Thursday, February 12, 2009

Predicts 2009: Business Intelligence and Performance

Predicts 2009: Business Intelligence and Performance
Management Will Deliver Greater Business Value

18 December 2008

Kurt Schlegel, Mark A. Beyer, Bill Hostmann, Rita L. Sallam, Bill Gassman, Nigel Rayner, Neil McMurchy, Neil Chandler, Matthew W. Cain

Gartner RAS Core Research Note G00163547

This year's business intelligence and performance management predictions describe how this space will evolve beyond a focus on technology to delivering greater business value from both existing capabilities and innovations coming into the market.


Gartner's five predictions in business intelligence (BI) and performance management reveal both the challenges and opportunities that IT leaders will have to deal with. We also look back at two predictions we made in the past — one we got right, one we got wrong — to give a sense of how this space has changed and what has not changed.

Key Findings
  • Packaged analytic applications delivered as both on premises software and software as a service (SaaS) will push control of the information used for decision making toward business units and away from IT organizations.
  • The economic crisis will reveal which enterprises have a sound information infrastructure and which do not.
  • The application of social software to the collaborative decision making process will demonstrate the business value of the information coming from BI systems by directly tying it to decisions made.
  • IT leaders in Type A enterprises that want to link analytics with business processes should consider large-grained mashups as a means of inserting analytics into existing applications.
  • Avoid a rigid adherence to standards defined by the IT organization, but prevent the business's increased control over packaged analytic applications from creating new BI silos.
  • The current economic crisis shows the importance of trust and transparency in the information that organizations use to run their business. Integrate the analytical insights derived from this information into the decision-making processes throughout the company.

Table of Contents


Strategic Planning Assumptions
A Look Back: Predictions From Previous Years


Enterprises will expect IT leaders in charge of BI and performance management initiatives to help transform and significantly improve their business. This year's predictions focus on the need for BI and performance management to deliver business value. Predictions range from the impact of business units exerting greater control over analytic applications to the impact of the economic crisis and how it will force a renewed focus on information trust and transparency to innovations such as collaborative decision making and trusted data providers that will significantly increase the value derived from BI investments.

SPA: By 2012, business units will control at least 40% of the total budget for BI.

Analysis by: Neil Chandler, Bill Gassman, Nigel Rayner

Key Findings: Discussions with business users indicate that they have lost confidence in the ability of the IT organization to deliver the information they need to make decisions. The IT organization excels at building BI infrastructure but struggles to understand the business enough to support it with the right information.

Market Implications: Business units drive analysis and performance management initiatives today. They mainly use spreadsheets that create dashboards full of metrics, and are turning to analytic applications and packaged business applications to automate the process. BI vendors already offer packaged analytic applications targeting specific functions, such as finance or marketing but are often not the choice of business users. As a result, business units will increase spending on packaged analytic applications, including corporate performance management (CPM), online marketing analytics and predictive analytics that optimize processes, not just report on them. By making these purchases outside of the influence of the IT organization, business units risk creating silos of applications and information, which will limit cross-function analysis. This adds complexity and delay to corporate planning and execution of changes.


  • Do not try to obstruct the business units but encourage them to use existing assets where possible.
  • Work with the business to create standards for purchasing classes of packaged analytic applications that minimizes the impact of isolated functions.
  • Show how performance management efforts will benefit the enterprise if metrics and reporting align to corporate goals.
  • Persuade departments to link to information management initiatives, performance management requirements and applications outside their own so that other departments can benefit from their data and analysis.

Related Research:

  • "The Impact of Recent CPM Trends on the Business Intelligence Market"

SPA: Through 2012, more than 35% of the top 5,000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets.

Analysis by: Bill Hostmann

Key Findings: The economic downturn forces every enterprise to stay abreast of dramatic changes in their business and to re-think their strategies and operating plans. In addition, the global financial crisis leads business stakeholders and governments to demand greater transparency about company finances, operations, decisions and core performance metrics. However, most organizations find they do not have the information, processes and tools needed by their managers to make informed, responsive decisions. Too many enterprises underinvest in their information infrastructure and business users tools.

Market Implications: Economics and regulators will mandate better information to detect change, make better decisions and communicate the changes and decisions. The economic crisis will reveal which enterprises have the information and tools to support management decisions and which do not. For example, could your enterprise provide the management team with information regarding a major business or market change without a painful, stop-everything project? Can your enterprise anticipate which customers will cut back their business and adjust its approach to minimize the loss? These kinds of decisions require a wide range of internal and external information and analysis to support rapid risk analysis and contingency planning with business rules, formulas, quality controls, processes and skills.


  • IT leaders in enterprises with a strong culture of information-based management should create a task force to respond to the changing information and analysis needs of executives.
  • IT leaders in enterprises without such a culture should document the costs and challenges of adjusting to new conditions and propose a business case for investing in the information infrastructure, process and tools to support decision making.

Related Research:

  • "IT Leaders' Top Three Reasons to Invest in Information Infrastructure"
  • "Key Issues for an Information Infrastructure Project, 2008"

SPA: By 2010, 20% of organizations will have an industry-specific analytic application delivered via SaaS as a standard component of their BI portfolio.

Analysis by: Kurt Schlegel

Key Findings: Information aggregators such as Nielsen, Thomson Reuters and IMS Health will increasingly rely on multi-tenant SaaS to deliver industry-specific analytic applications built from the data they collect from numerous competitors within a given industry. SaaS ensures a consistent data model and code base. Business users will be able to subscribe to SaaS-based analytic applications that provide an array of reporting and analysis capabilities.

Market Implications: This trend has two implications. First, it will shift the balance of power in the $5-billion BI platform market. As SaaS infrastructure and BI capabilities will be easily commoditized, information aggregators will emerge as major powerbrokers. Companies will only share their data with aggregators that can guarantee its security and confidentiality. While hundreds of information aggregators offering SaaS analytic applications will emerge, a virtual monopoly will persist within each industry segment because of the high barrier to entry for other information aggregators. Moreover, information aggregators will hire industry-specific business analysts whose expertise and analytical models can be delivered at a fraction of the cost of hiring analysts internally. The monopoly on industry-specific data coupled with low-cost analytical expertise will sustain a highly profitable subscription service. SaaS analytic applications will not eliminate the need for on-premises BI and data warehouse architecture, but they will command a much higher share of customer spending. As a result, much of the competition among BI platform, data integration and data warehouse vendors will shift from winning deals with customers to winning the OEM business of the information aggregators.

Second, the emergence of these offerings makes industrywide BI possible. Today, most BI leaders struggle to eliminate departmental BI silos. They try to collect and integrate granular data to make it consistent across the enterprise. Information aggregators collect granular data from numerous competitors in the same industry and store that information in a SaaS data warehouse with a single data model. As a result, they can calculate industrywide performance measures consistently. For example, First American, CoreLogic’s LoanPerformance mortgage analytics unit, collects granular data from numerous banks, loads it into a data warehouse and provides it to customers as an analytic application via SaaS. Using this application, users not only can see their own metrics, such as percentage of their loan portfolio that is 60 days past due, but they can compare the metric to a consistently calculated industrywide benchmark. Industry-specific information aggregators delivering analytic applications via SaaS will significantly increase the level of information transparency in those industries.


  • This trend will produce an explosion of industry-specific analytic applications built on different infrastructures. IT leaders should work with business users to identify the information aggregators in their industry and plan to incorporate a manageable number into their BI portfolio.
  • Do not just treat them as stand-alone analytic applications (much as Web site analytics is treated today). Work with the information provider to ensure the information tapped by the SaaS analytic application can be integrated into your internal data warehouse.
  • Look at coarse-grained mashups as a means to integrate the SaaS analytic applications with enterprise applications.

Related Research:

  • "Emerging Technologies Could Prove Disruptive to the Business Intelligence Platform Market"
  • "Emerging Technologies Will Drive Self-Service Business Intelligence"

SPA: In 2009, collaborative decision making will emerge as a new product category that combines social software with BI Platform capabilities.

Analysis by: Kurt Schlegel, Rita Sallam, Matt Cain

Key Findings: 71% of respondents to Gartner's latest BI survey indicate that improving decision making is the top driver for BI investments. However, most BI strategies focus on information delivery not decision making. IT leaders face an overwhelming challenge in moving their company's culture away from "gut feel" and toward empirical, fact-based decision making. The emergence of social software such as Facebook, MySpace and Delicious presents an opportunity for savvy IT leaders to exploit the groundswell of interest in informal collaboration. Instead of promoting a formal, top-down decision making initiative, these IT leaders will tap people's natural inclination to use social software to collaborate and make decisions.

Market Implications: Using social software enables a collaborative approach to decision making where relevant parties can come together, discuss an issue, brainstorm options, evaluate their pros and cons and make a decision. IT leaders need to align this use of social software with their BI architecture. In particular, users can tag assumptions made in the decision making process to the BI framework. For example, in making a decision about how much to invest in marketing a new product, users can tag the assumptions they made about the future sales of that product to a key performance indicator (KPI) that measures product sales. The BI platform could then send alerts to the user when the KPI surpassed a threshold so that the user knows when an assumption made in the decision making process no longer holds true.

If collaborative decision making takes off, social network analysis can track who is making decisions in the organization and how. Social network analysis would show the value of BI by tying the dimensions and measures to decisions made in the company. It would also create a powerful archive that would enable a forensic approach to audit decisions to understand how decisions are made in the company.


  • Promote the use of social software to make decisions.
  • Tie the assumptions made in the collaborative decision making process to BI platform metadata.
  • Apply social network analysis and decision audits to understand how decisions are made in the company.

Related Research:

  • "Business Intelligence and Decision Making"
  • "Deliver Business Value With a BICC Focused on Decision Making"

SPA: By 2012, one-thirds of analytic applications applied to business processes will be delivered through large-grained application mashups.

Analysis by: Kurt Schlegel, Bill Gassman

Key Findings: Enterprises should not trust their megavendor to solve all their integration problems. Vendors move slowly to integrate the disparate code bases they have acquired. Reliance on one vendor also limits the ability to use best-of-breed capabilities and weakens the buyer's negotiating position. At the same time, business units do not care about grand visions for SOA, such as assembling composite applications by weaving together fine-grained services.

Market Implications: Business people do not want to invest in a major application integration effort or throw out the applications they have. Out-of-the-box integration of business process management and BI has not yet materialized. Large-grained (typically referred to as coarse-grained) application mashups provide a more cost-effective way to embed analytics into the business process without a major re-architecture of the applications. For example, SPSS Predictive Analytics can run predictive models to produce a score and combine that score with a business rule to recommend a course of action. These analytical capabilities overlay enterprise applications such as Siebel CRM without a major integration effort. Mashups and user-configurable widgets are catching on fast in the consumer world and will migrate to work with enterprise applications and data.


  • IT leaders in Type A enterprises (rapid adopters of technology) who want to link analytics with business processes should use large-grained mashups of existing operational and analytical applications. Today most use the portal to integrate operational and analytical applications, but portals simply put the operational and analytical views side by side. Large-grained mashups overlay analytical insights, such as queries, scores, calculations, metrics and graphs, onto the graphical user interface of the operational application.

Related Research:

  • "A Pragmatic Approach to Integrating BI Within Automated Human Workflows"
  • "Designing Proper Service Granularity for Service-Oriented Architecture"

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3.0 A Look Back: Predictions From Previous Years

In response to your requests, we have looked back at some past predictions to see what we got right and what we got wrong. The two predictions below are from "Predicts 2005: BI and Data Warehousing Face Business Pressures."

On Target: 2005 Prediction

By 2006, more than 30% of global 2000 companies and government agencies with cross-enterprise, strategic BI initiatives will have formed BI competency centers (BICC).

This prediction proved to be accurate, and the trend has continued to grow. Earlier in 2008, surveys conducted by Gartner at the North America and European BI Summits showed that 31% of the respondents have a BICC, and an additional 38% have plans to implement a BICC within 12 months. A BICC is a necessary precursor to moving from a tactical approach to BI to a more strategic view. It helps sustain the organization's interest and efforts around BI. Indeed most of the predictions in this note aim at delivering more business value from BI initiatives and making it seem less like an IT-centric reporting effort. Establishing a true BICC is the best way to achieve this objective.

Off Target: 2005 Prediction

In 2005, the vision of "information democracy" (information available broadly to employees, consultants, customers, suppliers and the public) will re-emerge as a driving force for BI.

For most organizations in 2008, let alone 2005, information democracy remains elusive. The cultural change required challenges most organizations, and the costs and complexity of deployment of current technology prohibit rapid progress. BI initiatives still aim at making information more broadly available, but three years later most organizations are far from achieving this objective.

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