BI IN PRACTICE

CONTACT

	cepe@sisorg.com.mx
	México: 01 (55) 5256.4517 Monterrey: 01 (81) 8347.0027 Austin: 713 96 22 003
	México, D.F. Tamaulipas No. 150 Despacho 501 5°piso Torre A Col. Hipódormo Condesa. C.P.06100 Monterrey, N.L. Calle IV No. 1214 Fracc. San Jerónimo C.P. 64640 Austin, TX 3925 W Braker Lane, Suite 3.8096 Austin, TX 78759

HOW TO IMPLEMENT A SUCCESSFUL BI

A Business Intelligence Project has multiple angles that must be taken into account from the start of the implementation initiative.

From our perspective, and throughout our 15 years experience with this kind of projects, we have found there are six main critical factors that must be taken into account and monitored closely when starting a Business Intelligence initiative. These critical factors are:

• Business Requirements: The first group of factors aims at defining what the goal of the project is as well as all the elements of information needed as deliverables of the project which will support more effectively the decision-making process.
  
  Likewise, the way in which we will measure the impact of said information elements in the company results is of critical importance. As with any technology project, the investment in a Business Intelligence initiative must deliver a return on said investment, and it is critical to clearly establish from the start, where the project will make an impact, and as a result, where the return of investment will be.



• Methodology: It is critical to understand that a Business Intelligence Project is different from the development of transactional systems. It is very important to select a development methodology focused on Business Intelligence. This is because this kind of initiative requires that we pay attention to points that are irrelevant or that are approached differently for the development of transactional systems.
  
  The methodology should guide us throughout the whole life cycle of the project. Likewise, it should give us support in the moment the project becomes a process, and should lead the execution effort of said process as well as its performance measurement.



• Architecture: Once the business requirements have been defined and the way the return of investment will be measured is clear (the way we will measure the impact of information on the decision-making process), it is critical to define the architecture paradigm that best supports the generation of results we expect.
  
  The architecture paradigm can go from processing data by lots to real time, and from cubes analysis to the proactive delivery of information. The right choice of architecture is far from being a trivial process and requires large amounts of time and analysis since it represents perhaps, one of the critical-factor groups with the highest impact on the project in terms of time.



• Technology: Once the information deliverables as well as the data architecture we will use have been defined, it is time to choose the technology we will use to start operating each one of the components of the selected architecture. It must be effective enough in its price in order to satisfy the budget requirements, investment capacity and risk, and robust enough as to deliver the expected results of the project.
  
  For the selection process we must follow a strict evaluation process that will allow us to put in perspective the different possibilities so that, when it is time to make a choice, we take into consideration all the specific factors of our own BI initiative. We must remember that all BI initiatives are different, and so the measurement criteria used with one or another may not necessarily be entirely comparable.



• Data Quality: "Data Quality" is generally an underestimated bracket for this kind of project. Generally what ends up happening for these initiatives is that the quality of the data ends up becoming an additional component the BI initiative must bear in mind, which, if it were a trivial aspect, truly becomes a break point between the success or failure of the project.
  
  What happens is that, by not having a budget with quality data for the project, the BI initiative absorbs the issue within the original budget, which little by little starts affecting the efforts to achieve results, until we get to the point where the issue becomes so overwhelming that it ends up deteriorating the initiative by not being able to justify the investment on the quality of the data when the justification that investors expect is related with a better support to the decision-making process.



• Economies of Scale: The last Group of success factors has to do with the search for economies of scale throughout the project and throughout other company initiatives. The chosen technology can generally be used to satisfy other requirements. For example, the data collection layer of the system is in fact a data integration engine that may as well be used to substitute point by point interfaces.
  
  It is critical to understand the operation of all the technological components of the project and make full use of creativity in order to increase their applicability in the business so that we can boost the return of the investment on these components, as well as increase the economy of scale and improve the total cost of ownership.

As we mentioned before, this is only a summary of what we consider to be more important for this kind of initiatives. For further information or an in-depth presentation on the critical success factors in this kind of projects, please contact us.