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How not to come unstuck when implementing a Business Intelligence system – part 2

02 June 2016

Problems in the implementation of a Business Intelligence system may arise in any organization. They are most commonly associated with typical phenomena such as excess data, only part of which is valuable for the business, or a lack of appropriate order and completeness. Fortunately, these problems can be solved – mainly thanks to competent pre-implementation analysis, which helps create an efficient plan of action. Sometimes, however, the problem lies elsewhere – for example, difficulties may result from poor decisions or unrealistic customer expectations.

So how do you avoid mistakes in the process of implementing a business analytics system?

Identify your needs

Even during the pre-implementation analysis, it is vital to determine the specific problems and questions to which Business Intelligence systems will help us find the answer. A failure to clearly define these issues may mean that the system will contain all the data, but in actual fact will be of very limited use. Each company has different characteristics, different issues which must be dealt with, and analytical reports must respect this uniqueness. To make this possible, the system must be implemented so as to optimally fulfill the needs of a particular customer.

Make sure that the correct needs are identified

The incorrect identification of needs is also a major issue in implementing a BI system. The most common reason is the desire to have all the data and analyze all the areas that are redundant (in a previous article, I wrote why having all the data available in the BI system is inefficient). A faulty analysis means that in theory all the data that we wanted to have is available in the system, but in practice we are unable to gain full benefit from it.

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Give yourself enough time to analyze

Business and pre-implementation analysis is one of the most important stages of each implementation of Business Intelligence. Customers may seek to reduce the time for analysis to a minimum or accelerate the individual phases. Unfortunately, errors or omissions at this stage can be very costly in later phases, and often result in delays in the completion of the project as a whole.

Get to know the tools

Each new system is useful insofar as the people who use it can derive benefit from it. If the end-users are not able to use BI reports and analyses effectively, the system will be of limited use. Unfortunately, customers often overestimate their knowledge of the tools and sacrifice time spent on training, which ultimately means that the system is not utilized to its full potential.

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Customize tools

Above all, the final results of the implementation of Business Intelligence, from the perspective of the end-user, are the reports and the managerial cockpit. Due to the huge number of different specialists (even within a single company) who can reap the benefits of BI tools, as well as the diversity of their tasks, we cannot ignore the fact that they have different reporting needs. Any lack of appropriate visualization methods, tailored to the needs of specific groups, means that although reports show the correct data and the desired information, they are unattractive or ineffective for end-users, who therefore use them reluctantly or rarely.

 

Use only the essential tools

Depending on the choice of technology and software provider, some systems offer a wide range of different reporting tools, data presentation methods, and access points to information in the Business Intelligence system. However, there is a risk that too much equipment can cause a sense of distraction or confusion among end-users. So use only those tools you really need in choosing a certain, proven, developed and scalable solution to last “for years”, because changes are expensive and cause confusion, reducing the efficiency of the company as a whole.

Slawomir Drzymala

Business Intelligence Specialist

Konsultant Business Intelligence, który na co dzień projektuje i implementuje rozwiązania BI w Microsoft SQL Server, korzystając zarówno z klasycznych narzędzi, jak i funkcjonalności Power BI. Posiada doświadczenie w pracy z Oracle, SAP, IBM, QlikView oraz Pervasive.

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