Top 10 Trends in Business Intelligence, Part 1

What Do They Mean to the Energy Industry?

Published: 8 August 2006

What are the implications of the top 10 BI trends for the energy sector?

 

Earlier this year, Knightsbridge Solutions published its annual Top 10 Trends in Business Intelligence white paper. It summarizes the most relevant trends that are shaping how large organizations are approaching business intelligence (BI) this year and beyond.

It’s hard to ignore the momentum in this field. This year, Gartner ranked business intelligence as the highest technology priority among CIOs. Last year, surveys performed by Merrill Lynch and Forrester returned similar results; Forrester placed business intelligence in the top spot for planned application purchases, and Merrill Lynch claimed BI retained a consistent place in the top three spending priorities as compared to the previous year. And, Energy Insights identified BI as the number one IT investment for energy companies in 2006. 

 

The good news is that, in general, companies appear to be making solid progress with business intelligence, and energy companies understand the business value that BI can deliver. Clearly, the value and importance of improving quality and accessibility of enterprise data is more widely appreciated at the executive level. While companies are becoming more mature in their BI capabilities and approaches, much work remains to unleash the full potential of their data. Let’s explore the implications of the first five trends for energy companies.  

Trend #1: Information quality 
For energy companies, vast amounts of business value can be unlocked if information can be trusted as accurate. Reconciliation efforts between operational and financial areas of the business consume tremendous resources from energy organizations. Information quality issues exist across all segments of the industry, from upstream exploration and production through downstream refining and marketing, as well as utilities, pipeline companies and chemical manufacturers. In the upstream space, a legacy of mergers and acquisitions continues to cause data quality and consistency issues due to the diverse systems and business processes that have yet to be integrated. Energy traders see mismatches in how their forward trading systems and their back office systems manage data, causing constant unpredicted shifts in volumetric and P&L positions. 

More organizations than ever are reaching the conclusion that information quality is ground zero for solving many of their most pressing business problems. Why is this? Because poor information quality impairs decision making and promotes inefficiency, organizations are also realizing that to achieve improved information quality, traditional data cleansing and profiling need to be supplemented with data governance, master data management, meta data management, data certification and auditability, and data protection. Consequently, information quality cannot simply be viewed as a project, but needs to be viewed as a way of life. This entails organizational and process change. In addition, measurement and verification are needed to ensure the information quality program is reaching its objective. 

Trend #2: Master data management 
Enthusiasm for master data management (MDM) has exploded over this past year, and IDC has predicted that the MDM market will grow at a compound annual rate of almost 14 percent over the next five years. Master data is data that describes an organization’s key business entities, such as customers, products and vendors, with the goal of ensuring semantic consistency across organizational and business process lines and simplifying process and data integration. 

Energy companies rely on consistency of information. Whether it’s global well identification in upstream or counterparty and commodity hierarchies for trading purposes, a common nomenclature across an organization can provide tremendous benefits. 

Energy companies rely on critical data about their physical assets, wells, fields, partners, commodities, counterparties, locations and even their own organizational structure, so they can stay competitive. Unfortunately, this critical data is typically managed by very disparate, redundant, and often external information systems. Adding to this problem, most major energy companies are global operations, and have grown through numerous mergers and acquisitions. This leads to the exponential compounding of disintegrated and redundant data. Neglecting a solution to address the increase in complexity and redundancy of critical enterprise data can result in significant impacts across the value chain.  

When getting started, energy companies must keep in mind that master data is not as much about technology as it is about securing business-side involvement and ownership in the process. Furthermore, master data is not a one-time project, but rather an ongoing program. Phased delivery builds momentum, and addressing priority projects first results in immediate and tangible benefits.  

Trend #3: Data governance 
Data governance is the business function that provides a strategic direction for information quality efforts, sets standards and processes, and ensures that information quality goals are achieved. The six key dimensions of an effective data governance program include: policy and planning, organization, standards, processes and methods, monitoring, and communication. Without an effective data governance function, lasting information quality efforts are likely to fail.

Many organizations still view enterprise information management as a technology solution involving data warehouses, data migration and transformation with ETL software, and data presentation via BI software. While these technologies are typically part of the overall information management solution, the solution will not succeed without overarching organizational changes including how information and data is to be governed. The bottom line is that both business and IT must be represented. The business is best suited to own and manage the organization’s data, and representation across business units and divisions must be fair to deal with political dynamics. It may be useful to use a third party to objectively mediate discussions and keep the organization focused on the larger information quality goal.

Given the commonality in data across diverse business units that make up today’s global energy companies, designing and implementing a sound governance model is not an easy task – but it is absolutely a prerequisite to successful enterprise information management.

Trend #4: Enterprise-level BI 
For many organizations, the desire for enterprise-level BI continues to be driven by the ever-increasing need for an integrated view of data from many disparate sources. Fueling this need to integrate data are the growing demands for regulatory compliance, increasing mergers and acquisition activities as the economy continues to improve, and an increasing desire among executives to monitor and analyze performance at the global enterprise level. Achieving enterprise-level BI requires significant process and organizational changes, as well as a solid enterprise-level BI strategy and architecture that address the goals and objectives of both the business and IT. 

While many large global energy companies have a need and a growing desire to address enterprise-level business intelligence, and a number are beginning to lay out the necessary vision and strategy, relatively few have made real headway in tackling enterprise BI. The problem is that most energy companies struggle in selling the need for enterprise business intelligence at a high enough level of sponsorship within the organization to garner appropriate funding and resource planning. In these situations, it would behoove internal champions of enterprise-level BI to focus on developing very compelling business cases that can be presented at the CEO and CFO level to gain appropriate sponsorship. Fortunately, energy companies now understand that BI is not just another project, but involves investments and programs over time to build competencies and establish requisite organizational structure and process to sustain the gains. 

Trend #5: Regulatory compliance 
More companies are looking to business intelligence solutions as a means to help address regulatory compliance issues on an enterprise basis. A comprehensive regulatory compliance program needs to address deeper business and technology issues, including information quality and data integration problems. As a result, a great opportunity exists to leverage investments in BI solutions to support regulatory compliance programs.  

With Sarbanes-Oxley and other mandated regulations from agencies such as the Financial Services Authority, Environmental Protection Agency, the Federal Energy and Regulatory Commission, and the Commodities Futures Trading Commission, energy companies are recognizing the need for comprehensive BI and data warehouse programs to help them meet these stringent requirements, while avoiding costly penalties, negative media attention and executive scandal.

In summary, these trends indicate a greater awareness and appreciation of BI throughout energy organizations at all levels. Due to the incremental realized benefits and risk mitigation these solutions can deliver, even executives in the boardroom are getting behind the prevalent initiatives -- information quality and enterprise-level BI. Indeed, the signs are there that BI is maturing, as more and more companies are investing in BI solutions and the principles, approaches and methodologies that make them successful.

 For the entire white paper on the top 10 trends, please visit http://www.knightsbridge.com/. 

Look for next month’s article that highlights the remaining 2006 BI trends as they apply to the energy industry.