Group decision support systems provide structure and aid teams in managing the ideas from all members. Some of the key tools incorporated in such a system are: electronic questionnaires, electronic brainstorming tools, idea organizers, tools for setting priorities, and policy formation.
> Research the tools currently available and select one for "each" category.
> In your own words, present a scenario in which it could be used and your case for why this tool is the appropriate choice.
Need 3 pages with peer-reviewed citations. No introduction or conclusion required.
646
11 C H A P T E R
I n this chapter, we present several topics related to group decision support and col- laboration. People work together, and groups (or teams) make many of the complex decisions in organizations. The increase in organizational decision-making complex-
ity drives the need for meetings and group work. Supporting group work in which team members may be in different locations and working at different times emphasizes the important aspects of communications, computer-mediated collaboration, and workplace methodologies. Group support is a critical aspect of decision support systems (DSS). Effective computer-supported group support systems have evolved to increase gains and decrease losses in task performance and underlying processes. New tools and methodol- ogy are used to support teamwork. These include collective intelligence, crowdsourcing, and different types of AI. Finally, human–machine and machine–machine collaboration
■■ Understand the basic concepts and processes of group work, communication, and collaboration
■■ Describe how computer systems facilitate team communication and collaboration in an enterprise
■■ Explain the concepts and importance of the time/ place framework
■■ Explain the underlying principles and capabilities of groupware, such as group support systems (GSS)
■■ Understand how the Web enables collaborative computing and group support of virtual meetings
■■ Describe collective intelligence and its role in decision making
■■ Define crowdsourcing and explain how it supports decision making and problem solving
■■ Describe the role of AI in supporting collaboration, group work, and decision making
■■ Describe human–machine collaboration ■■ Explain how teams of robots work
LEARNING OBJECTIVES
Group Decision Making, Collaborative Systems, and AI Support
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are increasing the power of collaboration and problem solving. All these are presented in the following sections:
11.1 Opening Vignette: Hendrick Motorsport Excels with Collaboration Teams 647
11.2 Making Decisions in Groups: Characteristics, Processes, Benefits, and Dysfunctions 649
11.3 Supporting Group Work and Team Collaboration with Computerized Systems 652
11.4 Electronic Support to Group Communication and Collaboration 655
11.5 Direct Computerized Support for Group Decision Making 659
11.6 Collective Intelligence and Collaborative Intelligence 665
11.7 Crowdsourcing as a Method for Decision Support 669
11.8 Artificial Intelligence and Swarm AI Support of Team Collaboration and Group Decision Making 672
11.9 Human–Machine Collaboration and Teams of Robots 676
11.1 OPENING VIGNETTE: Hendrick Motorsports Excels with Collaborative Teams
Hendrick Motorsports (HMS) is a leading car racing company (with more than 500 employees) that competes in the Monster Energy NASCAR Cup Series. HMS’s major objective is to win as many races as possible each year. The company enters four race cars and their teams. HMS also builds its race cars. This includes building or rebuilding 550 car engines every year. In this kind of business, teamwork is critical because many different people with different skills and knowledge and several professional teams contribute to the success of the company.
THE OPERATIONS
HMS is engaged in car races all over the United States during the racing season (38 weeks a year). The company moves to a different racetrack every week. During the off-season time (14 weeks), the company analyzes the data obtained, and lessons learned during the latest racing seasons, and prepares for the following season. The company’s headquarters contains 19 buildings scattered over 100 acres.
THE PROBLEMS DURING THE RACING SEASON
The company needs to make quick decisions during races—some in real time, sometimes in a split second. Different team members need to participate, and they are in different locations. Communication and collaboration are critical.
Car racing is based on teamwork, drivers, engineers, planners, mechanics, and others who participate. Members must communicate and collaborate to make decisions.
The environment is too noisy to talk during a race. However, team members need to share data, graphs, and images, and chat quickly. Several decisions need to be made in real time that will help win races (e.g., how much fuel to add in the next few seconds to a car in the middle of the race). Team members must communicate and share data, including visual. It takes about 45–50 seconds for a car to complete a 2.5-mile lap at Daytona 500. During the race, top engineers need to communicate constantly with the fuelers. Last- minute data are common during the racing session.
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Any knowledge acquired in each lap can be used to improve the next one. In races, fueling decisions are critical. There are many other decisions to be made during the racing season. For example, after each race, the company needs to move a large crew with equipment and supplies from one location to the next (38 different venues). Moves need to be fast, efficient, and economical. Again, teamwork, as well as coordination, is needed.
OFF-SEASON PROBLEMS
There are 14 weeks to prepare for the next season. In addition, there is a considerable amount of data to analyze, simulate, discuss, and manipulate. For this, people need not only communication and collaboration tools but also analytics of different types.
THE SOLUTION
HMS decided to use Microsoft Teams, which is a chat-based platform, for team workspace in Microsoft Office 365. This platform is used as a communication hub for team members at the race tracks and at any other location in the organization.
Microsoft Teams stores data in different formats in its Teams workspace. Therefore, car crews, engineers, and mechanics can make split-second decisions that may help win races. This also enables computational analysis in a central place.
Microsoft Teams includes several subprograms and is easily connected to other soft- ware in Office 365. Office 365 provides several other tools that increase collaboration (e.g., SharePoint). For example, in the HSM solution, there is a working link to Excel as well as to SharePoint. Also, One Note of Teams is used to share meeting notes. Before Teams, the company used Slack (Section 11.4), but Slack did not provide enough security and functions.
Members need to share and discuss the massive amount of data accumulated during the racing season. Note that several employees have multiple skills and tasks. The solution included the creation of a collaboration hub for concurrent projects. Note that each different project may require different talents and data, depending on the project’s type. Also, the solution involves other information technology (IT) tools. For example, HMS uses Power BI dashboard to com- municate data visually. Some data can be processed as Excel-based spreadsheets.
Microsoft Teams is also available as a mobile app. Each team’s data file is available on the track at home and even under a car. So, the software package is able to respond to important situations right away.
The Results
The major results were improved productivity, smoother communication, easier collabora- tion, and reduction of the need for the time consumed in face-to-face meetings. People can chat online, seeing their partners without leaving their physical workplace. The company admits that without Teams, it would not have been able to accomplish its success. Today, Teams has everything the company needs at its fingertips.
u QUESTIONS FOR THE OPENING VIGNETTE
1. What were the major drivers for the use of Microsoft’s Teams?
2. List some discussions held during the racing season, and how they were supported by the technology.
3. List decisions held during the off-season, and how they were supported by the technology.
4. Discuss why Microsoft Teams was selected, and explain how it supports teamwork group decision making.
5. Trace communication and collaboration within and between groups.
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6. Specify the function of Microsoft Teams workspace.
7. Watch the video at youtube.com/watch?time_continue=108&v=xnFdM9IOaTE and summarize its content.
WHAT WE CAN LEARN FROM THIS VIGNETTE
The first lesson is that many tasks today must be done by collaborating teams in order to succeed. Second, time is critical; therefore, companies must use technology to speed opera- tions and facilitate communication and collaboration in teamwork. Third, it is possible to use existing software for support, but it is better to use a major vendor that has additional products that can supplement the collaboration/communication software. Fourth, chat- ting can expedite communication, and visual technology support can be useful. Fifth, team members belong to diverse units and have diverse skills. The software brings them together. Team members should have clear goals and understand how to achieve them. Finally, collaboration can be both within and between groups.
Sources: Compiled from Ruiz-Hopper (2016) and Microsoft (2017).
11.2 MAKING DECISIONS IN GROUPS: CHARACTERISTICS, PROCESS, BENEFITS, AND DYSFUNCTIONS
Managers and other knowledge workers continuously make decisions, design products, develop policies and strategies, create software systems, and so on. Frequently they do it in groups. When people work in groups (i.e., teams), they perform group work or teamwork. Group work refers to work done by two or more people together. One aspect of group work is group decision making.
Group decision making refers to a situation in which people make decisions together. Let’s first look at the characteristics of group work.
Characteristics of Group Work
The following are some of the functions and characteristics of group work:
• Group members may be located in different places. • Group members may work at different times. • Group members may work for the same organization or different organizations. • A group can be permanent or temporary. • A group can be at one managerial level or span several levels. • A group can create synergy (leading to process and task gains) or result in conflict. • A group can generate productivity gains and/or losses. • A group’s task may have to be accomplished very quickly. • It may be impossible or too expensive for all team members to meet in one place
at the same time, especially when the meeting is called for emergency purposes. • Some of the groups’ needed data, information, or knowledge may be located in
several sources, some of which may be external to the organization. • The expertise of a group’s team members may be needed. • Groups perform many tasks; however, groups of managers and analysts frequently
concentrate on decision making or problem solving. • The decisions made by a group are easier to implement if supported by all (or at
least most) members. • Group work has many benefits and, unfortunately, some possible dysfunctions. • Group behaviors are influenced by several factors and may affect group decisions.
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Types of Decisions Made by Groups
Groups are usually involved in two major types of decision making:
1. Making a decision together. 2. Supporting activities or tasks related to the decision-making process. For example,
the group may select criteria for evaluating alternative solutions, prioritizing possible ones, and helping design strategy to implement them.
Group Decision-Making Process
The process of group decision making is similar to that of the general decision-making process described in Chapter 1 but it has more steps. Steps of the group decision-making process are illustrated in Figure 11.1.
Step 1. Prepare for meetings regarding the agenda, time, place, participants, and schedule. Step 2. Determine the topic of the meeting (e.g., problem definition). Step 3. Select participants for the meeting. Step 4. Select criteria for evaluating the alternatives and the selected solution. Step 5. Generate alternative ideas (brainstorm). Step 6. Organize the ideas generated into similar groups. Step 7. Evaluate the ideas, discuss, and brainstorm.
FIGURE 11.1 The Process of Group Decision Making.
Preparation, schedule, agenda
Select participants
Define the problem
Select evaluation criteria
Idea generation, alternative solution
Organize submitted ideas
Idea evaluation, discussion
Select or find idea or shortlist of ideas
Make a choice, recommendations
Plan implementation
Implement solutions
1
2
3
4
5
6
7
8
9
10
11
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Step 8. Select a short list (finalists). Step 9. Select a recommended solution. Step 10. Plan implementation of the solution. Step 11. Implement the solution.
The process is shown as sequential, but as shown in Figure 11.1, some loops are possible. Also, if no solution is found, the process may start again.
GROUP DECISION FACTS When a group is going through the steps shown in Figure 11.1, the following is usually true:
• The decisions made need to be implemented. • Group members are typically of equal or nearly equal status. • The outcome of a meeting depends partly on the knowledge, opinions, and judg-
ments of its participants and the support they give to the outcome. • The outcome of a meeting depends on the composition of the group and on the
decision-making process it uses. • Group members settle differences of opinions either by the ranking person present
or through negotiations or arbitration. • The members of a group can be in one place, meeting face-to-face, or they can be
a virtual team, in which case they are in different places meeting electronically. They can also meet at different times.
Benefits and Limitations of Group Work
Some people endure meetings (the most common form of group work) as a necessity; oth- ers find meetings to be a waste of time. Many things can go wrong in a meeting. Participants may not clearly understand its purpose, may lack focus, or may have hidden agendas. Many participants may be afraid to speak up, or a few may dominate the discussions. Misunder- standings occur because of different interpretations of language, gestures, or expression. Technology Insight 11.1 provides a list of factors that can hinder the effectiveness of a manually managed meeting. Besides being challenging, teamwork is also expensive. A meeting of several top managers or executives can cost thousands of dollars.
Group work may have potential benefits (process gains) or drawbacks (process losses). Process gains are the benefits of working in groups. The unfortunate dysfunc- tions that may occur when people work in groups are called process losses. Examples of each are listed in Technology Insight 11.1.
TECHNOLOGY INSIGHT 11.1 Benefits and Dysfunctions of Working in Groups
The following are the possible major benefits and dysfunctions of group works.
Benefits of Working in Groups (Process Gains) Dysfunctions of Face-to-Face Group Process
(Process Losses)
• It provides learning. Groups are better than individuals at understanding problems. They can teach each other.
• Social pressures of conformity may result in groupthink (i.e., people begin to think alike and not tolerate new ideas; they yield to conformance pressure).
• People readily take ownership of problems and their solutions.
• It is a time-consuming, slow process. • Some relevant information could be missing.
• Group members have their egos embedded in the final decision, so they are committed it.
• A meeting can lack coordination, have a poor agenda, or be poorly planned.
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Benefits of Working in Groups (Process Gains) Dysfunctions of Face-to-Face Group Process
(Process Losses)
• Groups are better than individuals at catching errors.
• A meeting may be dominated by time, topic, opinion of one or a few individuals, or fear of contributing because of the possibility of conflicts.
• A group has more information and knowledge than any one member does. Members can combine their knowledge to create new knowledge. More and more creative alternatives for problem solving can be generated, and better solutions can be derived (e.g., through brainstorming).
• Some group members can tend to influence the agenda while some try to rely on others to do most of the work (free riding). The group may ignore good solutions, have poorly defined goals, or be composed of the wrong participants.
• A group may produce synergy during problem solving, therefore the effectiveness and/or quality of group work can be greater than the sum of what individual members produce.
• Some members may be afraid to speak up. • The group may be unable to reach consensus. • The group may lack focus.
• Working in a group may stimulate the creativity of the participants and the process.
• There can be a tendency to produce poor- quality compromises.
• Working together could allow a group to have better and more precise communication.
• There is often nonproductive time (e.g., socializing, preparing, waiting for latecomers).
• Risk propensity is balanced. Groups moderate high-risk takers and encourage conservatives.
• There can be a tendency to repeat what has already been said (because of failure to remember or process).
• Meeting costs can be high (e.g., travel, participation time spent).
• There can be incomplete or inappropriate use of information.
• There can be too much information (i.e., information overload).
• There can be incomplete or incorrect task analysis.
• There can be inappropriate or incomplete representation in the group.
• There can be attention or concentration blockage.
u SECTION 11.2 REVIEW QUESTIONS
1. Define group work.
2. List five characteristics of group work.
3. Describe the steps of group decision making.
4. List the major activities that occur in group work.
5. List and discuss five benefits of group work.
6. List and discuss five dysfunctions of group-made decisions.
11.3 SUPPORTING GROUP WORK AND TEAM COLLABORATION WITH COMPUTERIZED SYSTEMS
When people work in teams, especially when the members are in different locations and may work at different times, they need to communicate, collaborate, and access a diverse set of information sources in multiple formats. This makes meetings, especially virtual ones, complex with an increased chance for process losses. Therefore, it is important to follow certain processes and procedures for conducting meetings.
Group work may require different levels of coordination. Sometimes a group oper- ates at the individual work level with members making individual efforts that require
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no coordination. As with a team of sprinters representing a country participating in a 100-meter dash, group productivity is simply the best of the individual results. At other times, group members may interact in coordination. At this level, as with a team in a relay race, the work requires careful coordination between otherwise independent individual efforts. Sometimes a team may operate at the concerted work level. As in a rowing race, teams working at this level must make a continuous concerted effort to be successful. Different mechanisms support group work at different levels of coordination.
Most organizations, small and large, use some computer-based communication and collaboration methods and tools to support people working in teams or groups. From e-mails to mobile phones and Short Message Service (SMS), as well as conferencing tech- nologies, such tools are an indispensable part of today’s work life. We next highlight some related technologies and applications.
Overview of Group Support Systems (GSS)
For groups to collaborate effectively, appropriate communication methods and technolo- gies are needed. We refer to these technologies as group support systems (GSS). The Internet and its derivatives (i.e., intranets, Internet of Things [IoT], and extranets) are the infrastructures on which much communication and collaboration occurs. The Web supports intra- and inter-organizational collaborative decision making.
Computers have been used for several decades to facilitate group work and decision making. Lately, collaborative tools have received more attention due to their increased capabilities and ability to save time and money (e.g., on travel cost) and to expedite deci- sion making. Computerized tools can be classified according to time and place categories.
Time/Place Framework
The tools used to support collaboration, groups, and the effectiveness of collaborative com- puting technology depend on the location of the group members and on the time that shared information is sent and received. DeSanctis and Gallupe (1987) proposed a framework for classifying IT communication support technologies. In this framework, communication is divided into four cells, which are shown with representative computerized support technolo- gies in Figure 11.2. The four cells are organized along two dimensions—time and place.
When information is sent and received almost simultaneously, the communication is in synchronous (real-time) mode. Telephones, instant messaging (IM), and face-to-face meet- ings are examples of synchronous communication. Asynchronous communication occurs when the receiver gets (or views) the information, such as an e-mail, at a different time than it was sent. The senders and the receivers can be in the same place or in different places.
As shown in Figure 11.2, time and place combinations can be viewed as a four-cell matrix, or framework. The four cells of the framework are as follows:
• Same time/same place. Participants meet face-to-face, as in a traditional meeting, or decisions are made in a specially equipped decision room. This is still an impor- tant way to meet even when Web-based support is used because it is sometimes critical for participants to leave their regular workplace to eliminate distractions.
• Same time/different place. Participants are in different places, but they com- municate at the same time (e.g., with videoconferencing or IM).
• Different time/same place. People work in shifts. One shift leaves information for the next shift.
• Different time/(any place) different place (any place). Participants are in different places, and they send and receive information at different times. This occurs when team members are traveling, have conflicting schedules, or work in different time zones.
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Groups and group work in organizations are proliferating. Consequently, groupware continues to evolve to support effective group work, mostly for communication and col- laboration (Section 11.4).
Group Collaboration for Decision Support
In addition to making decisions, groups also support decision-making subprocesses such as brainstorming. Collaboration technology is known to be the driving force for productivity increase and boosting people and organizational performance. Groups collaborate to make decisions in several ways. For example, groups provide assistance for the steps in Figure 11.1. Groups can help to identify problems, to assist in choosing criteria for selecting solutions, generating solutions (e.g., brainstorming), evaluating alternatives, and assisting in the selection of the best solution and implementing it. The group can be involved in one step or in several steps. In addition, it can collect the necessary data.
Many technologies can be used for collaboration; several of them are computerized and are described in several sections in this chapter.
Studies indicate that adopting collaboration technologies increases productiv- ity: for example, visual collaborative solutions increase employees’ satisfaction and productivity.
COMPUTERIZED TOOLS AND PLATFORMS We divide the computerized support into two parts. In Section 11.4, we present the major support of generic activities in com- munication and collaboration. Note that hundreds, maybe thousands, of commercial products are available to support communication and collaboration. We cover only a sample here.
FIGURE 11.2 The Time/Place Framework.
Same Time
• Instant Messaging • Chatting, decision room • Web-based GSS • Multimedia presentation system • Whiteboard • Document sharing • Workspace
• GSS in a decision room • Web-based GSS • Workflow management system • Document sharing • E-mail, V-mail • Videoconferencing playback
• Web-based GSS • Virtual whiteboard • Document sharing • Videoconferencing • Audio-conferencing • Computer conferencing • E-mail, V-mail • Virtual workspace
• Web-based GSS • Virtual whiteboard • Document sharing • E-mail, V-mail • Workflow management system • Computer conferencing with memory • videoconferencing playback • Voice memo
Different Time
Same Place
Different Place
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Section 11.5 covers direct support of decision making, both to the entire process and to the major steps in the process. Note that some products, such as Microsoft Teams, which is cited in the opening vignette, support both generic activities and those in the decision-making process.
u SECTION 11.3 REVIEW QUESTIONS
1. Why do companies use computers to support group work?
2. What is GSS?
3. Describe the components of the time/place framework.
4. Describe the importance of collaboration for decision making.
11.4 ELECTRONIC SUPPORT FOR GROUP COMMUNICATION AND COLLABORATION
A large number of tools and methods are available to facilitate group work, e-collaboration, and communication. The following sections present only some tools that support the process. Our attention here is on indirect support to decision making. In Section 11.5, we cover direct support.
Groupware for Group Collaboration
Many computerized tools have been developed to provide group support. These tools are called groupware because their primary objective is to support group work indirectly as described in this section. Some e-mail programs, chat rooms, IM, and teleconferences provide indirect support.
Groupware provides a mechanism for team members to share opinions, data, infor- mation, knowledge, and other resources. Different computing technologies support group work in different ways depending on the task and size of the group, the security required, and other factors.
CATEGORIES OF GROUPWARE PRODUCTS AND FEATURES Many groupware products to enhance the collaboration of a small and large number of people are available on the Inter- net or intranets. A prime example is Microsoft’s Teams (opening vignette). The features of groupware products that support commutation, collaboration, and coordination are listed in Table 11.1. What follows are brief definitions of some of those features.
Synchronous versus Asynchronous Products
The products and features described in Table 11.1 may be synchronous or asynchronous. Web conferencing and IM, as well as voice-over IP (VoIP), are associated with the syn- chronous mode. Methods associated with asynchronous modes include e-mail and online workspaces where participants can collaborate while working at different times. Google Drive (drive.google.com) and Microsoft SharePoint (http://office.microsoft.com/en-us/ SharePoint/collaboration-software-SharePoint-FX103479517.aspx) allow users to set up online workspaces for storing, sharing, and working collaboratively on different types of documents. Similar products are Google Cloud Platform and Citrix Workspace Cloud.
Companies such as Dropbox.com provide an easy way to share documents. Similar systems, such as photo sharing (e.g., Instagram, WhatsApp, Facebook), are evolving for consumer home use.
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TABLE 11.1 Groupware Products and Features
General (Can Be Either Synchronous or Asynchronous)
• Built-in e-mail, messaging system • Browser interface • Joint Web page creation • Active hyperlink sharing • File sharing (graphics, video, audio, or other) • Built-in search functions (by topic or keyword) • Workflow tools • Corporate portals for communication, collaboration, and search • Shared screens • Electronic decision rooms • Peer-to-peer networks
Synchronous (Same Time)
• IM • Videoconferences, multimedia conferences • Audioconferences • Shared whiteboard, smart whiteboard • Instant videos • Brainstorming • Polling (voting) and other decision support (activities such as consensus building, scheduling)
• Chats with people • Chats with bots
Asynchronous (Different Times)
• Virtual workspaces • Tweets • Ability to receive/send e-mail, SMS • Ability to receive notification alerts via e-mail or SMS • Ability to collapse/expand discussion threads • Message sorting (by date, author, or read/unread) • Auto responders • Chat session logs • Electronic bulletin boards, discussion groups • Blogs and wikis
• Collaborative planning and/or design tools
Groupware products are either stand-alone, supporting one task (such as videoconfer- encing), or integrated, including several tools. In general, groupware technology products are fairly inexpensive and can easily be incorporated into existing information systems.
Virtual Meeting Systems
The advancement of Web-based systems opens the door for improved electronically sup- ported virtual meetings with the virtual team members in different locations, even in different countries. Online meetings and presentation tools are provided by tools such as webex, GoToMeeting.com, Skype.com, and many others. These systems feature Web
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seminars (popularly called Webinars), screen sharing, audioconferencing, videoconferenc- ing, polling, question–answer sessions, and so on. Microsoft Office 365 includes a built-in virtual meeting capability. Even smartphones now have sufficient interaction capabilities to allow live meetings through applications such as FaceTime.
COLLABORATIVE WORKFLOW Collaborative workflow refers to software products that address project-oriented and collaborative processes. They are administered centrally yet are capable of being accessed and used by workers from different departments and from different physical locations. The goal of collaborative workflow tools is to empower knowl- edge workers. The focus of an enterprise solution for collaborative workflow is on allowing workers to communicate, negotiate, and collaborate within an integrated environment. Some leading vendors of collaborative workflow applications are FileNet and Action Tech- nologies. Collaborative workflow is related to but different than collaborative workspace.
DIGITAL COLLABORATIVE WORKSPACE: PHYSICAL AND VIRTUAL A collaborative work- space is where people can work together from any location at the same or at a different time. Originally, it was a physical conference room that teams used for conducting meet- ings. It was expanded to be a shared workspace, also known as “coworking space.” Some of these are in companies; others are offered for rent. Different computerized technologies are available to support group work in a physical structure. For 12 benefits of collaborative workspace, see Pena (2017).
A virtual collaboration workspace is an environment equipped with digital support by which group members who are in different locations can share information and col- laborate. A simple example is Google Drive, which enables sharing spreadsheets.
Collaborative workspace enables tech-savvy employees to access systems and tools from any device they need. People can work together in a secure way from anywhere. The digital workspace increases team productivity and innovation. It empowers employees and unlocks innovation. It allows workers to reach other people for collaborative work. For details and other collaboration technologies, see de Lares Norris (2018).
Example
PricewaterhouseCoopers (PwC) built an ideation war room in its Paris office as a large, immersive collaboration facility to support customer meetings.
MAJOR VENDORS OF VIRTUAL WORKSPACE Products by five major vendors follow:
• Google Cloud Platform is deployed on the “cloud,” so it is offered as a platform-as-a- service (PaaS). Google is also known for its Flexible Workspace product.
• Citrix Workspace Cloud is also deployed on the “cloud.” Citrix is known for its GoToMeeting collaboration tool. Citrix Workspace Cloud users can manage secure digital workplaces on Google Cloud.
• Microsoft Workspace is part of Office 365. • Cisco’s Webex, a popular collaboration package including Meeting. • Slack workspace is a very popular workspace.
ESSENTIALS OF SLACK Slack workspace is a digital space on which teammates share, communicate, and collaborate on work. It can be in one organization, or large organiza- tions may have multiple interconnected Slack spaces.
Each workspace includes several topical channels. These can be organized as pub- lic, private, or shared. The remaining components of Slack are messages, searches, and notifications. There are four groups of people involved with Slack: workspace owners,
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workspace administrators, members, and guests. For a Slack Guide, see get.slack.help/ hc/en-us/articles/115004071768-What-is-Slack-.
Slack has many key features and can deliver secure virtual apps to almost any device.
Collaborative Networks and Hubs
Traditionally, collaboration has taken place among supply chain members, frequently those that were close to each other (e.g., a manufacturer and its distributor or a distributor and a retailer). Even if more partners were involved, the focus was on the optimization of information and product flow between existing nodes in the traditional supply chain. Advanced methods, such as collaborative planning, forecasting, and replenishment (CPFR), do not change this basic structure.
Traditional collaboration results in a vertically integrated supply chain. However, Web technologies can fundamentally change the shape of the supply chain, the number of play- ers in it, and their individual roles. In a collaborative network, partners at any point in the network can interact with each other, bypassing what are traditional partners. Interaction may occur among several manufacturers or distributors as well as with new players, such as software agents that act as aggregators.
Collaborative Hubs
The purpose of a collaborative hub is to be a center point for group collaboration. Collaborative hub platforms need to enable participants’ interactions to unfold in
various forms online.
Example: Surface Hub for Business by Microsoft
This product connects individuals wherever they are and whenever they want to use a digital whiteboard and integrating software and apps. It helps to create a collaboration workplace where multiple devices are connected wirelessly to create a powerful work environment.
Social Collaboration
Social collaboration refers to collaboration conducted within and between socially ori- ented groups. It is a process of group interactions and information/knowledge sharing while attempting to attain common goals. Social collaboration is usually done on social media sites, and it is enabled by the Internet, IoT, and diversified social collaboration software. Social collaboration groups and schemes can take many different shapes. For images, conduct a Google search for “images of social collaboration.”
COLLABORATION IN SOCIAL NETWORKS Business-related collaboration is most evidenced on Facebook and LinkedIn. However, Instagram, Pinterest, and Twitter support collabora- tion as well.
• Facebook. Facebook’s Workspace facebook.com/workspace is used by hundreds of thousands of companies utilizing its features, such as “groups,” to support team members. For example, 80 percent of Starbucks store managers use this software.
• LinkedIn. LinkedIn provides several collaboration tools to its members. For exam- ple, LinkedIn Lookup provides several tools. Also, LinkedIn is a Microsoft company and it provides some integrated tools. The creation of subgroups of interest is a useful facilitator.
SOCIAL COLLABORATION SOFTWARE FOR TEAMS In addition to the generic collabora- tion software that can be used by two people and by teams, there are software platforms specifically for forming teams and supporting their activities. A few popular examples
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according to collaboration-software.financesonline.com/c/social-collaboration- software/ are Wrike, Ryver, Azendoo, Zimbra social platform, Samepage, Zoho, Asana, Jive, Chatter, and Social Tables. For viewing the best social collaboration software by category, see technologyadvice.com/social-collaboration-software/.
Sample of Popular Collaboration Software
As noted earlier, there are hundreds or maybe thousands of communication and collabora- tion software products. Furthermore, their capabilities are ever changing. Given that our major interest is decision-making support, we provide only a small sample of these tools. We use the classification and example of Time Doctor, using the 2018 list (see Digneo, 2018).
• Communication tools: Yammer (social collaboration), Slack, Skype, Google Hangouts, GoToMeeting
• Design tools: InVision, Mural, Red Pen, Logo Maker • Documentation tools: Office Online, Google Docs, Zoho • File-sharing tools: Google Drive, Dropbox, Box • Project management tools: Asana, Podio, Trello, WorkflowMax, Kanban Tool, • Software tools: GitHub, Usersnap,Workflow tools: Integrity, BP Logix
OTHER TOOLS THAT SUPPORT COLLABORATION AND/OR COMMUNICATION
Notejoy (makes collaborative notes for team). Kahootz (brings stakeholders together to form communities of interest). Nowbridge (offers team connectivity, ability to see participants). Walkabout Workplace (is a 3D virtual office for remote teams). RealtimeBoard (is a enterprise visual collaboration). Quora (is a popular place for posting questions to the crowd). Pinterest (provides an e-commerce workspace that allows collection of text and images on selected topics). IBM connection closed (offers a comprehensive communication and collaboration tool set). Skedda (schedules space for coworking) Zinc (is a social collaboration tool) Scribblar (is an online collaboration room for virtual brainstorming) Collokia (is a machine learning platform for workflow) For additional tools, see Steward (2017).
u SECTION 11.4 REVIEW QUESTIONS
1. Define groupware.
2. List the major groupware tools and divide them into synchronous and asynchronous types.
3. Identify specific tools for Web conferencing and their capabilities.
4. Describe collaborative workflow.
5. What is collaborative workspace? What are its benefits?
6. Describe social collaboration.
11.5 DIRECT COMPUTERIZED SUPPORT FOR GROUP DECISION MAKING
Decisions are made frequently at meetings, some of which are called in order to make a one-time specific decision. For example, directors are elected at shareholder meetings, orga- nizations allocate budgets in meetings, cities decide which candidates to hire for their top
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positions, and the U.S. federal government meets periodically to set the short-term interest rate. Some of these decisions are complex; others can be controversial, as in resource alloca- tion by a city government. Process dysfunctions can be significantly large in such situations; therefore, computerized support has often been suggested to mitigate these controversies. These computer-based support systems have appeared in the literature under different names, including group decision support systems (GDSS), group support systems (GSS), computer- supported collaborative work (CSCW), and electronic meeting systems (EMS). These systems are the subject of this section. In addition to supporting entire processes, there are tools that support one or several activities in the group decision-making process (e.g., brainstorming).
Group Decision Support Systems (GDSS)
During the 1980s, researchers realized that computerized support to managerial decision making needed to be expanded to groups, because major organizational decisions are made by groups, such as executive committees and special task forces. The result was the creation of the group decision support systems methodology.
A group decision support system (GDSS) is an interactive computer-based sys- tem that facilitates the solution of semistructured or unstructured problems by a group of decision makers. The goals of GDSS are to improve the productivity of decision-making meetings by speeding up the decision-making process and/or to increase the quality of the resulting decisions.
MAJOR CHARACTERISTICS AND CAPABILITIES OF A GDSS GDSS characteristics follow:
• It supports the process of group decision makers mainly by providing automation of subprocesses (e.g., brainstorming) and using information technology tools.
• It is a specially designed information system, not merely a configuration of already existing system components. It can be designed to address one type of problem or make a variety of group-level organizational decisions.
• It encourages generation of ideas, resolution of conflicts, and freedom of expres- sion. It contains built-in mechanisms that discourage development of negative group behaviors, such as destructive conflict, miscommunication, and groupthink.
The first generation of GDSS was designed to support face-to-face meetings in a decision room. Today, support is provided mostly over the Web to virtual teams. A group can meet at the same time or at different times. GDSS is especially useful when controver- sial decisions have to be made (e.g., resource allocation, determining which individuals to lay off). GDSS applications require a facilitator for one physical place or a coordinator or leader for online virtual meetings.
GDSS can improve the decision-making process in various ways. For one, GDSS gen- erally provides structure to the meeting planning process, which keeps a group meeting on track, although some applications permit the group to use unstructured techniques and methods for idea generation. In addition, GDSS offers rapid and easy access to external and stored information needed for decision making. It also supports parallel processing of information and idea generation by participants and allows asynchronous computer discus- sion. GDSS makes possible larger group meetings that would otherwise be unmanageable; having a larger group means that more complete information, knowledge, and skills can be represented in the meeting. Finally, voting can be anonymous with instant results, and all information that passes through the system can be recorded for future analysis (producing organizational memory).
Over time, it became clear that supporting teams needed to be broader than GDSS has beed supported in a decision room. Furthermore, it became clear that what was really
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needed was support for virtual teams, both in different place/same time and different place/different time situations. Also, it became clear that teams needed indirect support in most decision-making cases (e.g., help in searching for information or in collaboration) rather than direct support for the decision-making process. Although GDSS expanded to virtual team support, it was unable to meet all the other needs. In addition, the traditional GDSS was designed to deal with contradictory decisions when conflicts were likely to arise. Thus, a new generation of GDSS that supports collaboration work was needed. As we will see later, products such as Stormboard provide those needs.
Characteristics of GDSS
There are two options for deploying GDSS technology: (1) in a special-purpose decision room and (2) as Internet-based groupware with client programs running wherever the group members are.
DECISION ROOMS The earliest GDSS was installed in expensive, customized, special- purpose facilities called decision rooms (or electronic meeting rooms) that had PCs and a large public screen at the front of each room. The original idea was that only executives and high-level managers would use the expensive facility. The software in an electronic meeting room usually ran over a local area network (LAN), and these rooms were fairly plush in their furnishings. Electronic meeting rooms were structured in different shapes and sizes. A common design was a room equipped with 12 to 30 networked PCs, usually recessed into the desktop (for better participant viewing). A server PC was attached to a large screen projection system and connected to the network to display the work at indi- vidual workstations and aggregated information from the facilitator’s workstation. Breakout rooms equipped with PCs connected to the server, in which small subgroups could consult, were sometimes located adjacent to the decision room. The output from the subgroups was able to be displayed on the large public screen. A few companies offered such rooms for a daily rent. Only a few upgraded rooms are still available today, usually for high rent.
INTERNET-BASED GROUPWARE Since the late 1990s, the most common approach to GSS and GDSS delivery has been to use an Internet-based groupware that allows group mem- bers to work from any location at any time (e.g., WebEx, GoToMeeting, Adobe Connect, IBM Connections, Microsoft Teams). This groupware often includes audio conferencing and videoconferencing. The availability of relatively inexpensive groupware, as described in Section 11.4, combined with the power and low cost of computers and the availability of mobile devices, makes this type of system very attractive.
Supporting the Entire Decision-Making Process
The process that was illustrated in Figure 11.1 can be supported by a variety of software products. In this section, we provide an example of one product, Stormboard, that sup- ports several aspects of that process.
Example: Stormboard
Stormboard stormboard.com provides support for different brainstorming and group decision-making configurations. The following is the product’s sequence of activities:
1. Define the problem and the users’ objectives (what they are hoping to achieve). 2. Brainstorm ideas (to be discussed later). 3. Organize the ideas in groups of similar flavor, look for patterns, and select only
viable ideas.
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4. Collaborate, refine concepts, and evaluate (using criteria) the meeting’s objectives. 5. The software enables users to prioritize proposed ideas by focusing on the selec-
tion criteria. It lets all participants express their thinking and directs the team to be cohesive.
6. It presents a short list of superior ideas. 7. The software suggests the best idea and recommends implementation. 8. It plans the project implementation. 9. It manages the project.
10. It periodically reviews progress.
For a video, see youtube.com/watch?v=0buRzu4rhJs.
COMPREHENSIVE GROUPWARE TOOLS INCLUDING THINKTHANK Although many capabili- ties that enable group decision support are embedded in common software tools for office productivity such as Microsoft Office 365, it is instructive to learn about specific software that illustrates some of groupware’s unique capabilities. MeetingRoom was one of the first comprehensive, same time/same place electronic meeting packages. Its follow-up product, GroupSystems OnLine, offered similar capabilities, and it ran in asynchronous mode (any- time/anyplace) over the Web (MeetingRoom ran only over a LAN). GroupSystems’ latest product is ThinkTank, a suite of tools that facilitate the various group decision-making activities. For example, it shortens cycle time for brainstorming. ThinkTank improves the collaboration of face-to-face or virtual teams through customizable processes toward the groups’ goals faster and more effectively than in previous product generations. ThinkTank offers the following:
• It can provide efficient participation, workflow, prioritization, and decision analysis. • Its anonymous brainstorming for ideas and comment generation is an ideal way to
capture the participants’ creativity and experience. • The product’s enhanced Web 2.0 user interface ensures that participants do not
need special training to join, so they can focus 100 percent on solving problems and making decisions.
• With ThinkTank, all of the knowledge shared by participants is captured and saved in documents and spreadsheets, automatically converted to the meeting minutes, and made available to all participants at the end of the session.
Examples: ThinkTank Use (thinktank.net/case-study)
The following are two examples of ThinkTank’s use.
• It enables transformational collaboration between supply chain partners. Their meet- ing was supported by collective intelligence tools and procedures. Partners agreed on how to cut costs, speed processes, and improve efficiencies. In the past, there had been no progress on these issues.
• The University of Nebraska and the American College of Cardiology collaborated using ThinkTank tools and procedures to rethink how electronic health records could be reorganized to help medical consultants save time. Patients’ appointment times were shortened by 5 to 8 minutes. Other improvements also were achieved. Both patient care and large monetary savings were achieved.
OTHER DECISION-MAKING SUPPORT The following is a list of other types of support pro- vided by intelligent systems:
• Using knowledge systems and a product called Expert Choice Software for dealing with multiple-criteria group decision making.
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• A mediating group decision-making method for infrastructure asset management was proposed by Yoon et al. (2017).
• For a group decision-making support system in logistics and supply chain manage- ment, see Yazdani et al. (2017).
Brainstorming for Idea Generation and Problem Solving
A major activity in group decision making is idea generation. Brainstorming is a process for generating creative ideas. It involves freewheeling group discussions and spontaneous contribution of ideas for solving problems and making strategy and resource allocation. Contributors’ ideas are discussed by the members. An attempt is made to generate as many ideas as possible, no matter how bizarre they look. Generated ideas are discussed and evaluated by the group. There is evidence that groups not only generate more ideas but also better ones (McMahon et al., 2016). Manually managed brainstorming has some of the limitations of group work described in Section 11.2. Therefore, computer support is frequently recommended.
COMPUTER-SUPPORTED BRAINSTORMING Computer programs can support the various brainstorming activities. The support is usually for online brainstorming, synchronously or asynchronously. Hopefully, electronic brainstorming eliminates many of the process dysfunctions cited in Section 11.2 and helps in the generation of many new ideas. Brain- storming software can stand alone or be a part of a general group support package. The major features of software packages follow:
• Creation of a large number of ideas. • Large group participation. • Real-time updates. • Information color coding. • Collaborative editing. • Design of brainstorming sessions. • Idea sharing. • People participation. • Idea mapping (e.g., create mind maps). • Text, video, documents, etc. posting. • Remote brainstorming. • Creation of an electronic archive. • Reduction of social loafing.
The major limitations of electronic software support are increased cognitive load, fear of using new technology, and need for technical assistance.
COMPANIES THAT PROVIDE ONLINE BRAINSTORMING SERVICES AND SUPPORT FOR GROUP WORK Some companies and the services and support they provide follow:
• eZ Talks Meetings. Cloud-based tool for brainstorming and idea sharing. • Bubbl.us. Visual thinking machine that provides a graphical representation of
ideas and concepts, helps in idea generation, and shows where ideas and thoughts overlap (visually, in colors).
• Mindomo. Tool for real-time collaboration that offers integrated chat capability. • Mural. Tool that enables collecting and sorting of ideas in rich media files. It is
designed as a Pinboard that invites participants. • iMindQ. Cloud-based service that enables creating mind maps and basic diagrams.
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For an evaluation of 28 online brainstorming tools, see blog.lucidmeetings.com/ blog/25-tools-for-online-brainstorming-and-decision-making-in-meetings/.
ARTIFICIAL INTELLIGENCE SUPPORTS BRAINSTORMING In Chapter 12, we will introduce the use of bots. Some software allows users to create and post a bot (or avatar) that rep- resents people in order to communicate anonymously. Artificial intelligence (AI) can also be used for pattern recognition and identifying ideas that are similar to each other. AI is also used in crowdsourcing (Section 11.7), which is used extensively for idea generation and voting.
Group Support Systems
A group support system (GSS), which was discussed earlier, is any combination of hardware and software that enhances group work. GSS is a generic term that includes all forms of communication and collaborative computing. It evolved after information technology researchers recognized that technology could be developed to support many activities that normally occur at face-to-face meetings when they occur in virtual meetings (e.g., idea generation, consensus building, anonymous ranking). Also, a focus was made on collaboration rather than on minimizing conflicts.
A complete GSS is considered a specially designed information system software, but today, its special capabilities have been embedded in standard IT productivity tools. For example, Microsoft Office 365 includes Microsoft Teams (opening vignette). It also includes the tools for Web conferences. Also, many commercial products have been developed to support only one or two aspects of teamwork (e.g., videoconferencing, idea generation, screen sharing, wikis).
HOW GSS IMPROVES GROUP WORK The goal of GSS is to provide support to participants in improving the productivity and effectiveness of meetings by streamlining and speed- ing up the decision-making process and/or by improving the quality of the results. GSS attempts to increase process and task gains and decrease process and task losses. Overall, GSS has been successful in doing just that. Improvement is achieved by providing support to group members for the generation and exchange of ideas, opinions, and preferences. Specific features such as the ability of participants in a group to work simultaneously on a task (e.g., idea generation or voting) and anonymity produce improvements. The following are some specific GSS support activities:
• Supporting parallel processing of information and idea generation (brainstorming). • Enabling the participation of larger groups with more complete information, knowl-
edge, and skills. • Permitting the group to use structured or unstructured techniques and methods. • Offering rapid, easy access to external information. • Allowing parallel computer discussions. • Helping participants frame the big picture. • Providing anonymity, which allows shy people to contribute to the meeting (i.e.,
to get up and do what needs to be done). • Providing measures that help prevent aggressive individuals from controlling a
meeting. • Providing multiple ways to participate in instant anonymous voting. • Providing structure for the planning process to keep the group on track. • Enabling several users to interact simultaneously (i.e., conferencing). • Recording all information presented at a meeting (i.e., providing organizational
memory).
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For GSS success stories, look for sample cases at vendors’ Web sites. As you will see in many of these cases, collaborative computing led to dramatic process improvements and cost savings.
Note that only some of these capabilities are provided in a single package from one vendor.
u SECTION 11.5 REVIEW QUESTIONS
1. Define GDSS and list the limitations of the initial GSS software.
2. List the benefits of GDSS.
3. List process gains made by GDSS.
4. Define decision room.
5. Describe Web-based GSS.
6. Describe how GDSS supports brainstorming and idea generation.
11.6 COLLECTIVE INTELLIGENCE AND COLLABORATIVE INTELLIGENCE
Groups or teams are created for several purposes. Our book concentrates on support for decision making. This section deals with the collective intelligence and collaborative intel- ligence of groups.
Definitions and Benefits
Collective intelligence (CI) refers to the total intelligence of a group. It is also refers to as the wisdom of the crowd. People in a group are using their skills and knowledge for solving problems and providing new insights and ideas. The major benefits are the ability to solve com- plex problems and/or design new products and services that result from innovations. A major research center on collective intelligence (CI) is the MIT Center for Collective Intelligence (CCI) (cci.mit.edu). A major study aspect of CCI is how people and computers can work together so that teams can be more innovative than any individual, group, or computer can be alone. CI appears in several disciplines ranging from sociology to political science. Our interest here is in CI as it relates to computerized decision making. We cover CI here and in Section 11.7 where we present the topic of crowdsourcing. In Section 11.8, we present swarm intelligence, which is also an application of CI. For the benefits of CI, see 50Minutes.com (2017).
TYPES OF COLLECTIVE INTELLIGENCE One way to categorize CI is to divide it into three major areas of applications: cognition, cooperation, and coordination. Each of these can be further divided. For an overview, see collective intelligence on Wikipedia. Our inter- est is in applications by which the group synergy helps in problem solving and decision making. People contribute their experience and knowledge, and the group interactions and the computerized support help in making better decisions.
Thomas W. Malone, the founder and director of CCI at MIT, considers CI as a broad umbrella. He views collective intelligence as “groups of individuals act- ing collectively in ways that seem intelligent.” The CCI work, known as the Edge, is available at the Edge video (31:45 minutes) available at edge.org/conversation/ thomas_w__malone-collective-intelligence.
Computerized Support to Collective Intelligence
Collective intelligence can be supported by many of the tools and platforms described in Sections 11.4 and 11.5. In addition, the Internet, intranet, and the IoT (Chapter 13) play a major role in facilitating CI by enabling people to share knowledge and ideas.
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Example 1: The Carnegie University Foundation Supports Network Collaboration
The Carnegie Foundation was looking for ways to have people work together collab- oratively in order to accelerate improvements and to share data and learning across its networks of people. The solution is an online workspace called the Carnegie Hub, which serves as an access point to resources and enables engagement in group work and collaboration.
The Hub uses several software products, some of which were described in Section 11.4, such as Google Drive, creating a collaborative workspace. The major aspects of the Carnegie Collection Intelligence project follow:
1. Content is shared in one place (the “cloud”) for everyone to view, edit, or contribute even at the same time.
2. All data and knowledge are stored in one location on the Web. Discovery is easy. 3. Asynchronous conversations using discussion boards are easy; all notes are publicly
displayed, documented, and stored. 4. These aspects facilitate social collaboration, commitment to problem solving, and
peer support. The Carnegie University faculty is now a community of practice, using collective intelligence to plan, create, and solve problems together. For details, see Thorn and Huang (2014).
Example 2: How Governments Tap IoT for Collective Intelligence
According to Bridgwater (2018), governments are using IoT to support decision making and policy creation. Governments are trying to collect information and knowledge from people and increasingly do so via IoT. Bridgwater cites the government of the United Arab Emirates that uses IoT to enhance public decision making. The IoT systems collect ideas and aspirations of the citizens. The collective intelligence platform allows the targeting of narrowly defined groups. Real estate plans are subjected to the opinion of residents in the vicinity of proposed developments. The country’s project of smart cities is combined with CI (Chapter 13). In addition to IoT, there are activities in CI and networks as shown in Application Case 11.1.
Introduction
Water management is one of the most important chal- lenges for many communities. In general, the demand for water is growing while the supply could shrink (e.g., due to pollution). Managing water requires the involvement of numerous stakeholders ranging from consumers and suppliers to local governments and sanitation experts. The stakeholders must work together. The objective is to have responsible water use and water preservation. The accounting office of PwC published report 150CO47, “Collaboration: Preserving
Water Through Partnership That Works” available at pwc.com/hu/hu/kiadvanyok/assets/pdf/pwc_ water_collaboration.pdf. It describes the problem and its benefits and risks. The report shares the differ- ent stakeholders’ perspectives, identifies the success factors of collaboration, and weighs the trade-offs for evaluating alternative solutions for the water manage- ment issue. An interesting framework for a solution is the collaborative modeling developed at Oregon State University in collaboration with Indiana University- Purdue University.
Application Case 11.1 Collaborative Modeling for Optimal Water Management: The Oregon State University Project
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The Challenge
Planning and managing water conservation activities are not simple tasks. The idea is to develop a user- friendly tool that will enable all stakeholders to par- ticipate in these activities. It is necessary to involve the stakeholder communities in using scientifically developed guidelines for designing water conserva- tion practices. Here are some of the requirements of the desired tool:
• The tool needs to be interactive and human guided and operated.
• It needs to be Web-based and user friendly. • Both individuals and groups should be able to
use it. • It should enable users to view and evaluate
solution designs based on both quantitative and qualitative criteria.
The Solution: WRESTORE
Watershed Restoration Using Spatio-Temporal Optimi- zation (WRESTORE) is a Web-based tool that meets the preceding requirements. It is based on AI and ana- lytical optimization algorithms. The algorithms process dynamic simulation models and allow users to spatially optimize the location of new water conservations. In addition to using the dynamic simulation models, users are able to include their own personal subjective views and qualitative criteria. WRESTORE generates alterna- tive practices that users can discuss and evaluate.
Incorporation of human preferences to com- puter solutions makes the solutions more accept- able. The AI part of the project includes machine learning and crowdsourcing (Section 11.7) to solicit
information from the crowd. The reason for the par- ticipative collaboration is that water is an essential resource and should not be only centrally controlled. The AI technologies “democratize” water manage- ment while harnessing the power of people and com- puters to solve difficult water management problems.
The machine-learning algorithms learn from what people are doing. Human feedback helps AI to iden- tify best solutions and strategies. Thus, humans and machines are combined to solve problems together.
The Results
WRESTORE developers are experimenting with the technology in several places and so far have achieved full collaboration from participating stakeholders. Initial results indicate the creation by WRESTORE of innova- tive ideas for developing water resources and distribu- tion methods that save significant amounts of water.
Questions for Case 11.1 1. Crowdsourcing is used to find information from a
crowd. Why is it needed in this case? (see Section 11.7 if you are not familiar with crowdsourcing).
2. How does WRESTORE act as a CI tool?
3. Debate centralized control versus participative col- laboration. Cite the pros and cons of each.
4. Why it is difficult to manage water resources?
5. How can an optimization/simulation/AI model support group work in this case?
Sources: Compiled from Basco-Carrera et al. (2017), KTVZ.com (Channel 21, Oregon, March 21, 2018), and Babbar-Sebens et al. (2015).
How Collective Intelligence May Change Work and Life
For several decades, researchers studied the relationship of CI and work. For example, Doug Engebert, a pioneer in CI, describes how people work together in response to a shared challenge and how they can leverage their collective memory, perception, planning, reasoning, and so on into powerful knowledge. Since Engebert’s pioneering work, the impact of technology is increasing organizations’ CI and building collaborative communi- ties of knowledge. In summary, CI attempts to augment human intelligence to solve busi- ness and social problems. This basically means that CI allows more people to have more engagement and involvement in organizational decision making. At MIT’s CCI, research is done on how people and computers can work together to improve work (see also Sec- tion 11.9). MIT’s CCI focuses on the role of networks, including the Internet, intranets, and IoT. Researchers there found that organizations’ structures tend to be flatter, and more
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decisions are delegated to teams. All this results in decentralized workplaces. For further discussion on MIT’s CCI, see MIT’s blog of April 3, 2016, at executive.mit.edu/blog/will- collective-intelligence-change-the-way-we-work/. For a comprehensive view on how CI can change the entire world, see Mulgan (2017).
A major thrust in CI is the collaboration efforts within a group, as described next.
Collaborative Intelligence
Placing people in groups and expecting them to collaborate with the help of technology may be wishful thinking. Management and behavioral researchers study the issue of how to make people collaborate in groups.
Called by some collaborative intelligence, Coleman (2011) stipulates that group col- laboration has the following 10 components: (1) willingness to share, (2) knowing how to share, (3) being willing to collaborate, (4) knowing what to share, (5) knowing how to build trust, (6) understanding team dynamics, (7) using correct hubs for networking, (8) mentoring and coaching properly, (9) being open to new ideas, and (10) using com- puterized tools and technology. A similar list is provided at thebalancecareers.com/ collaboration-skills-with-examples-2059686.
Computerized tools and technologies are critical enablers of communication, col- laboration, and people’s understanding of each other.
How to Create Business Value from Collaboration: The IBM Study
Groups and team members provide ideas and insights. To excel, organizations must utilize people’s knowledge, some of which is created by collective intelligence. One way to do this is provided by a study of collective intelligence conducted by the IBM Institute for Business Value. The study is available (free) at www-935.ibm.com/services/us/gbs/ thoughtleadership/ibv-collective-intelligence.html. There is also a free executive sum- mary. The study presents three major points:
1. CI can enhance organizational outcomes by correctly tapping the knowledge and experience of working groups (including customers, partners, and employees).
2. It is crucial to target and motivate the appropriate participants. 3. CI needs to address the issue of participants’ resistance to change. All in all, IBM
concludes that “Collective intelligence is a powerful resource for creating value using the experience and insights of vast numbers of people around the world.”
Access the untapped knowledge of your networks, IBM. (www-935.ibm.com/ services/us/gbs/thoughtleadership/ibv-collective-intelligence.html)
An offshoot of CI is crowdsourcing, the topic of the next section (11.7).
u SECTION 11.6 REVIEW QUESTIONS
1. What is collective intelligence (CI)?
2. List the major benefits of CI.
3. How is CI supported by computers?
4. How can CI change work and life?
5. How can CI impact organization structure and decision making?
6. The Carnegie case described how standard collaboration tools create a collective intel- ligence infrastructure. The WRESTORE case described a modeling analytical framework that enables stakeholders to collaborate. What are the similarities and differences between the two cases?
7. Describe collaborative intelligence.
8. How do you create business value from collective intelligence?
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11.7 CROWDSOURCING AS A METHOD FOR DECISION SUPPORT
Crowdsourcing refers to outsourcing tasks to a large group of people (crowd). One of the major reasons for doing so is the potential for the wisdom of a crowd to improve decision making and assist in solving difficult problems; see Power (2014). Therefore, crowdsourc- ing can be viewed as a method of collective intelligence. This section is divided into three parts: The essentials of crowdsourcing, crowdsourcing as a decision support mechanism, and implementing crowdsourcing for problem solving.
The Essentials of Crowdsourcing
Crowdsourcing has several definitions because it is used for several purposes in a number of fields. For a tutorial on crowdsourcing and examples, view the video (14:51 min.) at youtube.com/watch?v=lXhydxSSNOY. Crowdsourcing means that an organization is outsourcing or farming out work for several reasons: Necessary skills may not be available internally, speed of execution is needed, problems are too complex to solve, or special innovation is needed.
SOME EXAMPLES
• Since 2005, Doritos Inc. has run a “Crash the Super Bowl” contest for creating a 30-second video for the Super Bowl. The company has given $7 million in prizes in the last 10 years for commercials composed by the public.
• Airbnb is using user-submitted videos (15 seconds each) that describe travel sites. • Dell’s Idea Storm (ideastorm.com) enables customers to vote on features of Idea
Storm the customers prefer, including new ones. Dell is using a technically oriented crowd, such as the Linux (linux.org) community. The crowd submits ideas and sometimes members of the community vote on them.
• Procter & Gamble’s researchers post their problems at innocentive.com and ninesigma.com, offering cash rewards to problem solvers. It uses other crowdsourc- ing service providers such as yourencore.com.
• The LEGO company has a platform called LEGO Ideas through which users can submit ideas for new LEGO sets and vote on submitted ideas by the crowd. Accepted ideas generate royalties to those who proposed them if the ideas are commercialized.
• PepsiCo solicits ideas regarding new potato chip flavors for the company’s Lay’s brand. Over the years, the company has received over 14 million suggestions. The estimated contribution to sales increase is 8 percent.
• Cities in Canada are creating real-time electronic city maps to inform cyclists about high-risk areas to make the streets safer. Users can mark the maps when they expe- rience a collision, bike theft, road hazard, and so on. For details, see Keith (2018).
• U.S. intelligence agencies have been using ordinary people (crowds) to predict world events ranging from the results of elections to the direction of prices.
• Hershey crowdsourced potential solutions of how to ship chocolate in warm climates. For how this was done, see Dignan (2016). The winning prize was $25,000.
These examples illustrate some of the benefits of crowdsourcing, such as wide exposure to expertise, increased performance and speed, and improved problem-solving and innova- tion capabilities. These examples also illustrate the variety of applications.
MAJOR TYPES OF CROWDSOURCING Howe (2008), a crowdsourcing pioneer, divided the crowdsourcing applications into the following types (or models):
1. Collective intelligence (or wisdom). People in crowds are solving problems and providing new insights and ideas leading to product, process, or service innovations.
2. Crowd creation. People are creating various types of content and sharing it with others (for pay or free). The created content may be used for problem
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Another way to classify crowdsourcing is by the type of work it does. Some examples with a crowdsourcing vendor for each follow:
• Logo design—Design Bill • Problem solving—InnoCentive, NineSigma, IdeaConnection • Business innovation—Chardix • Brand names—Name This • Product and manufacturing design—Pronto ERP • Data cleansing—Amazon Mechanical Turk • Software testing—uTest • Trend watching—TrendWatching • Images—Flickr Creative Commons
For a compressive list of crowdsourcing, collective intelligence, and related compa- nies, see boardofinnovation.com.
THE PROCESS OF CROWDSOURCING The process of crowdsourcing differs from applica- tion to application, depending on the nature of the specific problem to be solved and the method used. However, the following steps exist in most enterprise crowdsourcing applications, even though the details of the execution may differ. The process is illustrated in Figure 11.3.
1. Identify the problem and the task(s) to be outsourced. 2. Select the target crowd (if not an open call). 3. Broadcast the task to the crowd (or to an unidentified crowd in an open call). 4. Engage the crowd in accomplishing the task (e.g., idea generation, problem
solving). 5. Collect user-generated content. 6. Have the quality of submitted material evaluated by the management that initiated
the request, by experts, or by a crowd. 7. Select the best solution (or a short list). 8. Compensate the crowd (e.g., the winning proposal). 9. Implement the solution.
Note that we show the process as sequential, but there could be loops returning to previ- ous steps.
Crowdsourcing for Problem-Solving and Decision Support
Although there are many potential activities in crowdsourcing, major ones are support- ing the managerial decision-making process and/or providing a solution to a problem. A complicated problem that is difficult for one decision maker or a small group to solve may be solved by a crowd, which can generate a large number of ideas for solving a
solving, advertising, or knowledge accumulation. Content creation can also be done by splitting large tasks into small segments (e.g., contributing content to create Wikipedia).
3. Crowd voting. People are giving their opinions and ratings on ideas, products, or services, as well as evaluating and filtering information presented to them. An example is voting in American Idol competitions.
4. Crowd support and funding. People are contributing and supporting endeavors for social or business causes, such as offering donations, and micro-financing new ventures.
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problem. However, inappropriate use of crowdsourcing could generate negative results (e.g., see Grant, 2015). On how to avoid the potential pitfalls of crowdsourcing, see Bhandari et al., 2018.
THE ROLE OF CROWDSOURCING IN DECISION MAKING Crowds can provide ideas in a col- laborative or a competitive mode. However, the crowd’s role may differ at different stages of the decision-making process. We may use a crowd to decide how to respond to a com- petitor’s act or to help us decide whether a proposed design is useful. Chiu et al. (2014) adopted Herbert Simon’s decision-making process model to outline the potential roles of a crowd. Simon’s model includes three major phases before implementation: intelligence (information gathering and sharing for the purpose of problem solving or opportunity exploitation, problem identification, and determination of the problem’s importance), design (generating ideas and alternative solutions), and choice (evaluating the generated alternatives and then recommending or selecting the best course of action). Crowdsourc- ing can provide different types of support to this managerial decision-making process. Most of the applications are in the design phase (e.g., idea generation and co-creation) and in the choice phase (voting). In some cases, support can be provided in all phases of the process.
Implementing Crowdsourcing for Problem Solving
While using an open call to the public can be done fairly easily by the problem owner, people who need to solve difficult problems usually like to reach experts for solving problems (solvers). For a company to obtain assistance in finding such experts, especially externally, it can use a third-party vendor. Such vendors have hundreds of thousands or even millions of preregistered solvers. Then, the vendor can do the job as illustrated in Application Case 11.2.
FIGURE 11.3 The Crowdsourcing Process.
Problem owner
Problem
Preparation, specific task(s) to outsource
Crowd membersCrowd Selection
Ideas, solutions submitted
Broadcasting task
Crowd perform work
Idea evaluation
Recommended solution
Activities
Components
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GlaxoSmithKline (GSK) is a UK-based global phar- maceutical/healthcare company, with over 100,000 employees. The company strives on innovations. However, despite its mega size and global presence, it has problems that it needs outside expertise to solve.
The Problem
The company researched a potentially disruptive technology that promised cure to difficult diseases. The company wanted to discover which disease to use as a test bed for the potential innovative treatments. It was necessary to make sure that the selection will cover a disease where every aspect of the new treatment is checked. Despite its large size, GSK wanted some outside expertise to sup- port and check the in-house research efforts.
The Solution
GSK decided to crowdsource the problem solution to experts, using InnoCentive Corp. (Innocentive. com). InnoCentive is a US-based global crowdsourc- ing company. The company receives challenges from client companies like GSK. These challenges are posted for solvers to see with the potential rewards, in InnoCentive’s Challenge Center. Solvers that think they want to participate follow instructions and may
sign an agreement. The solutions submitted are eval- uated, and awards are provided to the winners.
The GSK Situation
In total, 397 solvers engaged in this challenge, even the reward was minimal ($5000). The solvers resided in several countries. The solvers submitted 66 pro- posed solutions. The entire process lasted 75 days.
The Results
The winning solution proposed a new area that was not considered by GSK teams. The proposer was a Bulgarian who based his idea on a Mexican publi- cation. Several other winning proposals contributed useful ideas. Also, the process enabled collaboration between the GSK team and the winning researchers.
Questions for Case 11.2 1. Why did GSK decide to crowdsource?
2. Why did the company use InnoCentive?
3. Comment on the global nature of the case.
4. What lessons did you learn from this case?
5. Why do you think a small $5000 reward is sufficient?
Sources: Compiled from InnoCentive Inc. Case Study GlaxoSmithKline. Waltham, MA., GSK Corporate Information (gsk. com) and InnoCentive.com/our-solvers/.
Application Case 11.2 How InnoCentive Helped GSK Solve a Difficult Problem
CROWDSOURCING FOR MARKETING More than 1 million customers are registered at Crowd Tap, the company that provides a platform named Suzy that enables marketers to conduct crowdsourcing studies.
u SECTION 11.7 REVIEW QUESTIONS
1. Define crowdsourcing.
2. Describe the crowdsourcing process.
3. List the major benefits of the technology.
4. List some areas for which crowdsourcing is suitable.
5. Why may you need a vendor to crowdsource the problem-solving process?
11.8 ARTIFICIAL INTELLIGENCE AND SWARM AI SUPPORT OF TEAM COLLABORATION AND GROUP DECISION MAKING
AI, as seen in Chapter 2, is a diversified field. Its technologies can be used to support group decision making and team collaboration.
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AI Support of Group Decision Making
A major objective of AI is to automate decision making and/or to support its process. This objective holds also for decisions made by groups. However, we cannot automate a decision made by a group. All we can do is to support some of the steps in a group’s decision-making process.
A logical place to start is Figure 11.1. We can examine the different steps of the pro- cess and see where AI can be used.
1. Meeting preparation. AI is used to find a convenient time for meetings to take place. AI can assist in scheduling meetings so that all can participate.
2. Problem identification. AI technologies are used for pattern recognition that can identify areas that need attention. AI can be used in other types of analysis to identify potential or difficult to pinpoint problems.
3. Idea generation. AI is known for its quest for creativity. Team members can increase their creativity when they use AI for support.
4. Idea organization. Natural language processing (NLP) can be used to sort ideas and organize them for improved evaluation.
5. Group interaction and collaboration. AI can facilitate communication and collabo- ration among group members. This activity is critical in the process of arriving at a consensus. Also, Swarm AI (see the end of this section) is designed to increase interactions among group members so their combined wisdom is elevated.
6. Predictions. AI supports predictions that are required to assess the impact of the ideas generated regarding performance and/or impacts in the future. Machine learn- ing, deep learning, and Swarm AI are useful tools in this area.
7. Multinational groups. Collaboration among people located in different countries is on the rise. AI enables group interaction of people who speak different languages, in real time.
8. Bots are useful in supporting meetings. Group members may consult Alexa and other bots. Chatbots can provide answers to queries in real time.
9. Other advisors. IBM Watson can provide useful advice during meetings, supple- menting knowledge provided by participants and by Alexa.
Example
In 2018, Amazon.com was looking for a site for its second headquarters. A robot named Aiera from Wells Fargo Securities used deep learning to predict that the winning site would be Boston (Yurieff, 2018a). (When this chapter was written, the decision had not been made.)
For an academic approach on how to improve group decision making by AI, see Xia (2017).
AI Support of Team Collaboration
Organizations today are looking for ways to increase and improve collaboration with employees, business partners, and customers. To gain insight into how AI may impact collaboration, Cisco Systems sponsored a global survey, AI Meets Collaboration (Morar HPI, 2017), regarding the impact of AI, including the use of virtual assistants in the work space. The major findings of this survey are:
1. Virtual assistants increase employees’ productivity, creativity, and job satisfaction. Bots also enable employees to focus on high-value tasks.
2. Bots are accepted as part of workers’ teams.
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3. Bots improve conference calls. They also can take meetings notes and schedule meetings.
4. AI can use facial recognition to sign in eligible people to meetings. 5. Personal characteristics are likely to influence how people feel about AI in the
workplace. 6. Employees in general like to have AI in their teams. 7. Security is a major concern when AI, such as virtual assistants, is used in teams. 8. The major AI tools that are most useful are NLP and voice response; AI can also
summarize the key topics of meetings and understand participants’ needs. AI can be aware of organizational goals and workers’ skills and can make suggestions accordingly.
For how virtual meetings are supported with AI by Cisco Systems in their leading products, see Technology Insight 11.2.
TECHNOLOGY INSIGHT 11.2 How Cisco Improves Collaboration with AI
Cisco Systems is well known for its collaboration products such as Spark and Webex. The first step in introducing AI was to acquire MindMeld’s AI platform for use in Cisco’s collaboration products. The project’s objective was to improve the conversational interferences for any application or device so users could better understand the context of conversations. MindMeld uses machine learning to improve the accuracy of voice and text communication. To do so, it uses NLP and five varieties of machine learning. Cisco is also integrating IBM Watson into its enterprise collabora- tion solutions. As you may recall from Chapter 6, Watson is a powerful advisor. AI collaboration tools can increase efficiency, speed idea generation, and improve the quality of decisions made by groups. The improved Cisco’s technology will be used in conference rooms and everywhere else. One of the major AI projects is the assistant to Spark.
Monica, a Digital Assistant to the Spark Collaboration Platform Monica is trained to answer users’ queries by employing machine learning. Furthermore, users can use Monicait to interact with the Spark collaboration platform using natural language com- mands. It is an enterprise assistant similar to Alexa and Google Assistant (Chapter 12). Cisco’s Monica is the world’s first enterprise-ready voice assistant specifically designed to support meetings. The bot has deep-domain conversational AI that adds cognitive capabilities to the Spark platform.
Monica can assist users in several of the steps of Figure 11.1, such as:
• Organize meetings. • Provide information to participants before and during meetings. • Navigate and control Spark’s devices. • Help organizers find a meeting room and reserve it. • Help share screens and bring up a whiteboard. • Take meeting notes and organize them.
In the near future, Monica will know about participants’ internal and external activities and will schedule meetings using this information. Additional functions to support more steps of the pro- cess in Figure 11.1 will be added in the future.
For more about the assistant, see youtube.com/watch?v=8OcFSEbR_6k (5:10 minutes).
Note: Cisco Spark will become Webex Teams with more AI functionalities. In addition, Webex meetings will include videoconferencing for collaboration and other supports to meetings.
Sources: Compiled from Goecke (2017), Finnegan (2018), and Goldstein (2017).
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Swarm Intelligence and Swarm AI
The term swarm intelligence refers to the collective behavior of decentralized, self- organized systems, natural or artificial (per Wikipedia). Such systems consist of things (e.g., ants, people) interacting with each other and their environment. A swarm’s actions are not centrally controlled, but they lead to intelligent behavior. In nature, there are many examples (e.g., ant colonies, fish schools) of such behaviors.
Natural groups were observed to amplify their group intelligence by forming swarms. Social creatures, including people, can improve the performance of their individual mem- bers when working together as a unified system. In contrast with animals and other species whose interactions among group members are natural, people need technology to exhibit swarm intelligence. This concept is used in studies and implementation of AI and robotics. The major applications are in the area of predictions.
Example
A study at Oxford University (United Kingdom) involved predicting the results of all 50 English Premier League soccer games over five weeks. A group of independent judges scored 55 percent accuracy when working alone. However, when predicting using an AI swarm, their prediction success increased to 72 percent (an improvement of 31 percent). Similar improvement was recorded in several other studies.
In addition to improved prediction accuracy, studies show that using swarm AI results in more ethical decisions than that of individuals (Reese, 2016).
SWARM AI TECHNOLOGY Swarm AI (or AI swarm) provides the algorithms for the inter- connections among people creating the human swarm. These connections enable the knowledge, intuition, experience, and wisdom of individuals to merge into single improved swarm intelligence. Results of swarm intelligence can be seen in the TED presentation (15:58 min.) at youtube.com/watch?v=Eu-RyZt_Uas. Swarm AI is used by several third- party companies (e.g., Unanimous.aI, as illustrated in Application Case 11.3.
XPRIZE is a nonprofit organization that allocates prizes via competitions to promote innovations that have the potential to change the world for the bet- ter. The main channel for designing prizes that solve humanity’s grandest challenges is called Visioneer- ing. It attempts to harness the power of the global crowd to develop solutions to important challenges. The organization’s major event is an annual summit meeting where prizes are designed and proposals are evaluated. The experts at XPRIZE develop concepts and turn them into incentivized competitions. Prizes are donated by leading corporations.
For example, in 2018, IBM Watson donated a $5 million prize called “AI approaches and collabora- tion.” The competition had 142 registered teams, and 62 were left in round 2 in June 2018. The teams are
invited to create their own goals and solutions to a grand challenge.
The Problem
Every year, there is a meeting of 250 members of “Visioneers Summit Ideation” where top experts (entrepreneurs, politicians, scientists, etc.), partici- pate to discover and prioritize topics for the XPRIZE agenda.
Finding the top global problems can be a very complex challenge due to a large number of vari- ables. In just a few days, top experts need to use their collective wisdom to agree on the next year’s XPRIZE top challenges. The method used to support the group’s decision is a critical success factor.
(Continued )
Application Case 11.3 XPRIZE Optimizes Visioneering
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The Solution
In the 2017 annual meeting for determining what challenge to use for 2018, the organization used the swarm AI platform (from Unanimous AI). Several small groups (swarms) moderated by AI algorithms were created to discover challenging topics. The mis- sion was to explore ideas and agree on preferred solutions. The objective was to use the talents and brainpower of the participants.
In other words, the objective was to use the thinking together feature of swarm AI to generate each group’s synergy with the AI algorithms acting as moderators. This way, smarter decisions were generated by the groups than its individual par- ticipants. The different groups examined six pre- selected topics: energy and infrastructure, learning human potential, space and new frontiers, plant and environment, civil society, and health and well-being. The groups brainstormed the issues. Then, each participant created a customized evalu- ation table. The tables were combined and ana- lyzed by algorithms.
Application Case 11.3 (Continued)
The Swarm AI replaced traditional voting meth- ods by optimizing the detailed contribution of each participant.
The Results
Use of swarm AI did the following:
• Supported the generation of optimized answers and enabled fast buy-in from the participants.
• Enabled all participants to contribute. • Provided a better voting system than in previ-
ous years.
Questions for Case 11.3 1. Why is the group discussion in this case complex?
2. Why is getting a consensus when top experts are involved more difficult than when non-experts are involved?
3. What was the contribution of swarm AI?
4. Compare simple voting to swarm AI voting.
Sources: Compiled from Unanimous AI (2018), xprize.org, and xprize.org/about.
SWARM AI FOR PREDICTIONS Swarm AI was used by Unanimous AI for making predic- tions in difficult-to-assess situations. Examples are:
• Predicting Super Bowl #52 number of points scored (used for spread waging). • Predicting winners in the regular NFL season. • Predicting the top four finishers of the 2017 Kentucky Derby. • Predicting the top recipients of the Oscars in 2018.
u SECTION 11.8 REVIEW QUESTIONS
1. Relate the use of AI to the activities in Figure 11.1.
2. Discuss the different ways that AI can facilitate group collaboration.
3. How can AI support group evaluation of ideas?
4. How can AI facilitate idea generation?
5. What is the analogy of swarm AI to swarms of living species?
6. How is swarm AI used to improve group work and to initiate group predictions?
11.9 HUMAN–MACHINE COLLABORATION AND TEAMS OF ROBOTS
Since the beginning of the Industrial Revolution, people and machines have worked together. Until the late 1900s, the collaboration was in manufacturing. But since then, due to advanced technology and changes in the nature of work, human–machine collabora- tion has spread to many other areas, including performing mental and cognitive work
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and collaborating on managerial and executive work. According to Nizri (2017), human and AI collaboration will shape the future of work (see also Chapter 14).
Humans and machines can collaborate in many ways, depending on the tasks they perform. The collaboration with robots in the manufacturing scenario is an extension of the older model in which humans and robots collaborated with humans controlling and monitoring production and robots doing physical work that requires speed, power, accuracy, or nonstop attention. Robots are also doing work in hazardous environments. In general, robots complement human capabilities. An example is Amazon’s distribution centers where over 50,000 mobile robots do a variety of tasks, mostly in hauling materials and helping to fulfill customer orders. The robotic technology enables fully collaborative solutions. For details, watch the video at Kuka kuka.com/en-us/technologies/human- robot-collaboration. Kuka’s system allows the execution of complex jobs that can be done cost effectively.
Another collaborative human-robotic system is called YuMi. To see this sys- tem (from ABB Robotics) at work, watch the 4:38 min. video at youtube.com/ watch?v=2KfXY2SvlmQ. Notice that the robot has two arms.
Human–Machine Collaboration in Cognitive Jobs
Advancement in AI enables the automation of nonmanual activities. While some intelligent systems are fully automated (see automated decision making in Chapter 2 and chatbots in Chapter 12), there are many more examples of human–machine collaboration in cognitive jobs (e.g., in marketing and finance). An example is in investment decisions. A human asks the computer for advice concerning investments, and after receiving the advice, can ask more questions, changing some of the input. The difference from the past is that today the computers (machines) can provide much more accurate suggestions, by using machine learning and deep learning. Another collaboration example involves medical diagnoses of complex situations. For example, IBM Watson provides medical advice, which permits doctors and nurses to significantly improve their jobs. Actually, the entire field of machines advising humans is reaching new heights. For more on the increasing collaborative power of AI, see Carter (2017).
TOP MANAGEMENT JOBS A major task of managers is decision making, which has become one area of human–machine collaboration. Use of AI and analytics has improved decision making considerably, as illustrated throughout this book. For an overview, see Wladawsky-Berger (2017).
McKinsey & Company and MIT are two major players in researching the topic of col- laboration between managers and machines. For example, Dewhurst and Wilmott (2014) report on its increased use of man-machine collaboration, using deep learning. A Hong Kong company even appointed a decision-making algorithm to its board of directors. Com- panies are using crowdsourcing advice to support complex problem solving, as illustrated in Section 11.7.
Robots as Coworkers: Opportunities and Challenges
Sometime in the future, walking and talking humanoid robots will socialize with humans during breaks from work. Someday, robots will become cognitive coworkers and help people be more productive (as long as people do not talk too much with the robots).
According to Tobe (2015), a study at a BMW factory found that human–robot col- laboration could be more productive than either humans or robots working by themselves. Also, the study found that collaboration reduced idle time by 85 percent. This is because people and machines capitalize on the strengths of each (Marr, 2017).
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The following challenges must be considered:
• Designing a human–machine team that capitalizes on the strength of each partner. • Exchanging information between humans and robots. • Preparing company employees in all departments for the collaboration (Marr,
2017). • Changing business processes to accommodate human–robot collaboration (Moran,
2018). • Ensuring the safety of robots and employees that work together.
TECHNOLOGIES THAT SUPPORT ROBOTS AS COWORKERS Yurieff (2018b) lists the following examples of facilitating or considering robots as coworkers.
1. Virtual reality can be used as a powerful training tool (e.g., for safety). 2. A robot is working with an ad agency in Japan to generate ideas. 3. A robot can be your boss. 4. Robots are coworkers in providing parts out of bins in assembly lines and can check
quality together with humans. 5. AI tools measure blood flow and volume of the cardiac muscles in seconds (instead
of minutes when done completely by a radiologist). This information facilitates the decisions made by radiologists.
BLENDING HUMANS AND AI TO BEST SERVE CUSTOMERS Genesys Corp. commissioned Forrester Research Company to conduct a global study in 2017 to find how companies are using AI to improve customer service. The study, titled “Artificial Intelligence with the Human Touch,” is available at no charge from genesys.com/resources/artificial- intelligence-with-the-human-touch. A related video is available at youtube.com/ watch?v=NP2qqwGTNPk.
The study revealed the following:
1. “AI is already transforming enterprises by increasing worker efficiency and produc- tivity, delivering better customer experiences and uncovering new revenue streams” (from the Executive Summary).
2. A major objective of man–machine collaboration is to improve the satisfaction of both customers and companies’ agents rather than reduce cost.
3. Human agents’ ability to connect emotionally with customers for the increased satisfaction of themselves and customers is superior to that of service provided by AI.
4. By blending the strengths of humans and AI, companies achieve better customer service satisfaction of customers (71 percent) and agents (69 percent).
Note that AI excels in the support of marketing and advertising as illustrated in Chapter 2. See also Loten (2018) for the use of AI to support customer relationship management (CRM) and of crowdsourcing and collective intelligence to support marketing.
COLLABORATIVE ROBOTS (CO-BOTS) Collaborative robots (co-bots) are designed to work with people, assisting in executing various tasks. These robots are not very smart, but their low cost and high usability make them popular. For details, see Tobe (2015).
Teams of collaborating Robots
One of the future directions in robotics is creating teams of robots that are designed to do complex work. Robot teams are common in manufacturing where they serve each other or join a robot group in simple assembly jobs. An interesting example is the use of a team of robots in preparation to land on Mars.
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Example: Teams of Robots to Explore Mars
Before people land on Mars, scientists need to know more about the “Red Planet.” The idea was to use teams of robots. The German Research Centers for Artificial Intelligence (DFKI) conducted simulation experiments in the desert of Utah. The details of this simulation are described by Staff Writers (2016). The process is illustrated in a 4:54 min. video at youtube. com/watch?v=pvKIzldni68/ showing robots’ collaboration. For more information, see robotik.dfki-bremen.de/en/research/projects/ft-utah.html.
DFKI is not the only entity that plans to explore the surface of Mars. NASA plans to send swarms of robot bees with flapping wings called Marsbees that will operate in a group to explore the land and air of the Red Planet. The reason for the flapping wings structure is to enable low-energy flights (like bumblebees). Each robot is the size of a bee. Part of a wireless communication network, Marsbees will together create networks of sensors. Information will be delivered to a mobile base (see Figure 11.4, showing one robot) that will be the main communication center and a recharging station for the Marsbees. For more information, see Kang (2018).
Getting robots to work together is being researched at MIT. They use their per- ception system to sense the environment, and then they communicate their findings to each other and coordinate their work. For example, a robot can open a door for another robot. Read about how this is done and watch a video at ft.com/video/ ea2d4877-f3fb-403d-84a8-a4d2d4018c5e.
Example
Alibaba.com is using teams of robots in its smart warehouses where robots do 70 percent of the work. This is shown in a video at youtube.com/watch?v=FBl4Y55V2Z4.
Social collaboration of robots is being investigated by watching the behavior of swarms of ants and other species to learn how to design robots to work in teams. Watch the TED presentation at youtube.com/watch?v=ULKyXnQ9xWA on how to design a robot collaboration.
Having robots collaborate involves several issues such as making sure they do not col- lide with each other. This is a part of the safety issue regarding robotics. Finally, you can build your own team of robots with LEGO’s Mindstorms. For details, see Hughes and Hughes (2013).
FIGURE 11.4 Team of Robots Prepares to Go to Mars. Source: C. Kang.
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Chapter Highlights
• Groupware refers to software products that pro- vide collaborative support to groups (including conducting meetings).
• Groupware can support decision-making and problem solving directly or indirectly by improv- ing communication between team members.
• People collaborate in their work (called group work). Groupware (i.e., collaborative computing software) supports group work.
• Group members may be in the same organiza- tion or in different organizations in the same or in different locations and may work at the same or different times.
• The time/place framework is a convenient way to describe the communication and collaboration pat- terns and support of group work. Different tech- nologies can support different time/place settings.
• Working in groups can result in many benefits, including improved decision making, increased productivity and speed, and cost reductions.
• Communication can be synchronous (i.e., same time) or asynchronous (i.e., sent and received at different times).
• The Internet, intranets, and IoT support virtual meetings and decision making through collabora- tive tools and access to data analysis, information, and knowledge.
• Groupware for direct support typically contains capabilities for brainstorming, conferencing, scheduling group meetings; planning; resolving conflicts; videoconferencing; sharing electronic documents; voting; formulating policy; and ana- lyzing enterprise data.
• A GDSS is any combination of hardware and software that facilitates decision-making meet- ings. It provides direct support in face-to-face settings and in virtual meetings, attempting to increase process gains, and reducing process losses of group works.
• Collective intelligence is based on the premise that the combined wisdom of several collabo- rating people is greater than that of individuals working separately.
• Each of the several configurations of collective intelligence can be supported differently by technology.
• Several collaboration platforms, such as Micro- soft Teams and Slack, can facilitate collective intelligence.
• Idea generation and brainstorming are key activ- ities in group work for decision making. Several collaboration software and AI programs are sup- porting these activities.
• Crowdsourcing is a process of outsourcing work to a crowd. Doing so can improve problem solving, idea generation, and other innovative activities.
• Crowdsourcing can be used to make predictions by groups of people, including crowds. Results have shown better predictions, especially when communication is used among the predictors than when no communication was enabled.
• One method of communication in crowdsourc- ing is based on swarm intelligence. A technol- ogy known as swarm AI has had significant success.
• AI can support many activities in group deci- sion making.
• Human–machine collaboration can be a major method of work in the future.
• Machines that once supported manufacturing work are used now also in support of cogni- tive, including managerial, work.
• For people and machines to work in teams, it is necessary to make special preparations.
• Robots may work in exclusive teams. They do so in manufacturing and possibly in other activities (e.g., explore Mars) as they become more intelligent.
u SECTION 11.9 REVIEW QUESTIONS
1. Why is there an increase in human–machine collaboration?
2. List some benefits of such collaboration.
3. Describe how collaborating robotics can be used in manufacturing.
4. Discuss the use of teams of robots.
5. What will do robots on Mars?
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Chapter 11 • Group Decision Making, Collaborative Systems, and AI Support 681
Exercises
1. What are wikis? Search the Internet for some of the most popular tools for compiling wikis and putting them online.
2. Skype has been around for about 20 years but is still one of the most popular tools for online communication. Discuss its adoption in business and the advantages of using it.
3. What is crowdsourcing, and how it is used for business purposes? Search for two online crowdsourcing platforms and compare their pros and cons. (Hint: Kickstarter and Indiegogo are two good places to start.)
4. What is Slack, and how it is used? How is it different from other online cooperation tools?
5. Some software tools are aimed at improving cooperative work for designers. Do some research on the Internet and compare two of them. (Hint: Adobe XD and InVision Studio are two of the most popular in the field.)
6. How does the creative business sector use fanbases to support creative endeavors? (Hint: Explore platforms such as Patreon.)
7. Visit the Ko-Fi (“Buy me a Coffee”) Web site (https:// ko-fi.com/) and discuss how it can be used.
8. Which are the most common cloud services for securely storing documents online? What other applications can be used through these cloud services?
9. What is Quora, and what sets it apart as an online coop- eration tool? Search for any topic of interest on the site and base your explanation on the results.
10. Google Suite is a free platform available to anyone who signs up for a Google account. What tools are available to users?
11. Read Pena (2017). Examine the 12 benefits of collabora- tion. Which are related to social collaboration?
12. Compare Microsoft’s Universal Translator to Google’s Translator. Concentrate on face-to-face conversation in real time.
13. Pick at least five social networks that can be used to share news over the Web and compare them.
14. Investigate the status of IBM Connections Cloud. Exam- ine all the collaboration and communication features. How does the product improve productivity? Write a report.
Key Terms
Questions for Discussion
1. Explain why it is useful to describe group work in terms of the time/place framework.
2. Describe the kinds of support that groupware can pro- vide to decision makers.
3. Explain why most groupware is deployed today over the Web.
4. Explain in what ways physical meetings can be ineffi- cient. Explain how technology can make meetings more effective.
5. Explain how GDSS can increase some benefits of col- laboration and decision making in groups and eliminate or reduce some losses.
6. The initial term for group support system (GSS) was group decision support system (GDSS). Why was the
word decision dropped? Does this make sense? Why, or why not?
7. Discuss why Microsoft SharePoint is considered a work- space. What kind of collaboration does it support?
8. Reese (2017) claims that swarm AI can be used instead of polls for market research. Discuss the advantages of swarm AI. In what circumstances would you prefer each method? (Read “Polls vs. Swarms” at Unanimous AI.)
9. What is a collaborative robot? What is an uncollabora- tive one?
10. Discuss the ways in which social collaboration can improve work in a digital workplace.
11. Provide an example of using analytics to improve deci- sion making in sport.
asynchronous brainstorming collective intelligence collaborative workspace crowdsourcing decision room
group decision making group decision support
system (GDSS) group support system
(GSS) groupthink
groupware group work idea generation online workspace process gain process loss
swarm intelligence synchronous (real-time) virtual meeting virtual team
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682 Part IV • Robotics, Social Networks, AI and IoT
15. Compare Microsoft Teams to Spark Teams. Write a report.
16. Waze is a system that uses online cooperation to map traffic, accidents, and other transportation-related issues. Describe how the application works in practice.
17. Go to https://biz30.timedoctor.com/online- collaboration-tools/ and discuss any five of the 55 online collaboration tools mentioned on the page.
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