Today’s business environment is filled buzzwords and acronyms such as CRM, ERP, DSS, BI, DW, OLAP, OLTP, Data Mining, etc.  Terms such as these to a degree have a unique meaning and purpose.  It is also surprising to what degree they are related.  This paper is based on an exploration of Six Sigma quality management and its place within the overall framework of  BI (Business Intelligence) as a process management tool, or even a Decision Support System.  To cover the relationship between these two topics it is important to gain a general understanding of each.

Business Intelligence
Historically, business decisions would often be made with a few back of the envelope calculations by someone with extensive experience in a specific business and industry.  However, in today’s business environment companies house vast amounts of historical, transactional and other types of data that do not readily allow for managers to make stand along business decisions based on personal experience only.  Business Intelligence(BI) is a concept which is all-encompassing to the tools, practices and concepts which provide decision makers to access information needed to make the best decisions possible.  Typical components of BI include: CRM, ERP, DSS, DW, OLAP, Data Mining etc.

“Business intelligence refers to the use of technology to collect and effectively use information to improve business effectiveness.  An ideal BI system gives an organization’s employees, partners, and suppliers easy access to the information they need to effectively do their jobs, and the ability to analyze and easily share this information with others.”
(Business Objects-Implementing a Business Intelligence Strategy taken from www.dmreview.com)
 

A typical outline for a Business Intelligence system is as follows:

1. Internal and external data collected by various functional departments (IT, Marketing, Finance, etc.)
2. Data is gathered into Operation Data Stores (ODS)
3. ODS data is “Cleaned and transformed” for inclusion into the Data Warehouse where it becomes available to the entire business.
4. Functional departments create Data Marts which are small databases which house data that they will utilize repeatedly.
5. Various analytical tools (ex. OLAP) are used to create useful information for decision makers.
6. Decisions are made based on information provided.
7. Implementation of decisions creates new data which is collected back at the beginning of the process.

Furthermore, Business Intelligence has redefined the way businesses navigate the waters of competition. Understanding how Business Intelligence is implemented in an organization creates an important foundation to comprehend the long, diverse reach it has within a business. The outline assists not only in visualizing the implementation of Business Intelligence, but also in the implications it might have for business decisions.  
In essence Decision Support Systems (DSS) are the key to Business Intelligence.  Where BI is the driving concept in the quest to make our businesses information driven, DSSs are the actual utilization of BI tools to make better decisions. 

The components of a DSS are as follows:

Utilization of these components allow the User to obtain relevant decision-making information by taking data from the Data Management System, perform analysis on the data utilizing business models in the Model Management system, view the analysis against business/industry expertise from the Knowledge engine and view the processed information through some sort of user interface.  The decision maker then has utilized the DSS to obtain potentially critical information needed for making business decisions.

Six Sigma
Six Sigma is an increasingly widespread movement in businesses to achieve a goal within business processes of 3.4 defects per million events or less. In this definition, an event can be anything from a single unit manufactured to every customer flown. One major stipulation in the approach is that all decisions are data-driven, removing the possibility of subjective human judgement and allowing for easily reproduceable results. (Link 1) (Link 2)
The roots of Six Sigma began with Carl Frederick Gauss who was the pioneer of the normal curve. In the 1920's, Walter Shewhart discovered that a process needs correction at three sigmas and above. Invented in 1986 by a Motorola employee named Bill Smith. Motorola sets Six Sigma goals by 1987. In 1991, the first Six Sigma Back Belts were recognized internally at Motorla. In 1992, other corporations begin to adopt Motorola's Six Sigma initiative, most notably GE. As of today, Six Sigma is recognized as a collection of metrics, numerous methodologies, and a "management system for driving business results." It is much, much more than a typical quality system such as TQM or ISO. (Link 1) (Link 2)
When people refer to Six Sigma, they are more than likely referring to the DMAIC methodology. (Link 1) The DMAIC focuses on the cold, hard facts to meet the financial requirements of the company implementing it.

(http://www.dynamicdiagrams.com/case_studies/cio_six_sigma.html)
One of the older Six Sigma methodolgoies is called Design for Six Sigma (DFSS). This methodology is vaguely defined and thus varies from implementation to implementation, depending on variables such as business type, industry, and culture. One of the most common approaches using DFSS is called DMADV, while other approaches that have some acceptance are IDOV and DCCDI. The main differences between these various DFSS approaches is the name and number of phases, but ultimately the tools they use are identical. (Link 2)
The use of Six Sigma in any type of process has "generated bottom-line results for all types of organizations in hundreds of cases." There are numerous examples of huge savings for corporations. In Motorola's implementation, they have estimated nearly $16 Billion in savings! (Link 1 ) Rough estimates indicate that Six Sigma Black Belts save $230,000 per project per year, with the ability to complete four to six of those projects annually. In fact, the best part of Six Sigma is that it's reliance on cold, hard facts allows for analysts to easily trace financial benefits directly back to the implementation of the project. (Link 2) 
Six Sigma within Business Intelligence
Because Six Sigma is in essence the practice of monitoring and improving business processes it is clearly a valuable component within the overall Business Intelligence framework.  More specifically, because Six Sigma drives management behavior and decision-making regarding business processes, it is a type of Decision Support System (DSS).  Within this framework, of BI and DSS, Six Sigma can give valuable input to business leaders.  As seen in the Business Intelligence diagram on the next page, Six Sigma process monitoring can and does take place in every interface listed:
Analysis – Process analysis, often called Statistical Process Control (SPC) is at the heart of the Six Sigma program for quality
Report – Six Sigma tools such as control charts (X-bar and r, etc.) are important business reporting tools.
Scorecard – The Six Sigma components of control limits and defects per million opportunities provide businesses with a powerful quality scorecard.
Alerts – The Six Sigma process is designed to alert the business when a business process begins to fluctuate or become “out of control”.
Query – Although queries are not always required to monitor a process, they can be used to get data to be included in Six Sigma process evaluation.
Dashboard -  One of the most valuable tools under the Business Intelligence umbrella is the dashboard.  Dashboards provide managers with quick, easy to read high level information about an organization.  Quality indicators, as metrics within the Six Sigma process are often well represented in management dashboards. 
  

(http://www.cognos.com/cognos8businessintelligence/all-all-all.html)
Summary
Despite the many signficant improvements that Six Sigma can bring to an organization, components of Six Sigma can be improved upon to deliver even better results. Implementation of advanced Business Intelligence tools within a Six Sigma organization should provide a quick Return on Investment in the form of more effective preparation for Six Sigma projects, faster implementations, and increased long-term success of Six Sigma initiatives within the organization.