Figure 1, which provides an overview of the book’s organization and key concepts. The opening segment (Chapters 1-4) introduces spatial business foundations. Following these foundations, the book dives deeper (Chapters 4-7) into achieving business and social value in four areas (growing markets and customers, managing the organization, managing risk, and resilience, corporate social responsibility). The book then turns (Chapters 8-9) to the management and strategy elements aimed toward spatial excellence. The book concludes (Chapter 10) with a summary of key themes and a set of implications for practice for each of the themes. What follows is a brief preview of key concepts, applications, and company cases that are examined in the book.
Figure 1. Organization of Spatial Business Book, showing how each of the ten chapters fit within three sections
Spatial Business Fundamentals Spatial business refers to concepts, techniques, and actions that enhance the use of
locational insights to achieve business and broader societal goals. Spatial Business Fundamentals (Part I) begins by considering the fundamental principles of locational value and how understanding location value chains can inform various business functions such as marketing, operations, and supply chains. Chapter 1 also outlines levels of a company’s spatial maturity as well as the process of gaining maturity. The Shopping Center Group is provided as an example of a company with high spatial maturity and strategic use of location analytics.
These business and locational concepts provide an underpinning for describing the Spatial Business Architecture, which is outlined in Chapter 2. The architecture begins with the business goals and needs, then addresses business users and stakeholders who have responsibilities for addressing these business goals and using location analytics to do so. The
architecture continues with a series of location analytics tools to be applied to business areas, tools that depend on various forms of location data. Supporting all of these functions are the various platforms that host spatial business processes, such as the cloud, the enterprise, or mobile services. The final component is the net consequence in terms of location intelligence that can be used to provide business insights, inform decisions, and have an impact on business performance. Companies such as Zonda, OverIt, and Walgreens are described as examples of effective architectural deployments.
Location Analytics lies at the heart of the Spatial Business Architecture. Chapter 3 provides a deeper presentation of the use for descriptive, predictive, and prescriptive analyses. Descriptive location analytics provide exploratory spatial analysis of business patterns as well as visualization of patterns. Predictive location analytics encompasses spatial statistics to detect and predict business patterns, clusters, and hotspots. Prescriptive location analytics are often the most complex and can include spatial forecasting, space-time analysis, and GeoAI (geographic artificial intelligence). Examples of business use of these analytics are provided throughout Part II of the book.
Achieving Business and Societal Value Building on these Spatial Business Fundamentals, Part II explores the use of spatial
analytics across the business goals, featuring growing markets and customers operating the enterprise, and managing risk and resilience. It also considers the role of spatial business applications to understand and track a company’s social responsibility or what has been termed the “new purpose of the business”.
The role of location intelligence is evolving rapidly as geo-marketing is leveraged by organizations to generate deep locational insights about customers and markets. Chapter 6 analyzes the role of location analytics in market and industry cluster analysis to identify business opportunities, determine consumer preferences and buying patterns with customer segmentation, scrutinize geotagged social media streams to examine patterns and relationships between consumer sentiment and actual sales, and determine best locations for new facilities. The chapter also discusses the linkage of location analytics with the “7 Ps” of marketing. Acorn, Fresh Direct, Heineken, and Oxxo are provided as examples of location analytics used for growing markets and customers.
Effective management of business operations is a highly varied, process-oriented part of the organization and its functioning is critical to achieving business goals. Chapter 7 outlines how location analytics spans to include situational awareness to facilities, ensuring business and service continuity, and achieving efficiencies in supply chains and logistics. Chapter 8 focuses on risk and resiliency. Using location analytics, companies can gain a new way to measure and initiate operational actions action ahead of time, gaining the advantage of being proactive in managing risk. With improved visibility via dashboards, there is the capacity to quickly adjust to events such as natural disasters and COVID-19 related closures. Cisco, CSX Rail, and Travelers Insurance are provided as examples of location analytics using operational and risk management.
Corporate Social Responsibility (CSR) calls for a company to be socially accountable in ways that go beyond making a profit. The company takes a broader view of its goals, thinking not only of its stockholders, but also of the benefits to its employees, customers, community, the environment, and society as a whole. This expansive role of the business to address social, racial, economic, health, and educational inequities has been heightened worldwide by the COVID-19 pandemic. As corporate leaders navigate their businesses through increasingly uncertain business and geopolitical environments in the post-COVID world and are pressured to achieve growth, they are also being called to shape their organizations’ role in confronting and addressing these items. Chapter 7 outlines “shared value” strategies and actions by companies to use location analytics to address issues such as climate change impacts, sustainable supply chains, UN (2030) sustainable goals, and economic advancement of underserved communities. Marx and Spenser, Nespresso, Natura, AT&T, and JP Morgan are provided as examples of how location analytics can contribute to these important societal goals.
Toward Spatial Excellence A driving theme is that location analytics should not be considered an isolated GIS
undertaking, but rather an integral analytical function for creating business success. Given the importance of management and senior leadership in an enterprise’s spatial transformation, Part III details the application of management principles allied with spatial business strategies and building the location analytics workforce to accomplish this transformation. It concludes with implications for practice that serve as action items for those engaged in spatial business.
Chapter 8 outlines critical dimensions of spatial leadership needed to achieve spatial maturity, where location analytics become intertwined with business strategies and business gains. Core activities that are discussed include demonstrating the value of location analytics to key business goals, championing spatial initiatives, and developing the workforce capacity to achieve these goals. Companies such as CoServ Electric, and British Petroleum (bp) are provided as examples of effective spatial management and leadership.
Chapter 9 moves from leadership and management into strategic and competitive actions. Geospatial strategic planning is characterized as having both external and internal elements. The external element focuses on how location analytics can be used to strengthen the firm’s competitive position or modify forces affecting competition, such as customer relationships or new products. Internal planning emphasizes improving the firm’s own geospatial infrastructure and processes. The internal element focuses on the alignment with business needs, technological capacity, and human resource requirements to achieve desired location and business value. These strategic actions are demonstrated by both a large company example (Kentucky Fried Chicken) and a small company (RapidSOS) example.
The concluding chapter (10) moves to Implications for Practice from all that has been presented in the book. This discussion is centered around 10 themes that can guide spatial business actions:
1. Identify and Enhance Location Value Chain
2. Enable Spatial Maturity Pathway
3. Match Analytical Approach to the Business Needs
4. Build a Spatial Business Architecture
5. Use Market and Customer Intelligence to Drive Business Growth
6. Measure, Manage, and Monitor the Operation
7. Mitigate the Risk and Drive the Resiliency
8. Enhance Corporate Social Responsibility
9. Inspire Management to Capture Vision and Deliver Impacts
10. Solidify Spatial Leadership for Sustainable Advantage
A set of Implications for Practice are provided as specific steps that be taken to achieve an effective Spatial Business strategy and operation that will contribute to business success in today’s competitive and complex environment.
We hope you will find the following chapters to be informative about principles, concepts, and practices of Spatial Business and will inspire their use for business and societal gain. For leaders, it represents an important opportunity to leverage location intelligence for strategic leadership and competitive gain. For analysts, it is an exciting opportunity to deploy innovative location technologies and applications that can have a demonstrable impact. For students, it is a growing field of study and profession that complements and widens traditional business education and professions. For all, spatial business has elements that broaden the space of inquiry to consider related societal outcomes, challenges, and benefits for communities and the world.
The publication of Spatial Business represents a product of four years of work undertaken by the authors, who each made an equal contribution to the book. This book is a part of a Spatial Business Initiative conducted in cooperation with Esri. The partnership has been invaluable in providing a forum for investigating trends and developments in business location analytics. We are deeply grateful to Jack and Laura Dangermond for their support of this initiative. Special thanks are due to Cindy Elliott for her strong partnership as the designated lead at Esri as well as her insightful reviews of draft chapters. Nikki Paripovich Stifle and Karisa Schroeder provided expert input on several chapters, especially Chapters 2 and 10. We are also appreciative of the guidance provided by so many at Esri Press, especially Catherine Ortiz, Stacy Krieg, Dave Boyles (in the early stages of the project), Alycia Tornetta, and Jenefer Shute. The book has also benefited from our participation in Harvard Business School’s Microeconomics of Competition (MOC) network. Several key concepts in the book (e.g., location value chain, cluster mapping, and shared value) were inspired by materials, presentations, and collaborations made possible through the network.
During the book project, various forms of research and outreach were conducted to inform the concepts, methods, and cases outlined in the book. The most intensive of those efforts was the case study research for which several private sector leaders in charge of geospatial strategy and location intelligence provided keen insights about their respective organizations. We want to thank Gregg Katz, formerly of The Shopping Center Group, Ben Farster of Walgreens, Enrique Ernesto Espinosa Pérez of OXXO, Kurt Towler of Sulphur Springs Valley Electric Cooperative, Joe Holubar of Travelers Insurance, Brian Boulmay, formerly of British Petroleum, Lawrence Joseph of KFC, Martin Minnoni of RapidSOS, and Andy Reid of Zonda. Each of them agreed to be interviewed as part of our spatial business research, shared nuanced insights on how location analytics is shaping competitiveness and strategies in their respective organizations, and were generous with their geospatial industry perspectives. Esri’s Cindy Elliott, Helen Thompson, and Bill Meehan were instrumental in connecting us to several of these experts, and their roles are gratefully acknowledged.
We convey our thanks to several former and present graduate students who provided research assistance at various stages of the project. Anuradha Diekmann, Lauren Salazar, Simisoluwa Ogunleye, Jahanzeb Khan, and Burt Minjares helped to record and transcribe case study interviews, and to collect relevant secondary information from various companies, businesses, academic journals, and business information databases. They distilled key findings and corroborated the findings with the research team members and knowledgeable business contacts, and also helped us procure permissions for the project’s artwork. In addition to these talented students, we would also like to thank Kian Nahavandi in our school for her valuable administrative support for the book.
Finally, the University of Redlands provided a hospitable environment for the project. We are grateful to colleagues at the University for their steadfast encouragement and support for this project.
SPATIAL BUSINESS: COMPETING AND LEADING WITH LOCATION ANALYTICS
Fundamentals of Location Value
Creating Value If we begin with the premise that the purpose of a business is to create value, how do
we identify specific value? Focusing on the private sector, this value is typically revealed in products and services that are successful in the marketplace. Technology companies provide products that are purchased, real estate companies provide homes and office buildings that are purchased or leased, consultants provide advisory services that are procured. Every sector of industry, including government and nonprofits, has a range of specific value that it creates.
From a competitive perspective, this value is framed within the context of a company’s unique “value proposition” to its customers. Anderson, Narros, and Rossum (2006) identified three types of value proposition: all benefits, comparative advantage, and resonating focus. An all-benefits value proposition represents the comprehensive set of customer benefits a company provides, while a comparative advantage value proposition highlights its value relative to the competition. A resonating value proposition—considered the gold standard of value propositions—identifies the key points of difference that will deliver the most compelling value to the customer.
The challenge and opportunity of location analytics is to provide business insight into how location affects these value propositions, taking into account a host of geographic, economic, technological, environmental and societal actors.
Sustainable Value While many companies rightly focus on their value proposition to customers, broader
value considerations affect their business activities and decisions. In the five decades since economist Milton Friedman famously proclaimed that the sole responsibility of business is to make a profit, there has been a growing recognition that the purpose of a company entails yet transcends its profit-making capacity. On August 22, 2019, in recognition of this expanded view of the role of business in society, the prestigious US Business Roundtable announced a revised articulation of the purpose of a business. (Business Roundtable 2019) This broader perspective, backed by 181 of the top US companies, includes the following dimensions: delivering value to customers, investing in employees, dealing fairly and ethically with suppliers, supporting communities, embracing sustainable business practices, generating long-term value for shareholders, and effective engagement with shareholders. As Darren Walker, President of the Ford Foundation observed at the time of the announcement, “This is tremendous news because it is more critical than ever that businesses in the 21st century are focused on generating long- term value for all stakeholders and addressing the challenges we face, which will result in shared prosperity and sustainability for both business and society” (Business Roundtable, 2019).
These developments are often framed within the context of corporate social responsibility (CSR), and more recently Environment, Social, and Governance (ESG) factors. KPMG has conducted an annual survey since 1993 on global corporate CSR/ESG activities and reporting. At the time of the 1993 survey only 12% of the (N100) top companies in surveyed companies were reporting on their CSR-ESG activities. As of 2020, this reporting had grown to 85%. Moreover, the growth in the top global corporations (G250) which they started surveying in 1995) as gown to 90% (see figure 1.1) (KPMG 2020). Companies are clearly seeing the connection between their actions and the surrounding world, and the need to track and address societal and environmental factors that could inhibit their success. For example, that same 2020 survey found that top global (G250) reporting on the threat of global climate change as a financial risk had grown from had grown dramatically for both groups, with 43% of top global companies (G250) noting the risk and 53% of top national companies(N100) noting this financial risk.
Figure 1.1 Growth in ESG Reporting by Top National and Global Companies (trends for top national and global companies are displayed in dark blue and light blue lines respectively)
The COVID-19 pandemic has only served to intensify the interlinkages between companies and societal conditions. During the pandemic business have had to radically change employee work patterns and relationships with customers and do their part to safeguard to health and safety of all of those within their business ecosystem–all this amidst dramatic economic and employment contractions. It has become clear that the health and safety of employees is not only of great consequence when they are “at work” but depends upon the conditions of the environments and communities they live in and travel to.
Turning to the focus of this book, it is also the case that business location analytics has a role to play in advancing this broad purpose of business in delivering value to customers, communities, and the global environment. Such as role can be best introduced by considering the spatial decision cycle that enhances business value.
Spatial Decision Cycle Given these various dimensions of value (ranging from a product to a societal impacts), how can one start to spatially think about enhancing such value through location analytics.? It is useful to consider a cycle of four elements in a spatial decision process: value, spatial thinking, location analytics, and data (see Figure 1.2). The cycle begins with understanding the value created by a company’s products and services. It then considers the spatial dimension of the value created, followed by the appropriate location analytics suggested by this spatial thinking. The cycle then turns to the data requirement for achieving the desired location-analytics insights and concludes with the value added by these insights for business priorities.
Figure 1.2 Spatial Decision Cycle, showing linkages between its key elements: Value, Spatial Thinking, Location Analytics, and Data
Element 1: Value (proposition)
From a strategic perspective, spatial decision-making begins with business goals to deliver a company’s “value proposition” through market and customer growth, achieving competitive advantage in offerings, driving operational efficiencies, and managing risk and regulatory compliance. Taking into account the dimensions outlined by the Business Roundtable, these goals can also include upgrading employee skills, ensuring effective and sustainable supply chains, supporting local communities, and improving environmental conditions.
For example, the case of gourmet coffee maker Nespresso illustrates a company strategy that embraces these objectives and embraces location analytics as a means to achieve them. As the company notes in its Business Principles, their value proposition is to “promise consumers the finest coffee in the world that preserves the best of our world” (Nespresso, 2021). Similar to the Business Roundtable new statement of purpose, Nespresso notes that ” If we are to be successful – not only as a business, but in delivering on this promise – we know we must earn the trust and respect of our people, our customers, our suppliers and wider society.” As well be outlined in the Nespresso Case Study (in Chapter 8), a key aspect to delivering on this promise is the use of location analytics, to monitor and manage achieving a variety of business, environmental and community goals under their “Positive Cup Framework” (Nespresso, 2021). Of course, not every company operates in the same context as Nespresso, but a key value proposition can usually be discerned, with priorities that set the stage for spatial thinking.
Element 2: Spatial thinking
This second stage of the cycle focuses on utilizing spatial thinking to translate business objectives into spatial considerations. Spatial thinking is considered a form of intelligence, along with other forms of intelligence such as logical and interpersonal (Gardner, 2006). The National Research Council (2006) noted that there are three components to spatial thinking: spatial attributes, representations, and reasoning. In spatial business, spatial attributes refers to the ways to measure and assess location dynamics such as in trade areas, supply-chain transportation and so forth. Representations include various means of rendering spatial dynamics, such as customer cluster maps, business space-time trendlines, and supply network visualizations.
Perhaps the most important component is spatial reasoning. In spatial business, this calls for constructing a line of inquiry that reveals the influence of locational factors on business success. For example, a hospital can examine its supplier network to determine where in the supply chain interruptions are occurring. A retail company can examine trends in sales across different customer markets to determine where new stores should be opened because such locales have a strong presence of desired customer profiles.
A classic example of strategic spatial reasoning is the case of the investment company Edward Jones. Edward Jones started as a “small-town” investment firm in Missouri. The company viewed its comparative value proposition as providing a single investment service to more rural
communities, compared to Merrill Lynch, which provided full-service portfolios in large metropolitan areas (Collins & Rukstad, 2008). In the early 1980s, Edward Jones conducted a series of analyses and consultations and discovered that its resonating value proposition was that it offered a highly personalized investment service to those individual customers who wanted to delegate investment decisions. It further discovered that it could competitively offer these services in select rural and select metropolitan locales where such customer profiles were strongly represented. The company then proceeded to operationalize the new market mix. This spatial reasoning resulted in the rapid growth of Edward Jones from 400 to 1,000 locations in a seven-year period and remains its driving focus today (Edward Jones, 2020).
Element 3: Location analytics
Clear spatial thinking drives the choice of location analytics. If a business is mostly interested in a general understanding of spatial trends in customers, assets, suppliers, and so forth, then descriptive analysis can provide situational awareness through maps and infographics. If a business desires to carry the spatial analysis further, to understand how spatial insights can help achieve business value priorities, then explanatory analysis can be conducted to help explain dynamics such as why growth did or did not occur, or why certain sites or locations were or were not successful. If a business wants a predictive analysis of the likely success of a service, product, or location, it can conduct predictive spatial analysis. And if a business wants to know where to locate new locations or serve new markets, it can conduct prescriptive analysis. These spatial analysis approaches are reviewed in detail in Chapter 3.
Many industries are advancing their analytical capacities to move from descriptive to predictive and prescriptive analytics. As one example, the insurance industry is rapidly evolving to adjust to the more extreme climate conditions brought on by climate change and other socio- demographic and economic changes. Companies such as Travelers Insurance now employ a full range of location analytics to assist a range of business-critical functions (Travelers Insurance, 2021). These include predicting the location of natural disasters (for underwriting purposes), analyzing damage locations (for claim purposes), and identifying high priority locational impacts (for disaster response). These tools have been used with great success for recent hurricanes on the east coast and wildfires on the west coast (Claims Journal, 2019).
Element 4: Data
The fourth element in the spatial decision cycle is data. As the expression goes, “You are only as good as your data.” A business may have a driving need to use location analytics to enhance its success but will be hampered without the appropriate data. Typical data types include sales, profit, customer, cost, asset, and network data. In addition to this proprietary data, numerous governmental and commercial datasets can inform location analysis—for example, trade-area analysis, business transactions, supply chain network data and social, economic and environmental trends. Companies are leaning into digital transformation and, as part of that, aligning their various business intelligence enterprises, which includes enhanced interoperability of these data sources.
In addition to the need for “location stamped” data, three other data issues that deserve attention are the level of geographic specificity, the availability and consistency of data over time, and the policies surrounding data use. Regarding the first, the greater the level of granularity the better the analysis, although many publicly available data sets will limit the granularity for reasons of privacy and anonymity. Regarding the second, temporal data is critical for looking at spatial changes over time, such as the growth or decline of customers, sales, inventory, etc. An
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