Who's Who in Collaborative Decision Making

This report highlights vendors offering collaborative decision-making (CDM) platforms. These platforms support improved decision quality and transparency by assisting the right decision makers to find relevant information, discuss an issue, assess and document assumptions, brainstorm and evaluate options, agree on a course of action and then capture the process to mine and reuse best practices.

Key Findings

• CDM platforms are emerging to fill the gap in decision support for tactical and strategic decisions most often made by knowledge workers.
• CDM platforms combine business intelligence (BI) and other sources of information used for decision making with social networking and collaboration capabilities, decision support tools, methodologies and models to improve and capture the decision process.
• Some BI vendors are adding social software capabilities to their BI platforms to enable collaborative BI — some vendors use the term social BI — to facilitate discussion among decision makers on specific BI content, as opposed to collaboration on the entire decision process that CDM supports.
• Collaborative BI provides part of the functionality of what a broader CDM platform could enable and could be a steppingstone to broad and deep support for CDM, but collaborative BI does not equal CDM.
• The primary challenge to CDM adoption is cultural. CDM will tend to be adopted in more progressive companies that view and value fact-based decision making as a core competency and critical to their success.
• Initial adoption of CDM has been within workgroups or lines of business concerning specific business-process-centric decisions, such as resource allocation optimizations, vendor selection, planning and forecasting, and new product planning.

Recommendations

• Find a senior business executive willing to sponsor cultural change in support of fact-based, transparent decision making. The BI competency center is a logical place from which to spearhead a CDM initiative.
• Demonstrate the value of CDM through pilot projects, decision audits and simulations. Linking decisions to performance metrics, training decision makers in decision-making best practices, and using CDM in trade-off and optimization decisions will further demonstrate the value of CDM.
• Focus initially on definable departmental, line-of-business or process-specific decision processes, such as vendor selection, portfolio optimization, strategy management or forecasting, where the benefit of higher-quality and transparent decision making is easy to measure.

Market Overview

Effective decision making at all levels of an organization separates high-performing companies from poorly performing ones. Decision making is such a fundamental activity to the success of any organization — regardless of whether it is for profit, not for profit or a government — that improving it is by far the No. 1 driver of BI investment. Despite significant investments in BI and analytics, made in the name of improving decisions, the vast majority of organizations make thousands of increasingly collaborative decisions, often with poor outcomes, without insight into how decisions are made or their effectiveness. This is slowly changing, as organizations recognize the need for improved decision quality and transparency. Emerging CDM platforms are helping to solve this perennial challenge by combining BI and other sources of information used for decision making with social networking and collaboration capabilities, and with decision support tools/algorithms and models, to help knowledge workers make and capture higher-quality decisions. This report features platforms that provide CDM capabilities (see Note 1 for an explanation of evaluation criteria) that improve the quality and transparency of decisions by:

• Visually depicting what decision needs to be made, what the options are, what the weighted criteria are, and what information is relevant to the decision.
• Identifying and bringing together the right people, the right information and the right analysis tools.
• Alerting decision makers to events and changing patterns that indicate the need to make a decision.
• Allowing participants to discuss an issue, assess and capture assumptions, brainstorm and evaluate options, and agree on a course of action, thus enabling a new style of consensus-driven leadership.
• Capturing details of the collaboration and the information and assumptions used to make decisions.
• Providing decision tools, engines and methodologies to optimize decisions.
• Reducing the risk posed by personal bias, group think, failure to consider contrary views and blindness to the secondary effects of a decision.
• Improving the transparency of decisions by capturing the details of the decision-making process and recording the "who," "what," "when," "where," "why" and "how" of a decision, including all inputs and assumptions.
• Linking the decision-making process to the actual outcome of the decision itself, so that it can be measured and mined for decision-making best practices, patterns that could provide leading indicators of changes in the business environment, and templates for future decision making.

Organizations make many decisions every day at different levels of the organization, with different degrees of impact on the organization, and with varying levels of complexity, frequency and predictability. Operational decisions that can be made based on well-known decision logic and business rules and are highly structured, predictable and repeatable, such as loan approvals and fraud detection, or real-time decisions about customer promotions and offers, can be automated. At Gartner, we call this increasingly deployed category of decision support "intelligent decision automation," wherein well-known decision rules and workflows are embedded in analytic applications. However, CDM fills a gap in decision support for tactical and strategic decisions that are less frequent in nature, less predictable and unstructured, but individually can have a greater impact on the organization. These types of decisions are typically made by knowledge workers who are often managers, and they involve iterative thinking, ad hoc analysis and, importantly, they require collaboration with others.

While operational decisions are supported by intelligent decision automation by embedding decision rules and workflow in applications, this report focuses on CDM platforms that are intended to improve and capture tactical and strategic decisions. It features a number of products that have integrated multiple pieces of a CDM platform and could be enhanced to enable a broader CDM vision. In addition to CDM vendors, we include examples of BI vendors that deliver collaboration and social capabilities for BI content to improve their support of collaboration on BI input in the decision-making process. We would characterize these initiatives as "collaborative BI." Many BI vendors already provide the capability for users to tag comments to a specific report, analysis or dashboard. Collaborative BI also includes, or ties to, social capabilities to find the right people, based on social profiles, to include in a discussion thread to comment on, rate and blog about a specific result, and then dynamically recommend additional analysis based on past user behavior and similar content. In collaborative BI, the focus is on the BI artifact, such as a performance measure or query result. In contrast, in CDM, the focus is on the decision itself and the process and collaboration around it. Tactical and strategic decision examples best supported by CDM include: Which vendor should we select? Should we change our pricing policy? What portfolio of investment options will optimize our return? Should we hire more employees? Should we enter a new market? Should we buy a company?

In addition to BI vendors, a few corporate performance management vendors are enhancing the quality and transparency of the planning process by adding to their platforms collaboration capabilities, value-based planning optimization tools and closed-loop monitoring of key performance indicators (KPIs) tied to a plan. We characterize these capabilities as "collaborative performance management" (PM) and include vendor Cogniti in this report as an example of a vendor that offers collaborative PM. In collaborative PM, the focus is on the decision around the planning process. Collaborative BI and PM capabilities provide pieces of what a broader CDM platform would enable and, therefore, could be steppingstones to broad and deep support for CDM initiatives within an organization.

This research is not exhaustive and, as such, does not aim to cover every software vendor delivering CDM functionality; rather, it includes well-known smaller firms delivering this functionality and some established BI platform vendors that have been promoting new capabilities for CDM, collaborative BI and collaborative PM. No single vendor delivers the complete requirements for a comprehensive CDM platform out of the box, but it is worth noting that technology is not the primary barrier to CDM. Most large IT organizations could customize a social software environment with some basic templates for decision making that visually depict a decision, options, pros/cons and tags to relevant information. The real challenge to CDM adoption is cultural. CDM tends to be adopted by more progressive companies that view and value fact-based decision making as a core competency and critical to their success. For the most part, initial adoption has been within workgroups or lines of business around specific business-process-centric decisions, such as vendor selection, planning and forecasting, resource allocation optimizations and new product planning.

Figure 1 shows the high-level requirements of a comprehensive CDM platform within the context of a typical decision-making process.

BPM = business process management
CDM = collaborative decision making
SWOT = strength, weakness, opportunity and threat

Source: Gartner (September 2011)

CDM Vendors (in Alphabetical Order)

The following sections provide an overview of well-known firms delivering this functionality and some established BI platform vendors that have been promoting new capabilities for CDM, collaborative BI and collaborative PM. Each vendor section includes a table assessing key CDM criteria. Note 1 provides a description of each criterion.

Decision Lens (CDM)

Decision Lens, also highlighted in Gartner's "Cool Vendors in Analytics, BI and Performance Management, 2010," is a multicriteria CDM platform for optimizing strategic decision making. It is used by organizations including the U.S. Joint Chiefs of Staff, Kraft Foods, Johnson & Johnson, Oakland Athletics, Lockheed Martin, the U.S. intelligence community and Amtrak to make critical decisions.

Decision Lens provides a decision methodology, framework and platform that enable a group of diverse stakeholders and decision influencers to collaborate to structure a decision process, establish decision criteria and weights, and capture and blend the personal preferences and opinions of decision makers with fact-based data to build consensus. After supporting fact-based iteration and collaboration on all decision inputs, the Decision Lens platform applies resource optimization algorithms to optimize the resulting decision for net present value, risk variables or any other harder-to-quantify goals or benefits. Decision makers can explore each scenario using built in "what if" analysis capabilities. Decision Lens allows decision makers to assimilate and consider the qualitative and quantitative attributes of a decision. It does so by providing a method within the platform of combining the judgment of people with data to create a clear picture of which courses of action have the most value and highest likelihood of success. It is particularly useful when there are multiple stakeholders in a decision where there are many competing objectives to trade off and there is a need to establish a set of priorities by which they will evaluate various alternatives for prioritization. The Decision Lens platform has been successfully used by its customers across a variety of industries and collaborative decision types, including resource allocation, portfolio optimization, vendor selection and, in the case of professional sports, player selection decisions.

For example, in the U.S., the Military Health System (MHS) — which provides healthcare to all Department of Defense service members, retirees and their families — lacked a coherent method for defining and prioritizing global capital facility investments linked to strategic goals and objectives encompassing a systemwide perspective across all service lines (for example, Army, Navy, Air Force, Marines). Before using Decision Lens, it was not uncommon for multiple service lines to have underutilized clinics in close proximity to one another. The MHS used Decision Lens to bring service line stakeholders together to identify capital requirements and objectively prioritize and optimize potential capital investments based on criteria established through collaboration, with workflow to incorporate an executive review and approval process. With ongoing use of the system, the MHS is able to respond to changes in the market using Decision Lens' sensitivity and scenario analysis and rapid portfolio reallocation capabilities. Figure 2 shows how users can define, rate and weight decision goals for alternatives and then view how each alternative stacks up after aggregate input is calculated. Table 1 shows how the Decision Lens platform maps to the CDM requirements defined in Note 1.

Source: Decision Lens

Source: Gartner (September 2011)

IBM: IBM Cognos BI V.10.1 (CDM and Collaborative BI)

IBM is delivering both CDM and collaborative BI capabilities to customers as part of IBM Cognos BI v.10.1. As Figure 3 shows, IBM Cognos BI v.10.1 ships with integrated IBM Connections social and collaboration software for collaborative discussions and actions concerning decisions. With this capability, users can engage in a collaborative discussion based on BI information or other information using built-in social software to initiate activities and decisions, engage others with relevant expertise, and post messages, files and links, and discuss or review others' opinions. Users can also create and reuse decision templates. For more complex or multistep strategic and tactical decisions, the platform enables users to create and contribute to workflows and approval chains. During the course of the decision process, the platform captures decision history to track accountability and build future best practices, which users can access using integrated search capabilities.

Source: IBM

Figure 4 shows IBM Cognos BI v.10.1's collaborative BI features. Within IBM Cognos BI v.10.1, users can comment on BI information and share perspectives. Comments within IBM Cognos BI can be associated with either the overall table or chart, or associated with a specific cell value.

Source: IBM

As CDM is available as a feature within Cognos v.10.1, IBM doesn't have a stand-alone CDM product marketing team promoting and selling this product. Instead, it will be just another feature among many in Cognos 10. This raises a question mark over how serious IBM really is about CDM.

Table 2 shows how IBM meets the requirements for CDM as defined in Note 1.

Source: Gartner (September 2011)

Lyzasoft: Lyza (CDM and Collaborative BI)

Gartner highlighted Lyzasoft in "Cool Vendors in BI and Performance Management, 2009" (Note: This document has been archived; some of its content may not reflect current conditions) because of its desktop data discovery platform featuring strong business user data mashup capabilities. Since then, Lyzasoft has delivered server-side capabilities for sharing BI content with larger user workgroups and has been one of the first BI vendors to add collaboration and social concepts to its platform, supporting both collaborative BI and more advanced CDM requirements. Lyza is a Web-based collaboration hub. Everyone in a workgroup can participate in the decision and intelligence process with the ability, for example, to search, comment, blog, rate, forward and bookmark analysis in the decision process. A user can link a collaboration and analytical stream to a decision or decision process, as Figure 5 shows, or can share and collaborate on BI content, such as a dashboard or report, as Figure 6 shows.

Lyza's customers include a railroad that is using the platform to bring together people from around the company, from many locations and many diverse departments (including power, crew, yards, marketing, services, loading, pickup/delivery, pricing and accounting). They are able to pool their information, expertise and problem-solving skills to create holistic ideas to decide on courses of action, including routes, replenishment strategies and train services to improve the railroad's performance for specific customers, routes and train types.

The technical support center of a financial services firm uses Lyza to integrate data from telephone, knowledge management and HR systems so that the team can share and discuss the observed case management resolution performance of various search techniques being used by agents. It can then decide on best practices to push out to all agents.

Table 3 shows how Lyza meets the requirements for CDM as defined in Note 1.

Source: Lyzasoft

Source: Lyzasoft

Source: Gartner (September 2011)

Microsoft: Microsoft SharePoint 2010 and Microsoft Project Server 2010 (CDM)

Microsoft SharePoint 2010 is a platform on which CDM applications can be built. One such application built by Microsoft is Microsoft Project Server 2010, which provides tools based on Microsoft SharePoint, to optimize portfolio management decisions. The Microsoft SharePoint 2010 platform includes the core capabilities — BI, collaboration and social software — needed to build collaborative decision-making solutions and is, therefore, well suited for use by partners and internal IT groups as a platform for building custom CDM solutions. Figure 7 shows how SharePoint 2010 could be used as a CDM platform. Decision makers can create team work spaces within SharePoint focused on a decision, activity or project. They can find the right colleagues, start video, voice or IM chats with them, and capture team discussions with threaded conversations. Users can share and collaborate on documents related to the activity or decision. Users can also generate reports from within SharePoint that link to the decision.

Table 4 shows how Microsoft SharePoint 2010 meets the requirements for a CDM platform as described in Note 1.

Source: Microsoft

Source: Gartner (September 2011)

Microsoft Project Server 2010 leverages the CDM features of SharePoint 2010 in addition to a built-in portfolio optimization engine to help analysts model various scenarios to identify the optimal project portfolio. Project Server 2010 brings together collaboration and structured execution and workflow capabilities to automate portfolio management decisions and processes. Figure 8 shows how a decision maker could use portfolio selection techniques and run what-if analyses inputting a variety of cost constraints in order to recommend project portfolios that deliver the maximum ROI and that align most effectively with the organization's business strategy. Project Server has out-of-the-box integration with Microsoft Dynamics enterprise applications.

Table 5 shows how Microsoft Project Server 2010 meets the requirements for a CDM platform as described in Note 1.

Source: Microsoft

Source: Gartner (September 2011)

Purus Technologies: DecisionSurface (CDM)

Purus Technologies' CDM platform, DecisionSurface, combines collaboration, social software and decision-making best practices to facilitate higher-quality decisions and capture information about them. DecisionSurface automatically links the experiences and skills of people to their contributions in previous decision projects, so that staff can be found based on their experiences, their relationships to historical projects and the nature of their collaborative relationships to each other.

DecisionSurface captures the documents and information used within the decision process or "activities." Purus extends information by adding the concept of a "precedent" or a DecisionAsset that brings the insights of previous experiences back for reuse. The Purus CDM platform provides tools to structure the decision process to facilitate "deliberation," a decision-making process and best practice approach based on research from the MIT Center for Collective Intelligence. In the deliberation process, business questions are broken down into the issues, then the ideas to resolve each of the issues, and finally the arguments for each of the ideas as a structure to drive the most efficient and effective discussion toward actionable business decisions. Figure 9 shows how this best practice decision-making approach is supported in DecisionSurface.

By capturing and organizing the details of these decisions and the context in which they were made, and storing them in an asset repository, the corporate experience and knowledge can grow. Purus' initial focus for DecisionSurface is on collaborations that start with a business question and result in a business decision. DecisionSurface is offered as an in-house solution or software as a service in the cloud.

Table 6 shows how DecisionSurface meets the requirements of a CDM platform as described in Note 1.

Source: Purus

Source: Gartner (September 2011)

SAP: SAP StreamWork (CDM)

SAP was the first megavendor to deliver a stand-alone purpose-built CDM platform. Within SAP StreamWork, a decision maker can find and select the best collaborators for a decision based on their profile and capture the entire decision process, including email discussions and other reference data. Basic workflow capabilities allow decision makers with different levels of authority to sign off on decisions made. SAP StreamWork integrates with SAP BusinessObjects BI OnDemand, so decision makers can upload spreadsheets, Crystal Reports and Crystal Dashboards, analyze data, and create and share visualizations. To assist with objective decision making, SAP StreamWork comes with polls, pro/con tables, ranking and mind maps, as well as weighted decision-making tools. SAP StreamWork is optimized for an SAP application environment, as it integrates within the process and workflow of SAP applications. Currently, this integration applies to SAP CRM, SAP BusinessObjects Strategy Management and SAP Product Lifecycle Management. Additional integrations are planned for SAP BusinessObjects Intelligence Platform, SAP Collaborative E-Care Management and SAP NetWeaver Enterprise Workspaces.

For example, a sales team within an SAP StreamWork customer connects with an outside consultant to help choose the best hardware configuration for an opportunity. The outside consultant can participate, but can't access confidential data. The sales manager can collaborate with the entire team through SAP CRM using feeds and updates, and can invite external consultants to join conversations in SAP StreamWork. Participants are notified automatically about updates by email, smartphone or RSS feed. Collaboration and discussion can be started and viewed directly in the context of the existing SAP CRM activity. External consultants can access relevant documents and comments securely in the cloud via SAP StreamWork. Access to confidential files and information is restricted to internal employees with direct access to SAP CRM. Teams use built-in tools in SAP StreamWork to brainstorm, compare hardware options, come to a consensus and choose the best strategy objectively. The entire discussion, with all relevant documents, is archived in SAP StreamWork for future reference. All "activities" show opportunity milestones and are collected in SAP CRM. An activity contains all ideas, documents and discussion. Confidential files and comments can be shared securely with staff outside the office and with external agencies. The entire decision-making process is archived in case the decision is challenged by management, and for reuse and the identification of best practices.

Figure 10 shows how a user can initiate a new decision, find decision makers and capture a collaboration thread. It also shows how users can access past decisions. Figure 11 shows the decision tools that are available within SAP StreamWork to support decisions. Table 7 shows how SAP StreamWork meets the requirements of a CDM platform as described in Note 1.

Source: SAP

Source: SAP

Source: Gartner (September 2011)

Collaborative BI and Collaborative PM Vendors (in Alphabetical Order)

Cogniti (Collaborative PM)

Cogniti provides a closed-loop collaborative PM platform that captures, optimizes and monitors strategic, operational and financial planning decisions and the execution of those plans. Specifically, it enables networked teams to collaborate on a plan, use scenario modeling to compare courses of action based on financial value, and then define and implement KPIs to continuously measure and manage the performance of resulting key strategic and operational initiatives. Figure 12 shows how Cogniti can be used to collaborate during the plan execution phase based on the monitoring of plan KPIs. Table 8 shows how Cogniti capabilities map to the requirements of a CDM platform as described in Note 1. This analysis shows that Cogniti is best characterized as a collaborative PM vendor.

Source: Cogniti

Source: Gartner (September 2011)

Panorama Software: Necto (Collaborative BI)

Panorama Necto is an example of a collaborative BI solution that facilitates interaction around BI content created in the Panorama Software BI platform. It also helps users streamline their analyses and learn from best practices through recommendations for additional BI content and analysis, based on other users' past behavior, as well as content similarity. Necto is included here not because it is a CDM platform — it is not — but because by including an example of collaborative BI, readers will have a concrete example of what it is, what it is not and the differences between collaborative BI and CDM, which are often confused in the market.

Figure 13 shows Necto's collaboration capabilities concerning BI content. The social bar on top shows the most relevant users for this particular data view. A user can "drag and drop" any other user and start a discussion with him or her on a grid, chart or a particular insight. All discussions and annotations are stored contextually inside the system for future reference and analysis. Necto can also guide BI users to the next best piece of analysis. Based on other people's actions and patterns, the system shows the user what other users viewed after a particular chart or dashboard — Necto refers to the BI work space as a "workboard" — using relevancy based on people's behavior. It also recommends to the user which workboards are similar in content (with relevancy based on data/content) to the one being viewed. This feature is similar to the way in which Amazon recommends items including books and helps narrow and speed a search with relevant information. The social aspects of Necto enable ad hoc groups with a common interest (for example, a product, a service, a geographical area) to become a social-insight-generating network concerning BI content across an enterprise.

Table 9 shows how Panorama Necto meets the requirements of a CDM platform as described in Note 1. This analysis shows that Panorama Necto is best described as having collaborative BI capabilities.

Source: Panorama Software

Source: Gartner (September 2011)

Appendix: Summary of Vendor Capabilities

Table 10 shows a summary of the CDM vendor capabilities assessed in this report.

Source: Gartner (September 2011)