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BI Collaboration Best Practices:
BI Collaboration

online columnist John Onder     Column published in DMReview.com
April 15, 2005
  By John Onder

Editor's note: DM Review would like to welcome John Onder as the newest online columnist. He is a partner in Chicago Business Intelligence Group (CBIG) with extensive experience in providing information technology services, business reengineering, system assessment and planning services. He will write about BI Collaboration.

This is the first article in a series to explore the subject of Business Intelligence Collaboration (BI-C). We'll investigate and present methods, principles, the processes to build an effective program, examples of BI-C and some thoughts on the future of BI-C.

The concept BI-C is something that all organizations have done to some extent in implementing a business intelligence application. BI-C is the interaction and sharing of processes, technologies, people and knowledge. The concept of sharing of BI resources, experiences, technologies, methods and best practices as an integral part of a business operation is something all organizations have done, but typically in one-off discussions over the cubicle wall, in meetings or general discussions. Few organizations though have implemented a collaborative framework as part of their daily operations. With the business landscape changing, business models physically expanding through the use of outside services and offshore development, the complexity of BI applications increasing, and data volumes for BI skyrocketing, the need for an effective BI-C process is greater than ever, but the tools to support the need have lagged.

Throughout my career working in all types of business environments, I've seen examples where limitations and barriers exist on the ability to share information, designs, best practices, etc. These aren't political barriers, but physical and process barriers. Most firms just have not implemented a procedure to facilitate collaboration even though intrinsically everyone realizes the benefits are huge. When firms implement a collaborative business intelligence program, optimal integrated communication and decision-making occurs.

The first step is to recognize the key characteristics of an effective program:

  1. An organized and efficient process to share and communicate information.
  2. A flexible process to allow for various levels of use. Many different levels of participants (from analysts, developers, project managers to executive sponsors) will be involved in any BI project. Both a BI-C methodology and BI-C tools must be accessible by all.
  3. BI-C is intended to facilitate the sharing of ideas, knowledge and information to leverage IP, methods, people and technology, but it should also foster innovative and independent thinking by removing many of the common barriers to be able to innovate and be creative.

In short, a BI-C program should simply make the process of planning, building and implementing a BI application a low-risk, high-return experience by leveraging the collective know-how of the organization and extended BI community in an easy to use and accessible resource.

Benefits of BI Collaboration

It has been proven that an effective collaboration program can help an organization go beyond the traditional site- and/or team-specific constraints. Considering that most organizations have multiple different physical locations, even if just departmental on the same campus, this significantly limits the amount of interaction and sharing. Combine this with the fact that most organizations also have multiple, complex BI/DW applications in the planning, design or development stage, and you have a multi-layered problem. A BI-C program will help organizations bridge this collaboration gap and will give a BI development team the capability to accomplish more, at a faster rate of development and acceptance and at a lower overall cost to produce and own.

Implementing a BI Collaboration Program

It is a given that collaborative technologies and processes can be used to facilitate the design and implementation of business intelligence applications. But how do you make collaboration a reality when all the pieces are spread across the organization over many departments with their own priorities and agendas? Automation is the answer. The holy grail of collaboration is automating a common process workflow and knowledge repository and, for BI projects, integrating a BI specific methodology of best practices, deliverable templates/examples, plans, etc. is critical. We all know BI projects are a different breed. While most organizations have knowledge repositories, work plan repositories, methodologies and development processes, none are contained within the same integrated and automated platform. Collaboration can only work well when developers, analysts, project managers, program managers, strategic planners and business sponsors are all working with and using the same data, processes and information to plan, build and deploy BI applications. The capability to automate sharing and interaction is a necessity.

But to automate, you need first to know what must be automated and how all the various pieces work together.

There are four main domains of BI-C: process, technology, people and information (See Figure 1). Within each domain are many supporting sections of BI-C. And within each section are the details that define the domain. The Sections of BI-C as presented in this article are very broad in definition and also very deep, comprising all the attributes of a BI program.

Figure 1: Four Domains of Business Intelligence Collaboration

For BI-C to work well, all four domains must be utilized, interact and share with the three major phases of a BI project: planning, building and implementation. If you think about the problem, for example, when a project is in the planning stage, one would need to understand who within the organization has worked on similar projects (business solution, technologies, etc.), where a similar architecture been implemented (same type of reporting tools, same relative size of database) within the organization, ensure a consistent process is used so one can leverage best practices (methods, project management) and understand if a similar type of project has been performed, get access to the deliverables of the project (requirements documents, data models). As an example, if a P&L data mart in the snack foods brand division of a large food manufacturer is being developed in their Chicago location leverage the knowledge and collaborate with the people who implemented a P&L data mart in the frozen foods brand division of the same large food manufacturer with their offices located in St. Louis, the benefits are self-evident.

In future columns my colleagues at the Chicago Business Intelligence Group and I will dig into the details of each domain and section components, discuss other examples of BI-C and present our thoughts on how to implement BI-C in your organization.


For more information on related topics visit the following related portals...
Business Intelligence (BI) and Enterprise Information Portal (EIP).

John Onder, a partner in Chicago Business Intelligence Group (CBIG), has extensive experience in all facets of providing information technology services, business reengineering, system assessment and planning services. He has in-depth expertise in business planning and practical implementation of business intelligence and data warehouse applications across many industries. CBIG is a full service, vendor-independent DW/BI consultancy staffed by senior level professionals. Onder can be reached at john.onder@chicagobigroup.com or (773) 477-8783.

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