The search for business intelligence
Anyone who tracks the evolution of information technology in our society might come to the conclusion that there is no limit to our need for information. This is an easy conclusion to make since the number and sophistication of our information systems appear to be growing at precipitous rate. We keep implementing new functionality to address specific business needs and requirements.
Anyone who tracks the evolution of information technology in our society might come to the conclusion that there is no limit to our need for information. This is an easy conclusion to make since the number and sophistication of our information systems appear to be growing at precipitous rate. We keep implementing new functionality to address specific business needs and requirements. But the results of our efforts are inevitably more and more data.
While our ability to control specific transactions and work flows through information technology continues to increase, how effective are we at making tactical decisions based on the mounds of data we collect? Information may be an asset, but in copious quantities it can literally choke the decision-making process. We might be impressed by the number of reports and inquires within our enterprise applications, but can we effectively use these tools? Despite all their underlying data, do our applications present the information we really need in a manner that we can effectively use in our decision-making processes?
Business intelligence (BI) is a collection of tools, applications, and technologies designed to address the issues raised by the above questions. Its basic value proposition is that it can help a company tap into key decision-making information that traditional reporting tools cannot provide or present in a manner that allows for immediate action. BI is a common topic in sales, marketing, and supply chain applications. Without knowing much about BI, it should be easy to image why it would be a hot topic in identifying customer buying trends or supplier performance. But is BI relevant in the CMMS/EAM world?
To answer this question, one first must have a basic understanding of BI from a conceptual level. This doesn't require an in-depth understanding of its technical architecture — only a rudimentary grasp of the basic components used to build BI solutions. From a very simplistic viewpoint, BI solutions can be broken down into three primary building blocks:
Analytical — These are tools and applications used to explore and analyze data from multiple perspectives. They are used to discover and publish trends inherent in data but not self-evident. They are typically referred to as online analytical processing (OLAP) software. Under the OLAP umbrella falls a whole host of tools and techniques used to statistically forecast, model, and analyze data.
OLAP doesn't necessarily mean BI. Some OLAP solutions are complex, requiring a sophisticated skill set to effectively use. But BI is a very user-centric concept. BI OLAP products provide graphical front-ends that allows users to visually slice-and-dice information innumerable ways. Their learning curve is significantly shorter than traditional OLAP tools.
Report writers and ad-hoc query tools — These are the most familiar part of the BI equation. They offer end users the ability to create and publish custom reports and inquiries. The ability to produce visually oriented results makes a report writer or query package BI-friendly. They also provide end users the ability to drill-down through these results. With a click of a mouse, a user can move from a high to lower-level display to successfully investigate underlying trends and structures.
Data storage — These solutions provide an infrastructure for the other two components. BI can consume a lot of data processing power. It can also cut across multiple applications tying together disparate data sources. Running BI analytical and reporting tools directly against production databases can significantly degrade performance and present significant integration challenges.
BI vendors provide a variety of tools to extract, transform, and load data into formats more suitable for BI analysis and reporting. Data marts are the usual end target for this process. Data marts are specialized databases designed to store information from multiple sources and optimized for the type of analytical processing inherent in BI solutions.
From a high level perspective these components may just seem a repackaging of existing IT tools. But most traditional reporting and analytical tools are static in nature providing information snapshots produced by a series of structured events. BI is a dynamic concept. Its delivery mechanisms are designed to deliver continuous information in near real time. BI solutions typically allow end-users to dynamically change the parameters used to drive its reports and inquiries. They also permit end-users to dynamically investigate the underlying trends inherent within any information display. Users can quickly move from a high to low levels of information in the quest to quickly answer key decision-making questions.
BI solutions don't necessarily incorporate all of these components and attributes. But they do share the common objective of providing the information needed to quickly make decisions. These aren't the typical operational questions that applications usually help address. They are decisions that organizations make to enhance their competitive position.
Given this viewpoint, BI does have relevance for maintenance management. Since its inception, CMMS/EAM software has provided mission-critical information to help maintenance departments increase the competitiveness of their companies. But CMMS/EAM packages have grown considerably in functions and features. Originally, maintenance organizations used them primarily to control operations. While the number of their reports and inquiries keep expanding, our ability to effectively sift through this mound of information is being overtaxed increasingly.
A CMMS/EAM can produce trend information needed by maintenance decision makers. It can summarize emergency outages, identify failure trends, gauge labor performance, measure vendor performance, and report on many other service indicators. But does it provide maintenance managers with ability to quickly view key performance indicators and measurements? Does it allow maintenance to look beneath the reported numbers to discover root causes and truly analyze trends? Is it proactive in its delivery mechanisms alerting maintenance about issues and problems as they happen?
Traditional CMMS/EAM reporting tools can't effectively answer these questions. Realizing this, most top-tier CMMS/EAM vendors now provide a BI solution set or path for their product line. Approaches vary, but they can be categorized as follows:
Alliances — Many top CMMS/EAM vendors partner with an established BI solution provider like Cogos (cognos.com), Brio Technology (brio.com) and Crystal Decisions (crystaldecisions.com). These alliances are typically more about marketing than technology sharing and integration. But a few joint references/case studies can provide a good indication about the real strength of the alliance.
Incorporate BI functionality — BI techniques can be directly incorporated into a CMMS/EAM package. Datastream's (datastream.net) MP5i has more than 20 pre-defined key performance indicators (KPIs) that provide end-users with BI views of asset, work order, inventory, purchasing, and project management data. MP5i also provides the ability to modify existing or create new KPIs. Mincom (mincom.com) is another EAM solution provider that supplements their products with integrated BI functionality. Look for more and more CMMS/EAM vendors to incorporate KPIs, digital dashboards, balanced scorecards, and other BI techniques into their packages.
Data marts — The structure of application databases is not well suited for BI solutions. BI is a data-crunching proposition that can cross multiple applications. EAM provider Indus International (indusinternational.com) addresses this issue through their Knowledge Warehouse, which provides the data extraction, transformation and storage tools needed to drive and distribute BI solutions. Cayenta (cayenta.com) is another EAM vendor that provides custom data warehousing and BI development services capable of supporting enterprise-centric BI solutions.
BI hasn't yet established a large footprint in the CMMS/EAM world. It is still an emerging concept. However, it certainly has relevance for any company seeking to maximize the value of information locked away in its CMMS/EAM database. Organizations still struggling to gain control of their basic maintenance operations will gain more return by devoting their energies elsewhere. But for certain companies integrating BI into their CMMS/EAM equation will pay considerable dividends.
|Search the online Automation Integrator Guide|
Case Study Database
Get more exposure for your case study by uploading it to the Control Engineering case study database, where end-users can identify relevant solutions and explore what the experts are doing to effectively implement a variety of technology and productivity related projects.
These case studies provide examples of how knowledgeable solution providers have used technology, processes and people to create effective and successful implementations in real-world situations. Case studies can be completed by filling out a simple online form where you can outline the project title, abstract, and full story in 1500 words or less; upload photos, videos and a logo.
Click here to visit the Case Study Database and upload your case study.