Once BI is implemented within an organization, its usage usually grows beyond initial expectations. For example, an organization may assume that its BI solution will be used by 10 to 20 users, when in reality over 400 users query data on a monthly basis. Because the initial design of the platform will have been based on a low number of potential users, the system may not be able to sustain such a high number of queries, and will most likely "crash" (fail), causing users to lose faith in the new system and potentially revert to their pre-BI environment for stability. In addition to lacking confidence in the new system, the organization may see the challenge of getting an unstable system up and running as not worth the effort, delays, and time required.
With unrealistic expectations, frustration may cause the organization to rethink its use of BI. Generally, once BI adoption occurs within one part of the organization and other departments or business units see its benefits, adoption begins to spread throughout the entire organization. For a BI solution to meet these increasing needs, organizations should anticipate the use of BI before implementation of a solution.
Another consideration is the type of BI tool use. For example, if a sales manager needs to increase sales and therefore wants to analyze trends, product distribution, and sales performance, creating a set of static reports will not be helpful. A data visualization tool to manage these items and to develop a plan based on trend analysis will more likely produce the appropriate results.
With unrealistic expectations, frustration may cause the organization to rethink its use of BI. Generally, once BI adoption occurs within one part of the organization and other departments or business units see its benefits, adoption begins to spread throughout the entire organization. For a BI solution to meet these increasing needs, organizations should anticipate the use of BI before implementation of a solution.
Another consideration is the type of BI tool use. For example, if a sales manager needs to increase sales and therefore wants to analyze trends, product distribution, and sales performance, creating a set of static reports will not be helpful. A data visualization tool to manage these items and to develop a plan based on trend analysis will more likely produce the appropriate results.
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