Five Steps to Business Intelligence Project Success
Successful business intelligence (BI) projects encompass more than implementation of a solution on time and within budget. True success should be measured by how the BI solution improves the organization's overall performance through increased efficiency in reporting, planning, financial functions, and performance measurements. This will help ensure organizations' BI projects fall into the estimated 30 percent success rate.
Much has been written about measuring return on investment (ROI) for BI, and the general conclusion is that gaining tangible insight into the initial benefits is not easy. Identifying long-term benefits becomes more practical as planning and analysis, compliancy, and forward-looking approaches become more mainstream within organizations. To gain insight into how to implement a BI solution successfully, organizations should benchmark the success of other organizations, including their implementations and use of BI, against their own current initiatives. It is equally important that organizations learn from other organizations' failures—and avoid repeating them.
This article identifies and explores five steps that organizations should take to avoid the common pitfalls encountered by many businesses when implementing a BI solution. These areas include the identification of the business problem, BI tool use, the delivery of data, training initiatives, and development of a framework toward choosing the proper solution for the organization. These five areas provide an overview of items that should be identified before implementing BI within an organization or business unit.
Identifying the BI business problem is the first step to ensuring a successful project. Once an organization knows what is broken, not only can it start to find ways to fix the problem, but it can also identify the proper resources, create buy-in, and prioritize how to tackle the project. To produce an ROI, a BI solution needs to correspond to an organizational business problem; otherwise, implementing an ad hoc query tool, online analytical process (OLAP) cube, or dashboard will not create lasting benefits.
Unfortunately, it is common for BI solutions to be pushed onto a business unit in order to meet an information technology (IT) objective rather than an organizational need. Sometimes, organizations get caught up with general initiatives and lose sight of the actual benefits BI provides in terms of performance management, collaboration, workflow, process improvement, etc. To attain buy-in, the user community should be a part of the problem identification process. An implementation decision that comes from management still requires input from users as to what their requirements are, and this information can make the difference between the implementation of a tool that works as a value proposition and an implementation that may be seen as useless.
Step Two: Determining Expectations of Use
Once BI is implemented within an organization, its usage usually grows beyond initial expectations. For example, an organization may assume that its BI implementation will involve 10 to 20 users, when in reality, over 400 users query data on a monthly basis. Based on the initial design of the platform, the system may not be built 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 a lack of confidence, getting an unstable system up and running may not seem worth the effort, delays, or time it would involve. 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, other departments or business units see the benefits, and adoption begins to spread throughout the organization. For an organization to meet these needs, the anticipated use of BI should be determined beforehand.
Another consideration is the type of BI tool use. For example, if a sales manager needs to increase sales and wants to analyze trends, product distribution, and sales performance, creating a set of static reports will not produce the appropriate results. A data visualization tool to manage these items and develop a plan based on trend analysis will more likely produce the appropriate results.
The collection of the right information for reporting and analysis becomes essential to deliver value to organizations. Although the identification of required data is time consuming, it is the backbone of BI. Additionally, identifying how data will be delivered, what the appropriate data cleansing activities are, and whether data is delivered in batch or in real time should be defined in advance. If data is not cleansed or delivered when needed, then the front-end BI tools will not provide the proper value to the organization. BI solutions impart value through the analysis of data, so it is essential for data to arrive when required, in the proper format, and at the right time. In addition to extract, transform, and load (ETL) tools, data quality and data cleansing need to be inherent aspects of the delivery of BI within the organization. In reality, short of an organization-wide master data management (MDM) initiative, the responsibility of providing accurate data will fall on the shoulders of the business units implementing BI.
Some organizations are misguided and think that their BI solution will provide them with the tools to fix their data problems. BI solutions can provide ongoing data quality processes, but these are not innate to software offerings. Some BI tools include enhanced data quality and integration features, and some vendors assume this responsibility should fall to the organization. Organizations should implement data management structures to minimize frustrations that result from data issues.
Step Four: Rolling Out Training Initiatives
Deciding when to roll out training contributes to project success. Training initiatives should begin right before or during the implementation phase. However, in many organizations, training is rolled out months before actual implementation, creating hype among the employees about the new system and what they will be able to do with it. By the time implementation actually occurs—months later—the initial excitement and buy-in has subsided, and more importantly, users have forgotten their newfound skills. To build momentum again, training needs to be repeated—wasting time and money.
Buy-in related to change is never easily achieved within organizations. Users become attached to their current processes whether or not those processes are productive. Buy-in does not occur immediately upon showing users the inherent value of BI, as their whole way of doing business will change. Creating a training program and delivering that training in a timely fashion helps users apply their newfound skills immediately, and helps to increase user buy-in.
Organizations should identify whether more value will be provided by a vertical solution that is built specifically for the organization's industry or department, or by a horizontal solution that can grow with the organization. For example, does the organization need a generic reporting, querying, and analysis tool that will extend across the organization, or does the organization need to develop a process and compliancy that will adhere to the
In addition, the use of BI in the future and its anticipated usage may help determine whether a horizontal or a vertical solution will best meet the organization's needs. Organizations requiring compliance should take advantage of vertical-based solutions because vendors have developed solutions to meet specific compliance requirements. Horizontal solutions need intense customization to bring them up to par, leading to extra time and money spent on developing the solutions.
Organizations in key vertical industries should strongly consider vertical-based solutions that will meet their needs out of the box. Vertical-based solutions are likely to meet the general requirements of a specific industry or department, but since horizontal BI solutions do not base themselves on specified data models, they may be more versatile to the changing demands of the organization. Therefore, if an organization anticipates rapid BI growth across the organization, having the ability to develop solutions based on individual needs may be more beneficial. This relates to identifying the business problem and anticipating the future needs of the organization.
All too often, BI projects fail to meet an organization's expectations. But with research, planning, and a solid methodology, such failure can be avoided. To help ensure BI project success, organizations should work through these five essential steps: identifying their business problems, determining how they will use their BI solutions, knowing how and when data is delivered, rolling out user training initiatives at appropriate times, and developing a framework for selecting the type of solution that will best fit their organizations' needs.