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BI Strategy:
Making the Right Strategic Choice: Determining Which Analytics Capabilities Fit Your Needs

online columnist Rich Cohen     Column published in DMReview.com
February 9, 2006
 
  By Rich Cohen

There is a child in all of us who wants the latest and greatest toy on the market. You know the one; it has all the bells and whistles and can do really nifty things. You need it! You really do - at least that's what your inner child says. But do you?

This month I would like to discuss how to determine - based on what information you need and the way you use that information - the analytic tools and technologies that are the most appropriate fit for your specific needs. You may truly require the hottest tools on the market - the ones with all the power. But then again, you may not. Hopefully, by the time you reach the end of this column, you'll have a better idea of how to come up with the answer.

No matter how small, every company needs access to some type of business intelligence (BI) information. BI solutions can include:

  • Transaction processing systems that give you hindsight - they tell you what has happened with the company.
  • Data marts and data warehouses that give you foresight into what might happen and insight as to what's really driving business results.
  • Executive information systems (EIS) to give management a 360-degree view of the issues facing your company.

Many companies have a mix of these technologies. An ever-growing number of companies also employ advanced technologies, such as neural networks and data mining, to support the insight needs of the company. The trick is to figure out which mix of these BI solutions fits your needs.

Which technologies you need - and in what combination - will largely be determined by your information needs environment. In other words, what you need is determined by what you want to know. Let's start by reviewing some BI basics - what technologies are available and what they do. Figure 1 depicts the different types of information and analysis capabilities that companies might require according to their information needs environment.

Figure 1: Information Analysis Capabilities

The most basic type of BI capability is transaction processing technology that records everyday activities of the company in the form of straightforward, after-the-fact reporting. The information is often highly summarized, and the reports are usually standard, rather than ad hoc.

Online analytical processing (OLAP) technologies are the next step up. These tools deal with aggregated, tactical information. Typical OLAP tools enable drill down, drill up, "what if" analysis, ad hoc reporting, pivoting and other activities on data for relatively sophisticated data analysis.

Next up on the sophistication scale are the executive information systems (EISs). These systems facilitate one-stop shopping, exception-based analysis of strategic information. The functional core of sophisticated EIS technology is the use of alert-driven environments that include key performance indicators (KPIs), scorecards, executive dashboards, electronic briefing books, command centers, etc.

On the extreme end of the analytic scale are technologies that employ statistics-based (e.g., association, regression, etc.) or artificial intelligence (e.g., neural networks) capabilities. These tools use powerful analytic algorithms to enable very sophisticated what-if and scenario analysis, and they can reveal less-than-obvious patterns or similarities in transactions or events.

As I mentioned previously, you'll likely need a hybrid combination of technologies to meet your analysis and reporting needs. Therefore, it's critical to examine that environment before you make a decision that could be technically elegant and expensive but doesn't meet your needs.

To determine what your information-needs environment looks like, it is a good idea to conduct an information needs assessment. This assessment consists of an analysis of current and future information needs, analysis needs, and budget constraints you're likely to face when making your technology choices.

To assess your current and future information needs you will need to examine your business process and data models along with your reporting structures. You will also want to look at how information flows within your company and to conduct interviews with leaders and knowledge workers in critical business functions to get frontline input about their information needs. Finally, it's critical to consider growth plans and other anticipated changes in your company that could have an impact your information needs.

To assess your analysis needs, you will want to determine what type of questions you routinely ask about your company. For example, if you mostly need to report on transactional information, your company's analysis needs may not be as involved as those of a company that considers it critical to perform complex "what if" analysis, scenario modeling, and real-time, exception-based performance monitoring and alerting. Whatever your analysis needs, however, it's critical to look at both the present and the future when making the determination.

Analysis of spending constraints is fairly straightforward. You determine, based on your information and analytical needs, which technology combination effectively fits your needs and your budget. Compromise is inevitable. It is imperative, however, that you prioritize correctly and spend the most dollars on the most critical needs.

Regardless of which analytics technology mix you ultimately determine fits your needs, there are a few leading practices that you should follow to help you leverage the most value from your technology choice. At a minimum, you should:

  • Align the technology mix with your overall corporate strategy. This alignment will help you make technology decisions based on your needs and your company's strategic direction.
  • Integrate BI capabilities across data sources. This integration will help enable you to reduce or virtually eliminate manual efforts to produce desired results.
  • Maintain consistency in KPI definitions across BI technology implementations. This consistency will further reduce the need for manual reconciliations and variance explanations.
  • Create role-based metrics and rollups to maintain consistency as the data is aggregated, summarized and analyzed. This increases the likelihood that you will get consistent answers to questions, no matter which system you query.
  • Choose a technology mix that is scalable. Your technology must be able to keep up with your information requirements as your business grows and your analysis needs change.

Ultimately, the challenge in meeting your information needs is choosing the appropriate technology mix. The key to effectively meeting that challenge lies in thoroughly examining your needs, understanding which technologies could best meet those needs and confirming that you follow leading practices when implementing the technology mix you have chosen. After that, it is simply a matter of acting on all that good information you are bound to get!

 

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For more information on related topics visit the following related portals...
Analytics and Business Intelligence (BI).

Rich Cohen is a principal in Deloitte Consulting LLP's Information Dynamics practice where he is responsible for the strategy, development and implementation of data governance, data warehousing, decision support and data mining engagements to support the emergence of world-class business intelligence applications. Cohen has more than 27 years of experience in the design, development, implementation and support of information technology in a variety of industries. Over the last 18 years, he has had extensive experience in the creation of technology strategies, implementations and deployment of CRM and business intelligence solutions to drive improved business performance.



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