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to interpret the visuals and make recom-mendations. Finally, companies must manage the data, visuals tools, and les-sons learned in order to be effective.

A Visual ApproachDecision makers that want to visu-alize ecosystems need a structured

CO M PA N I E S C A N N O longer rely on just their internal competencies. They must complement their own competencies with those of

other firms through alliances, part-nerships, and digital relationships. Google, by opening its mobile An-droid platform to manufacturers and developers, has become the leading apps provider in the mobile space. These multifaceted interdependen-cies create complex connections, or ecosystems, that affect and are affect-ed by multiple stakeholders such as suppliers, distributors, outsourcing firms, makers of related products or services, and technology providers.3 Competition today is between eco-systems. Understanding ecosystems can then help managers improve strategic decisions and reshape the boundaries of their industries. In-terpreting this network of interac-tions, however, can be difficult. For example, a nascent ecosystem like the Internet of Things (IoT) has no dominant player and is increasing in scale, scope, and complexity.4 Under these circumstances, companies can have difficulty determining the most effective business opportunities.

We describe a graph theoretic visu-alization method to help companies map relationships between ecosystem stakeholders. To visualize ecosystems

effectively, many entities, activities, and tools are required. Capturing, gen-erating, and interpreting ecosystems requires a sponsor who wants to learn more about a company, a technology, or an industry, data scientists to collect salient data and prepare it for analysis, visualization tools, and a domain expert

Economic and Business Dimensions Visualization to Understand Ecosystems Mapping relationships between stakeholders in an ecosystem to increase understanding and make better-informed strategic decisions.

DOI:10.1145/3000610 Bala R. Iyer and Rahul C. Basole

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platform companies for the IoT ecosys-tem. Lists can be augmented by semi-open sources such as Crunchbase or Angel.co or paid services such as Dun & Bradstreet, DataFox, and CB In-sights. Once finalized, the analyst can visit each company’s website to iden-tify listed partners that provide servic-es or components for platforms and document dependencies. Most com-pany websites list strategic alliances or partners, and describe the types of relationships (for example, technical, marketing, licensing, and so forth) and content (for example, date formed, nature, and other characteristics).

Finalize semantics for nodes and dependencies: Based on the data col-lected so far, the analyst can prepare it for visualization. Some software requires explicit specification of the visual encodings of nodes and edges (including the attributes that drive color, shape, size, and dependen-cies), and particular consideration to data type (that is, quantitative, ordinal, categorical). More recent software packages (for example, Tab-leau, Gephi, ecoxight) allow dynamic selection of attributes and assign-ments. Node sizes are usually based on a company’s revenue or number of employees. Dependencies are often color coded, based on relationship.

Visualize, analyze, and interpret: The visualizations in the figures in this column use Gephi, an open source graph visualization tool.2 Many visualization packages offer different network layout algorithms. Most com-monly used are derivations of force-directed layouts, in which prominent nodes are drawn in the center and less prominent ones are pushed to the pe-riphery. Nodes close to each other have stronger associations. After visualiza-tion, the sponsoring organization can be asked for feedback to determine if they have any insights about compa-nies in key network positions or clus-ters of interest, find any surprises, and identify companies that did not make the list. Corrections are incorporated in subsequent analysis. This iterative process creates confidence in the visu-alizations.

Interpreting the VisualizationAs noted, the IoT is a complex ecosys-tem not yet dominated by any single

approach and several visual repre-sentation methods can be used.1 The methodology consists of steps dis-cussed here. This approach is not lin-ear; there are many feedback loops be-tween the stages. Progress is guided by human decision making along the way. We use The Internet of Things (IoT) as an illustration of this methodology.

Determine industry structure: Think of an industry as a company, its com-plementors and competitors. Identify the value chain or stacks of activities that deliver something of benefit to customers. These are inferred from industry publications and company websites. Industry structure helps the analyst identify the companies that are the major platform companies in an

industry. For the IoT industry, the stack shown in Figure 1 is an illustration based on current industry consensus. Refinements to the stack can be made as new companies emerge. An inde-pendent list of available platforms can be collected from trade publications and mapped onto the stack.

Identify companies and their attributes: Platforms are important to technology-centric industries.5 Identifying platform companies for the ecosystem can be done by searching articles in industry publications. Use Internet search en-gines, news portals, socially curated news websites, or social media sources to locate these articles. Industry pub-lications complemented with discus-sions with practitioners identified 34

Figure 1. An Internet of Things (IoT) stack.

Application Layer for Sense Making for example, Analytics

System Integrators for example, Accenture, Cognizant

Infrastructure for example, Azure, Amazon Web Services, Telstra

Platforms for Device Connectivity for example, Thingworkx, Xively, Iotivity

Sensory Layer for example, ARM, Intel, Sigfox

Figure 2. The IoT ecosystem.

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player. In Figure 2, platform compa-nies are the red-colored circles and component providers are the gray-col-ored circles. Dependencies between platforms and components are shown as links. This visualization can be used to identify key players and determine business opportunities.4

Alliance Strength. Density of con-nections, number of partners, and network centrality all provide a sense of the resources available to any given firm that serves as an axis. In Figure 1, it’s easy to see, for example, that the Zigbee Alliance and Industrial In-ternet Consortium each represent an important nexus of activity. If one is a small player looking to join a winning alliance then choosing from among the bigger players could be wise. While, if one is a competing nexus, choosing compatibility with other midsize players could reshape the network landscape.

Vertical Integration. Companies that provide end-to-end solutions become vertically integrated and tightly controlled. For example, in its early days, the software indus-try was dominated by IBM, Digital Equipment, and International Com-puters. These end-to-end solutions providers fragmented into multiple companies and divided technical leadership. The IoT ecosystem (see Figure 3) reveals many clusters, sug-gesting they are either providing end-to-end solutions or leaving in-tegration to the user. IBM among those three early pioneers survives today, but Bluemix (integrating IBM products and services), Kaa (providing middleware services that work with any stack), and 365 Farmnet (specialized for agricultural services) might be relevant for indi-vidual specializations and doomed from a network perspective.

Preferential Attachment. With pro-liferation of platforms in the IoT eco-system, solutions providers must se-lect one platform over another. If they simultaneously commit to too many platforms they make significant re-source commitments. In the software industry, solutions providers attach themselves to one or two platforms based on incentives, momentum or technological superiority. Here solu-tions providers are unsure, they can

Figure 3. Vertical differentiation in the IoT ecosystem.

Figure 4. Preference of Android to IFTTT.

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track the ways users integrate services and devices, providing insights into how users derive value through a prod-uct’s use. Alphabet’s Nest has used this very effectively to implement the “Works With Nest” program. Because of this program, customers buying Nest will have the option to integrate it with the most common devices like LG washing machines or Amazon’s Echo. Nest’s position can be further so-lidified, if it became interoperable with highly connected platforms (as shown in Figure 3). This position gives it ac-cess to critical knowledge flows across the network.

ChallengesVisualizations can help with under-standing industry structure and emer-gence of key players. The dynamic na-ture of competition makes every new entrant and every move by an existing player relevant to the topology the ecosystem changes and the competi-tive position of companies. Compa-nies must constantly track nodes and dependencies in networks. Compu-tational tools for data gathering and AI techniques for text processing and understanding can be automated so executives can focus on understanding and exploring interactive visuals. Eco-system visualization continues to grow and mature as data scientists, graph theorists, and visualization research-ers create new techniques. In this way, ecosystem visualization is likely to be-come ubiquitous in high-velocity busi-ness environments.

References1. Basole, R.C. et al. Understanding business ecosystem

dynamics: A data-driven approach. ACM Trans. Management Information Systems (TMIS) 6, 2 (Feb. 2015), 6.

2. Bastian, M., Heymann, S., and Jacomy, M. Gephi: An open source software for exploring and manipulating networks. ICWSM 8, (2009), 361–362.

3. Iansiti, M. and Levien, R. The Keystone Advantage: What the New Dynamics of Business Ecosystems Mean for Strategy, Innovation, and Sustainability. Harvard Business Press, 2004.

4. Iyer, B. To predict the trajectory of the Internet of Things, look to the software industry. Harvard Business Review (Feb. 25, 2016).

5. Parker, G.G., Van Alstyne, M.W., and Choudary, S.P. Platform Revolution. Norton Publishing, New York, 2016.

Bala R. Iyer (biyer@babson.edu) is Professor and Chair TOIM Division, Babson College, MA. Twitter: @BalaIyer

Rahul C. Basole (basole@gatech.edu) is Associate Professor, School of Interactive Computing, and Director, Tennenbaum Institute, Georgia Institute of Technology, GA. Twitter: @basole

Copyright held by authors.

hedge their bets by selecting multiple platform. Oracle built huge market share by supporting multiple plat-forms like Windows and Linux. An-droid (see Figure 4) is preferential to IFTTT, ensuring that Android can inte-grate with most other products.

New Entrant and Network Effects. Major players in non-IoT industries (for example, Samsung, Apple, and Alpha-bet) still fight for dominance in the IoT ecosystem. To gain developers, these companies open up their IoT platforms and programming interfaces. Brand recognition, existing devices, plat-forms, and relationships with devel-opers might give them an advantage. As Alphabet expands into home auto-mation with Nest, many Google Play developers might move with it. De-veloper familiarity with Google’s API in one setting could also be used to develop products in other settings. A similar trend in the software industry enabled Microsoft’s strong position in operating systems to help it domi-nate the web browser market. In Fig-ure 3, Apple Homekit occupies a key position in the network. With Apple’s

decision to open its API, it instantly brings several hundreds of thousands of developers into the equation.

Focus on the Core. An emergent eco-system builds infrastructure first (see the core of the ecosystem in Figure 5). Personal computers needed an operat-ing system before the explosion of appli-cations could occur. The IoT ecosystem needs constant monitoring. Communi-cating data across networks is critical. Low-power solutions and connectivity are needed in the infrastructure (see the figure showing the core of the current IoT ecosystem) to help connect devices and ensure efficiency.

The Power of Interoperability Emer-gent ecosystems require integration of devices and services. They also require interoperability between competing platforms. These significant challeng-es benefit from learning about the early days in the software industry. Applica-tion Program Interfaces (APIs) allowed firms to interact and share information with other firms, and made it easy to achieve integration and interoperabil-ity across platforms and devices. They could be used for more: APIs could

Figure 5. Core of the IoT ecosystem.