Agenda for Analytics, Business Intelligence and Performance Management, 2012

Transcription

1 Agenda for Analytics, Business Intelligence and Performance Management, 2012 Published: 7 March 2012 G Analyst(s): Neil Chandler Gartner's 2012 research agenda will help leaders of business intelligence, performance management and analytics initiatives create a strategy that improves business performance. Analysis Figure 1. Analytics, Business Intelligence and Performance Management Agenda Overview Source: Gartner (March 2012) Traditionally, business intelligence (BI), performance management (PM) and analytics addressed tactical needs, such as reporting monthly sales by product and region or tracking financial performance against target. The main challenges were collecting and collating data from diverse sources and getting users to adopt standard reporting tools chosen for them by the IT organization.

2 Today, senior management expects business analytics to provide a competitive advantage, such as by predicting sales under various scenarios or recommending next steps to improve financial performance. Therefore, business analytics leaders face challenges of a different order, including developing a proactive organization, addressing a growing number of use cases and providing a range of BI capabilities that better address the needs of users. Gartner's 2012 research agenda will help leaders plot a strategy for helping to grow and transform the business while continuing to meet tactical needs. For business analytics leaders, a combination of data warehouse and BI platforms no longer suffices: People: BI, PM and analytics have started to pervade work at all levels of the organization. Information: Enterprises must analyze many types of unstructured content and external information, not just structured data that the enterprise controls. Use cases: A growing number of analytic use cases require integrated infrastructure that accommodates a variety of application sources. Methods: Users need more sophisticated analytics, better presentation of results and tighter integration with the systems they work in. Three trends have forced this new reality on business analytics leaders. First, with today's economic turmoil, enterprises cannot count on steady growth as the normal environment. They need sophisticated planning and simulation tools to identify new business opportunities. Then they must track their performance more carefully against business metrics. Second, big data from sources such as operational technologies, social media, cloud services and mobile computing has drastically increased the volume of information to analyze. Information enters the enterprise at an accelerating rate. It comes in a wider variety of types (text, pictures, audio, video, maps, blogs, tags, links, activity streams, ratings, "likes," etc.). It must be validated to different levels of quality and context for a larger number of purposes. Third, business analytics technologies have matured while user expectations have increased. Packaged analytic applications offer capabilities, such as statistical regressions and forecasts, that enterprises used to have to custom-build. Demand is increasing for process- and domain-centric solutions from a growing number of providers. But enterprises still need leading-edge technologies. Users demand better performance and they don't want to switch from the application they're working in to find information and then switch back. Gartner's 2012 research will address all three trends. Key Issues How should organizations apply analytics to improve business processes and outcomes? How should organizations rearchitect their analytics, BI and performance management technology? Page 2 of 8 Gartner, Inc. G

3 What are the best practices to create an enterprise metrics framework? Which leadership and organizational competencies are required to use information and analysis to optimize decisions and manage performance? How should organizations apply analytics to improve business processes and outcomes? Business analytics will make a difference to business performance only if business and IT leaders implement these technologies as part of a comprehensive strategy. Gartner's business analytics framework shows all the components needed for such a strategy note that technology plays a relatively small role (see Figure 1). The framework embodies two key points. First, business analytics must align with the enterprise's business objectives and must affect the organization's performance in a measurable way. IT leaders must measure the success of business analytics in the same terms as enterprise performance is measured. Second, business analytics solutions should combine three components: people, processes and platform. Plans for BI, PM and analytics projects must take into account the needs of those who produce and consume information as well as IT staff that help deliver analytics. Business analytics should occur within the context of processes, and this context has at least three dimensions. IT leaders must help domain experts develop sound analytic processes to support the use of BI, PM and analytics tools. The information used by these tools and processes must adhere to quality standards created through a governance process. Finally, analytic tools and insights must become an organic part of decision processes so that users don't have to go outside their work environment to find the information they need. A business analytics platform must include a common information infrastructure that provides consistent capabilities, regardless of where the information comes from. And the platform must deliver a variety of analytic and decision support capabilities. Planned Research Gartner's 2012 research will continue to explore how clients can use the business analytics framework in their specific environments. We will present best practices for aligning BI, PM and analytics with business goals. We will talk about the various roles involved with business analytics, including business and analytics roles as well as IT roles. We will examine the various challenges to establishing processes for business analytics, particularly how to incorporate it into decision processes. We will discuss the functions users need by means of Gartner's information capabilities framework (see "Information Management in the 21st Century"). We will also expand our research on decision capabilities, such as social decision making and decision automation. And we will focus on advanced analytic capabilities, such as real-time and predictive functions, that can provide a competitive advantage. How should organizations rearchitect their analytics, BI and performance management technology? Over the years, most enterprises have accumulated numerous siloed business analytics applications. A strategic approach requires them to be rationalized into a coherent platform or Gartner, Inc. G Page 3 of 8

4 environment. Some enterprises have explored standardization on the environment of a software megavendor. However, such a standard will not work for most enterprises because: The components within a megavendor's stack have uneven levels of integration. New technologies will continually emerge from small vendors. Those technologies will often provide more of a competitive advantage than those available from the megavendor. No one vendor provides all the necessary components to support business analytics fully. Standardizing on a single vendor puts an enterprise in a terrible negotiating position. The business analytics team needs to rationalize the portfolio based on the specific capabilities and use cases the enterprise needs to integrate data from disparate data sources. Business analytics leaders will need an architectural approach that can deliver standards and a robust foundation without stifling differentiation and innovation. The number of use cases that business analytics must support will continue to multiply, and they will require multiple tools. IT leaders can address the dilemma of standards versus differentiation and innovation through pace layers the notion that some parts of the environment (such as infrastructure) should remain stable for long periods while other parts should change rapidly (tools that differentiate the enterprise). IT leaders can map their business analytics technologies to a pace layer architecture based on the "run, grow, transform" model. Technologies for running the business can be controlled and long-lasting; those for growing the business may change over the course of three to five years; and those for transforming the business can be designed to change once every year or two. Planned Research Gartner's 2012 research will focus on advice to help business analytics leaders rationalize their tools and create a coherent environment that provides basic common services while allowing for change and innovation. We will explore the various options for business analytics architecture (such as the Pace-Layered Application Strategy) and which enterprises will benefit from each. We will thoroughly explore technologies, products, vendors and markets. We will track the maturation of technologies and watch for the appearance of new technologies. We will assess the impact of product changes on clients. We will follow the plans of key business analytic vendors, and we will analyze how new business analytics trends and requirements affect the markets. What are the best practices to create an enterprise metrics framework? Companies need an enterprise metrics framework that aligns strategic goals with operational activities. Without such a framework, business processes cannot easily show how they deliver business value. Managers who try to improve processes can only guess what effect their decisions will have on enterprise performance; they cannot manage processes empirically. While most companies have dashboards centered on key performance indicators, they rarely have true metrics frameworks complete with a strategy map. Business analytics leaders cannot create an enterprise metrics framework on their own if the firm lacks one. They must collaborate with business and functional managers at all levels. IT leaders who Page 4 of 8 Gartner, Inc. G

5 are trying to lead the way toward an enterprise metrics framework will encounter challenges such as: Lack of understanding of the framework's importance Political and cultural sensitivities Difficulty defining metrics Issues over sponsorship Planned Research Gartner's 2012 research will provide recommendations and best practices to help clients who want to develop or improve an enterprise metrics framework. We will highlight the benefits of this, including case examples. We will analyze the challenges involved and show how to overcome them for example, by selling the idea of the framework to business leaders. Which leadership and organizational competencies are required to use information and analysis to optimize decisions and manage performance? The business analytics framework emphasizes that responsibility for BI, PM and analytics initiatives must extend beyond the IT organization to the business. A lack of business buy-in remains the biggest obstacle to a strategic approach for business analytics. All too often the IT organization assumes leadership of initiatives by default. IT leaders gather requirements from the business and implement tools only to discover that they go unused. To overcome this challenge, IT leaders must address the causes, which include: Business managers often not understanding how business analytics can provide strategic value and therefore not being motivated to engage with the effort. BI, PM and analytics projects not aiming at measurable business goals. The IT organization trying to force the standardization of business analytic tools. As a result, users make tactical, departmental purchases of their own tools. IT leaders not marketing their successes to the business side. Business leaders being given a sponsorship role as though they are only the customers of business analytics, not the leaders. Business analytic leaders therefore need to work closely with business users at all levels to ensure success. Consequently, the planning and execution of projects should occur within the framework of a business analytics team or BI competency center. The team should embody the shared responsibility for the success of business analytics. Thus, it should include business users, analysts, architects, IT staff and possibly finance staff. Unless the team incorporates business and analytic skills, BI, PM and analytics projects will not advance the business as much as they should. The business analytics team also becomes a forum for spreading best practices across the organization. Gartner, Inc. G Page 5 of 8

6 The team needs to strike a balance between centralized control over business analytics and freedom for local departments to innovate and design projects that meet their specific needs. Planned Research Gartner's 2012 research will focus on the skills that business analytics leaders need to succeed with a strategic approach. We will recommend best practices for engaging with the business. We will share case examples from enterprises whose business analytics programs have succeeded in achieving their business goals. We will continue to expand on the staffing and best practices for operating a business analytics team. We will show the expanded role that the team must play to execute a business analytics strategy. Related Priorities Gartner's Key Initiatives address significant business opportunities and threats, and typically have defined objectives, substantial financial implications, and high organizational visibility. They are typically implemented by a designated team with clear roles, responsibilities and defined performance objectives. Table 1 shows Key Initiatives related to the business analytics agenda. Table 1. Key Initiatives for Business Analytics Key Initiative Analytics Business Intelligence and Performance Management Information Governance and MDM Programs Advancing Data Management Maturity Content, Collaboration and Social Initiatives Information Infrastructure and Big Data Projects Focus Gartner will focus on three analytical styles: predictive, real-time and content. Investments in these areas will yield insights to optimize various business domains. Business intelligence and performance management initiatives help enterprises align their organizations with consistent and insightful measurement and decision support systems. Information governance programs like master data management (MDM) are key to efforts to gain value from information reuse across an organization, and are central to enterprise information management. Data management consists of the practices, architectures and tools for enhancing the specification, management and accessibility of information assets across the organization. Content, collaboration and social capabilities enable people to find and manage the right content and to work together effectively. Information infrastructure is a set of technology capabilities to support information management goals. The term "big data" refers to information of extreme size, diversity, complexity and the need for rapid processing. Source: Gartner (March 2012) Page 6 of 8 Gartner, Inc. G

7 Recommended Reading Some documents may not be available as part of your current Gartner subscription. "Gartner's Business Analytics Framework" "Strategic Road Map for Analytics" "Eight Steps to Foster the Creation of a Business Intelligence Competency Center" "How Your Measurement Maturity Could Be Stalling Business Performance" "Hype Cycle for Performance Management, 2011" "Magic Quadrant for Business Intelligence Platforms" "Applying Gartner's Pace Layer Model to Business Analytics" Gartner, Inc. G Page 7 of 8

8 GARTNER HEADQUARTERS Corporate Headquarters 56 Top Gallant Road Stamford, CT USA Regional Headquarters AUSTRALIA BRAZIL JAPAN UNITED KINGDOM For a complete list of worldwide locations, visit Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. or its affiliates. This publication may not be reproduced or distributed in any form without Gartner s prior written permission. The information contained in this publication has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information and shall have no liability for errors, omissions or inadequacies in such information. This publication consists of the opinions of Gartner s research organization and should not be construed as statements of fact. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see Guiding Principles on Independence and Objectivity on its website, ombudsman/omb_guide2.jsp. Page 8 of 8 Gartner, Inc. G