Businesses that seek ways to get an edge in the market often depend on data and its strategic utilization. Typically, to get to the point and make informed decisions, they need to analyze vast amounts of information. However, grasping proper insights from these data is not an easy endeavor. Ideally, these insights should be in an understandable and interpretable form.
Today it becomes possible with effective BI solutions that make complex reports look digestible. Moreover, they help enhance operational efficiency, understand customers better, and improve services. That is why BI approach is becoming more and more popular.
Yet, implementing BI technologies still has some bumps along the way. To help you consider the main possible challenges of BI, we crafted a comprehensive article. Let’s get straight to discuss these issues and understand how you can overcome them.
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Top 7 BI Implementation Challenges to Consider
1. Ineffective Data Architecture
One of the key challenges in developing business intelligence solutions is designing data architecture. Basically, it forms the foundation upon which the entire BI ecosystem rests and impacts the effectiveness, scalability, and sustainability of BI solutions.
A well-structured data architecture ensures that information is organized, integrated, and maintained in a consistent manner. On top of that, it streamlines data access, eliminates silos, and provides a single source of truth across users.
However, there is a great variety of information sources, including structured, semi-structured, and unstructured, so integrating and managing diverse data types becomes a daunting task. To keep everyone in the company interacting with the same reliable and up-to-date information, your team has to build a flexible and agile data architecture.
2. Poor Data Quality
Next on our list of BI challenges is data quality. The accuracy of business intelligence solutions relies on the data they are built on. Even with substantial investments, dedicated efforts, and a skilled team in place, you can’t succeed if you use incomplete, missing, or outdated information.
To harness such kinds of business intelligence problems, data management can serve as a helping hand. It includes such practices as profiling, real-time monitoring, and regular information cleansing. At its core, data management ensures that information is secure, accessible, and correct.
To ensure data quality (DQ), you can define key data quality metrics such as accuracy, completeness, consistency, timeliness, or uniqueness. By establishing clear and measurable criteria, it is possible to both benchmark relevant information and identify areas that need improvement.
Additionally, there are many methods to monitor data quality, such as creating reports for tracking DQ or incorporating a DQ indicator into your current reports. These techniques allow you to determine how reliable and accurate the data you receive.
3. Unclear BI Strategy
Another one of the significant challenges of BI solutions is the lack of a clearly defined business intelligence strategy. And really, how can you guide the implementation process and ensure that the organization goals and objectives are met effectively without an appropriate plan?
If you don’t have a clear strategy, the scope of your BI projects can expand beyond the intended. As a result, you can face delays, increased costs, and difficulties in getting meaningful insights.
Without a solid plan, you might also end up with BI tools that don’t meet the needs of end users. This can cause low user adoption rates and frustration among employees who struggle to find value in the BI tools.
As you can see, underestimating the significance of a well-implemented business intelligence roadmap can lead to a range of additional problems. So take your time to carefully plan and execute your data-driven strategy.
4. Weak Content Management
Companies that overlook the importance of effective content management can face many challenges during the business intelligence implementation process. As a quick side note, here content management means handling and organizing the data itself, reports, dashboards, and other information generated by BI systems.
Obviously, employees are more likely to embrace BI solutions when they can easily find and use the content they need. Appropriate content management facilitates quick search and retrieval of specific reports or data.
It’s also important to create documentation for each of these reports since it provides clear explanations of the metrics used to assess data. Documentation ensures users understand and appropriately interpret data to make better-informed decisions.
Additionally, it is worth notifying your employees about new reports or updates to existing ones. Thus you can help your team to keep up with the latest insights.
On top of that, alongside effective content management, it is critical to deliver information in an accessible and simple manner. With that in mind, consider designing user-friendly interfaces for BI tools. Such UIs can present complex data in a simple manner utilizing charts, graphs, and other visualization.
Without a well-crafted design, users may be unwilling to engage with BI solutions. This, in turn, can significantly contribute to lower rates of BI adoption. More on that we will talk in the upcoming chapter.
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5. Low Adoption Rates
One of the common problems that can arise during business intelligence implementation is low adoption rates. You may face challenges in encouraging your staff to employ business intelligence tools. For example, they may be reluctant to say goodbye to Excel, SaaS platforms, or other apps they are so comfortable using.
Being unfamiliar with BI tools is just one reason why people do not want to use them. Another reason is a deficiency in data literacy. If you don’t have skilled employees who can interpret data accurately, then possibly you can’t make informed decisions. Whereas, data-literate employees can assess the credibility of data sources, understand the context, and draw meaningful conclusions.
Consequently, if you want to harness the full potential of your business intelligence solutions and tackle problems on time, then it is definitely worth fostering data literacy among your team.
To get to the point, you may offer training or master classes to your staff. Also, consider opening support channels in your team’s message board to provide timely responses to your employees queries.
As a result, you can build a community of data-literate individuals within your organization who can help others and share their expertise.
6. High Fees
We’ve almost come toward the conclusion of the list of business intelligence challenges and we can’t omit the substantial expenses it requires. Pricing for BI software might vary depending on:
- data volume
- company size
- project dimension
- number of users
- complexity of the implementation process
Typically, you need to consider costs for licenses, hardware specifications, employee training, and software maintenance. The latter can come with additional fees.
That is to say, implementing BI is not a one-time endeavor, but rather an ongoing process that demands constant development and investment. Business intelligence tools need to evolve alongside a company’s changing needs and its existing data landscape.
So, as a garden requires constant care to thrive, a successful BI implementation requires sustained attention, which may cause additional expenses. Yet, it is definitely the case when such expenses are reasonable.
Companies that opt to cut corners in efficiently processing data run the risk of being pushed out of the competition. Hence, investing in robust analytics and BI tools is a pathway to success.
7. Hard to Deliver Mobile BI
The list of business intelligence challenges will be incomplete without mobile BI. Though adapting business intelligence tools to mobile devices appears to be simple, it doesn’t mean that this process is devoid of complexities.
Here are some basic issues you can come across along your way:
- Data Security. Mobile devices can be more susceptible to security breaches, so employing strong encryption and authentication measures is crucial.
- User Experience. With different screen sizes and a variety of device types, it’s vital to think about how users can smoothly navigate and interact with your BI solution on their mobile devices.
- Performance and Speed. Mobile networks might not always provide the same level of connectivity and speed as traditional networks.
Overall, to successfully utilize mobile BI, you need careful planning, design, development, testing, and ongoing maintenance. On top of that, your team should be experienced in BI, web, and mobile technologies.
Overcome Challenges and Implement Robust BI Solutions
We skimmed through the main business intelligence challenges that need to be addressed while building your BI solution. By harnessing these issues, you can ensure that there are no roadblocks on your way to efficient BI and improved decision-making.
However, It’s not an easy feat, so probably you may need additional resources or professional advice. If you’re struggling to manage the array of issues related to BI, give us a shout. We will help you tap into the vast pool of potential of business intelligence development. Contact us today.