Why Enterprises Fail With Their Business Intelligence InitiativesTushar Sonal
The market for business intelligence solutions is growing at pace. Organizations are now adopting the technology to have a data-driven decision framework and gain competitive advantage. Business Intelligence solutions give companies the ability to make consistently informed decisions. Modern business intelligence tools come with flexible and interactive reporting features, giving the user the ability to perform their own analysis and answer their specific business questions. It promises increased decision efficiency and reduced reliance on the IT team for ad-hoc reporting. However, despite the enthusiasm, business intelligence projects often fail to deliver organizations with the promised high-value impacts. According to Gartner, 70-80% of enterprise business intelligence initiatives fail.
TDWI states in its survey that only 28% of senior business leaders across industries are confident that analysts at their organizations can create their own dashboard and reports without close IT support. The business users are typically unable to access the right data sources and perform queries. This study is a setback to the idea of a modern workplace where analytics is democratized. We have identified that the success of analytics is greatly dependent on getting a few crucial pieces right.
Often, organizations stake all their bets on the right technology. This tends to overlook certain important factors. The hallmark of a successful business intelligence project is that it is architected with a strong user involvement at every stage. It meets the user requirements and provides fast query response times. Organizations must first figure out how the implementation roadmap can be aligned with their corporate strategies. And identify and define a reasonable timeline and budget within which it can be delivered.
Top reasons why companies fail at business intelligence
Lack of user involvement in business intelligence strategy
Executing a business intelligence project requires collaboration among a number of key stakeholders at each stage of the implementation and planning journey. When expectations are not articulated and incorporated, it can lead to projects that are not optimized for success.
Issues like report-, metrics-, definition- discrepancies across the organization, inconsistent data quality can curtail the benefit from analytics. Different departments must be willing to break down the siloes and share useful data that will result in improved analytics quality. Often, lack of co-operation at enterprises leads to the creation of irrelevant report/ dashboards and sub-optimal UI/UX. It can be avoided by having a comprehensive enterprise approach to analytics. A well-planned pilot stage can result in building awareness of the solution and getting all the stakeholders’ attention before the real implementation begins. Involve the stakeholders at every stage and take their feedback. Do not limit it to requirement gathering and user acceptance testing phases. Deliver the answers to actual business needs. Understand the department objectives and align it with enterprise strategy.
Lack of Training/ Up-skilling for Users to Utilise the Analytics Technology
Today self-service BI tools like Qlik offers self-service data preparation, modeling and visualization capabilities. While this is ground-breaking, creating a sophisticated analysis for themselves and customizing charts for top-notch visualization demands users to learn additional skills.
There needs to be training road-map and analytics workshops for up-skilling the users. This must take into account their current skill level. Without this, they might be unable to use the tool effectively, leading to suboptimal-adoption. The company should also make the right hires to plug in any gaps within the team.
Often, the organization does not adequately perform this change management. Without proper training, the enterprise-wide business intelligence will just lie around under-utilized, curtailing the benefit to your organization.
Not Getting Management Buy-In
Analytics is a management dream. Management buy-in is extremely important. A senior executive backing the project makes a difference in addressing a lot of concerns. It will ensure that the employees make an active effort to adopt the new paradigm by making it a mandatory part of their work. In fact, according to TDWI, 41% of successful analytics projects have a senior executive backing the initiative. This will lead to clearly set priorities and pull the right resources into the critical activities. On the course of the journey, your organization will need to make some tough calls. You have to phase off the existing spreadsheet-based reporting by giving give people the cut-off date. As long as there is a plan B, plan A ca never be successful. As long as spreadsheet continues being used, BI will not be adopted. This mandate can only come from the top. Otherwise, people will continue to rely on the existing reporting methods and your business intelligence initiative will not become very successful.
Bad Analytics Partner Experience
If you are taking the analytics implementation internally, you should take it up as a project with a timeline, cost, and quality. However, many times these metrics get lost when monitoring for internal projects. Hence, business intelligence projects often need the expertise of an external vendor at some stage or all of them. But you must perform due diligence before choosing the vendor. Consider their level of expertise in the technologies that you need. Understand if they have sufficient domain knowledge in your lines of businesses in order to understand and develop the right use cases. Understand the total cost of ownership (TCO) if you involve the vendor services and support. The incompetent vendor will leave your organization vulnerable to a sub-standard execution. Analytics projects are typically costly and time taking and you would not want to be at the sorry end of the bargain at the end of a protracted project. Be explicit about expectations from your vendor. Ask them for flexibility and transparency in the whole project execution. A business intelligence solution requires not just cost-investment, but also an investment of relationships.
Relying on inappropriate BI technology can put a strain on your IT department. Such a solution will not have the capacity to answer the questions that your user community is asking for. Make sure that your solution has the desired in-built performance and governance capabilities. Choosing the right BI solution for your enterprise has to be a thoroughly-researched task. Consider the current application landscape and where you want to see your initiatives to reach. Understand what your users expect from the solution. Consider how many users need to adopt the solution and what their current skill level is. Also understand the complete costs including license, development, support costs, etc. Often, budgets for a BI project fail to take into account the complete cost involved. Such as they omit the costs of extracting the necessary data from current systems. Does your solution include purchases that you are currently unaware of? The right partners will keep you informed of the industry best practices. Do not hesitate in taking an expert’s help in choosing the right technology.
Poor Adoption by the analytics users
The insights gleaned from analytics should be easy to interpret with very well-designed dashboards. Poorly designed dashboards will affect your analytics adoption. The design must be done after a detailed user persona research. Different user groups need different type and complexity of reporting solution. The tool must display critical KPIs and metrics with story-telling features that make it easy for users to comprehend. If it does not, then they might get disengaged from the whole corporate initiative. Ensure the highest level of data quality in order to deliver accurate results. Training and mentor-ship will play a crucial role here. Familiarize the business users with the capabilities and benefits of the product. This will convince the users that the product offers windows to valuable insights that are really necessary. You can also consider embedding reports into existing applications that are used by the user. It will simplify its adoption leading to better use. Ultimately, the true test of your business intelligence solution would be how well it has been adopted.
It is not due to any one major factor that the business intelligence fails. It usually does due to some crucial steps failing. Delivering the analytics solution will require you to juggle a lot of moving pieces. Such initiatives are critical for organizations to evolve and thrive in today’s market. It will bring about transparency and provides data-driven insights for your decision making. Leverage your digital disruption and ensure that your analytics initiative is a success. By focusing on the few key factors mentioned, you can optimize the likelihood of success.
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