If you have researched the benefits of business intelligence, you may have seen from other sources that the failure rate of BI implementation is 70-80%.

The reason for this high rate is because of the transition into adopting business intelligence may not be accurately matched to the businesses that try to carry them out. By tailoring your BI Roadmap to accurately address the pain points of your business, your company's data will become a successful asset. 

 The components of a successful BI Implementation

Readiness Focused - Creating the foundation for implementing BI takes time, effort, budget, and buy in. 

Plan for Change & Adoption - BRanching into the actions to be taking, businesses should be listening to both employees and clients, and consider the impact of BI to them. 

Execution Focused - YOur business requirements and governance goals plays a huge part in what BI technology you should invest in.

Readiness Focused

Measured Business Value - If an enterprise analytics initiative or even a specific use case hypothesis does not specifically identify the value and overall contribution to the organization’s strategic goals, then it should not be pursued. Similarly, if a use case does not clearly identify the value and a mechanism for measuring that value, then it should not be included in an analytics use case prioritized roadmap. Analytics use case value can be quantified in various ways, including, for example, increased savings/revenue, increased safety, reduced risk, improved operational efficiency, and improved reliability.

Operational Support & Resources - A proper strategy, prioritization, resource skill sets, business processes, funding, data quality, and leadership support are all necessary for proper analytics support. Understanding the roles of a BI implementation and determine how you will fill them is also important. The most common roles to consider adding are:

• Architect – establishes technical and data foundational environments; establishes development standards; assures BI solution integrates into existing structures or a new structure is determined
• Developer – fulfills requirements with a technical solution; includes data and front end development; can be performed in any project delivery methodology environment (waterfall, Scrum, etc..)
• Requirements specialist / Integration analyst – gathers requirements, assures alignment to business processes and integrates new data solutions into existing processes & structures
• Project Manager – manages the overall project schedule, coordinates across all resources, manages project communications, risks, issues, changes, etc.. Role can be full or part time.

Executive Sponsorship -  An executive sponsor is responsible for the overall success of the program, and continuously assure alignment to corporate strategy, and delivery of value. Without that buy in and sponsorship, projects are susceptible of dying out without success. 

Execution Focused

Tools & Technology - The technology approach will likely be at least slightly different for each organization and should establish a thorough understanding of their business goals and requirements for their analytics program before making decisions regarding technology (“what before how”). Consider the following when selecting a technology best suited for your organization:

• Technology and tools should align with business user needs and sponsorship
• Strive for “natural analytics” solutions with seamless integration
• Beware long implementation timelines and long time to value cycles
• Consider “1st to be 2nd” approach
• Plan for data growth, both longer and wider
• Focus locally to assure effectiveness, be prepared for enterprise needs in parallel
• Balance with business plans; scale when needed, but not much “build it and they will come”

One of the key reasons BI Implementation Projects fail is that they go for the “cheapest” tool and don’t consider total cost of ownership or they spend all their time researching tools and lose sight of the other components to a successful BI roadmap.

Governance - Balance the goals of self-service and governance according to your goals. 

BI Project Pitfalls and How to Avoid

 It is common for BI projects to fail or get hung up due to lack of BI strategy, lack of training/education, using unstructured data, and most commonly lack of adoption. We recommend treating BI as a business process improvement initiative rather than an IT-centric undertaking, focus on supporting key business objectives with better information embedded in specific business  processes, and the use of a BI-specific development methodology, such as Scrum or Decision Path’s BI Pathway method. These are all part of building a data culture within your organization.