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Top 5 business intelligence trends and their impact on manufacturing

Companies are becoming more mature in their business intelligence capabilities, but there is still much work to be done to unleash the full potential of enterprise data.

This article originally appeared on the BeyeNETWORK

In January, Knightsbridge Solutions released the latest version of its annual “Top 10 Trends in Business Intelligence” white paper, updated for 2006. It summarizes the most relevant trends that are shaping how large organizations are approaching business intelligence (BI) this year and beyond. 

It is hard to ignore the momentum in the space. 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 business intelligence retained a consistent place in the top three spending priorities as compared to the previous year.  


The good news is that, in general, companies appear to be making good progress with business intelligence. With the vast amount of research on CIO interest in business intelligence, it is clear that 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, there still appears to be much work to do to unleash the full potential of their data. Let’s explore the implications of the first five trends for manufacturing companies.  

Trend #1: Information Quality
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? It is because poor information quality makes regulatory compliance difficult, impairs decision making and promotes inefficiency. Organizations are also realizing that to achieve improved information quality, traditional data cleansing and profiling needs to be supplemented with data governance, master data management, meta data management, data certification and auditability, and data protection. Accordingly, information quality cannot simply be viewed as a project, or even a program, but needs to be viewed as a way of life. This entails organizational and process change.  

For manufacturers, information quality issues exist throughout the supply chain. One reason for this is that manufacturers depend on data from suppliers, contract manufacturers, distributors, retailers and consumers in order to effectively and efficiently source raw materials, forecast demand, make and market their products. Very seldom will manufacturers have control over the quality and format of this external data. Through incremental improvements in data quality throughout the supply chain, however, manufacturers can realize significant performance improvements, including improved speed and efficiency of product manufacture, improved ability to perform demand analysis, improved channel partner effectiveness through timely and accurate product and pricing information, and improved customer satisfaction through timely and accurate customer information. 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% 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.

All manufacturing companies rely on critical data about their suppliers, partners, customers, products and even their competitors, so they can remain competitive. Unfortunately, this critical data is typically managed by very disparate, redundant and often external information systems. Adding to this problem, most major manufacturers have global operations, and they have grown through numerous mergers and acquisitions over the years. This then 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. These might include delays in time to market, reduced productivity, higher supply chain costs and decreased customer satisfaction.  

When beginning a master data management initiative, manufacturers 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 is 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 on effective data governance function, information quality efforts are unlikely to succeed.

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 helpful to use a third party to objectively mediate discussions and keep the organization focused on the larger information quality goal.

Given the dependence that manufacturers have on cooperation across the functional areas that comprise the value chain, as well as the global nature of most Fortune 500 manufacturers, 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
The desire for enterprise-level business intelligence for many organizations 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 merger/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 business intelligence requires significant process and organizational changes, as well as a solid enterprise-level business intelligence strategy and architecture that address the goals and objectives of both the business and IT.

While many large global manufacturers have a need and a growing desire to address enterprise-level business intelligence, and a number are beginning to develop the necessary vision and strategy, relatively few have made real headway in tackling enterprise business intelligence. The problem is that most manufacturers struggle in selling the need for enterprise business intelligence at the appropriate level within the organization to garner appropriate funding and resource planning. In these situations, it would behoove internal champions of enterprise-level business intelligence to focus on developing very compelling business cases that can be presented at the CEO and CFO level to gain appropriate sponsorship. Fortunately, manufacturers now understand that business intelligence 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 BI 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. Accordingly, a big opportunity exists to leverage investments in BI solutions to support regulatory compliance programs.

Manufacturing companies face a number of regulatory compliance issues, including Sarbanes-Oxley, Restriction of Hazardous Substances (RoHS), Title 49 CFR: Hazardous Materials Regulations, Title 40 CFR: Protection of Environment, and Waste from Electrical and Electronic Equipment (WEEE) Compliance, just to name a few. While regulatory compliance among manufacturers does not seem to be a driving force behind data warehouse and BI programs, in contrast to how it is for companies in other industries – particularly financial services and healthcare – there are still opportunities to leverage enterprise information initiatives to better support a company’s ability to comply with mandated regulations. After all, doing so can help manufacturers avoid costly penalties, negative media attention and even keep executives out of court.

Greater Awareness
In summary, these trends indicate a greater awareness and appreciation of business intelligence throughout organizations, including manufacturing companies, at all levels. Even executives in the boardroom are supporting the prevalent themes we’re seeing this year – information quality and enterprise-level business intelligence – due to the incremental realized benefits and risk mitigation these initiatives can deliver when using the right principles, approaches and methodologies. Indeed, the signs do indicate that business intelligence is maturing.

In my next article, I will address how the remaining five top BI trends identified in Knightsbridge’s white paper are playing out in the manufacturing sector. For the entire white paper on the top 10 trends, please visit

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