Contents
Common BI Challenges
- Lack of Data Quality
- Data Silos and Integration
- Choosing the Right Business Intelligence Tools
- Overcoming Budget Constraints
- Limited Technical Expertise
- Data Security and Privacy Concerns
Leveraging BI For Growth
Best Practices for Successful BI Implementation
Conclusion
Introduction
In today’s business world, data is king. Entrepreneurs and business owners must make data-driven decisions to stay ahead of the competition. Business intelligence (BI) tools have become essential for analyzing data and making informed decisions. However, navigating the maze of BI can be a daunting task, especially for those who are new to the concept. Entrepreneurs often face common challenges such as data integration, data quality, and data visualization. This article will explore some of the typical BI challenges entrepreneurs encounter and provide actionable tips to help you overcome them.
Common Business Intelligence Challenges for Entrepreneurs
Lack of data quality
One of the most significant challenges entrepreneurs face when implementing BI is ensuring their data is of high quality. Poor data quality can lead to inaccurate insights, which can harm decision-making. It is essential to ensure that your data is clean, accurate, and up to date before implementing BI tools. Some of the typical causes of poor data quality include manual entry, acquisition and mergers, real-time updates, indiscriminate data collection and system upgrades.
Manual Entry
Manual entry refers to businesses physically imputing data into their systems by hand despite the extensive array of automated avenues available. Typically, this process involves substantial hours and large numbers of employees. Due to this, the probability of human error throughout the system increases significantly and reduces the data quality as incorrect data is less likely to be noticed.
Acquisition and mergers
When companies are acquired or merged, large quantities of data are transferred to fit the new regime. During this process, it is likely there may be instances of duplications, invalid formatting or simply incorrect data. As a result, the quality of the data will be reduced, and subsequent analysis will err.
Real-time updates
Typically, BI is able to acquire data and become informed on patterns and trends in real-time. As this process is so expeditious, there is a chance the data that has been acquired is potentially incomplete or has been manipulated. As a result, the quality of the acquired data and the insights that can be gained will be significantly diminished.
Indiscriminate data collection
Businesses often collect data as they attain it. However, not all data is relevant to the functions of each entity, and thus it is sometimes difficult to distinguish between relevant data and irrelevant data during collection, particularly when collecting large quantities of data. The process is time-consuming and reduces the company productivity and available storage. It is beneficial in these circumstances to identify and store specific data that is of importance to the company instead of collecting large quantities of possibly relevant data.
System upgrades
Although system upgrades are a necessary part of maintaining security and productivity, they can cause issues in relation to data quality if they occur too frequently. This is due to the significant probability of data being deleted or corrupted during the upgrading process.
Overcoming Issues with Data Quality
To combat the issues highlighted above, it is necessary to clean up your data and erase any unnecessary pieces of information. Furthermore, it is also important to reduce duplicates and ensure consistency of formatting. The essential factors to having clean data include completeness, accuracy, consistency, timeliness and integrity.
Completeness
A group of data is complete when all the pieces of information required for a particular purpose have been acquired. For example, when a business requires a customer’s name, date of birth, email and contact information but not passport information, the data will be considered complete as soon as the required information is acquired.
Accuracy
Data is more accurate when entered via an automated system rather than manually due to human error. To have accurate data, it must be compiled without manipulation or duplication. This is especially the case with large quantities of data that are acquired simultaneously, as there are increased chances of more inaccurate data due to the increased quantity being collected. This risk can be mitigated by collected smaller quantities of data at a time and ensuring that data is accurate and reliable throughout the process to increase the quality of the data.
Consistency
Identical data should be identical. If they are not the same, then the data is therefore unreliable and will consequently create space for capricious decisions. This risk can be mitigated by cross-examining supposedly identical data and ensuring it is represented correctly.
Timeliness
Timeliness simply refers to the time at which the data is available. Data should be continuously updated as it changes to ensure it is correct and available when it is required.
Integrity
The data should reflect true, real-world data. It should be reliable and data groups should only remain in warehouses if they are required. For example, where some customer information is required, but some is missing, the entire data group is invalid and no longer useful.
If these five factors are satisfied, the data quality will remain high and business insights will be at their maximum potential.
Data silos and integration
Another common challenge entrepreneurs face is the presence of data silos. Data silos are data repositories that store data in different locations or systems, isolating it from other departments. For example, a data warehouse or a cloud storage space. Due to the segregation between the stored data, it is difficult to access and analyze. As a result, the data cannot serve its maximum potential.
It is necessary for businesses to identify siloed data so that they can improve their productivity, however, integrating data from multiple sources can be complex. Entrepreneurs must ensure that their BI tools can seamlessly handle data integration.
It is first necessary to establish where data silos originate to determine how to successfully integrate siloed data. Typically, they are created unintentionally as a byproduct of individual departments neglecting to consolidate data with other departments. For example, they may occur as a structural or technological data silo.
Structural data silos are created due to policy choices within companies, such as mergers. Alternatively, they may occur when an organisation grows rapidly, and it is more practical for varying departments to construct individual data storage systems. Technological data silos result due to technological issues, such as spreadsheets that are unable to successfully incorporate all the relevant data.
One solution to data silos is creating a central data repository that consolidates data from different sources into one place. Other avenues include using an application programming interface, which allows multiple different data sources to interact and communicate with each other.
Choosing the right business intelligence tools
Choosing the right BI tools is critical to success. Many entrepreneurs make the mistake of selecting BI tools based on price or popularity rather than their specific needs. Evaluating your business requirements and choosing tools that align with your goals is essential. For example, if you need to analyze large datasets, you may need a tool that can handle big data. Similarly, if you need real-time insights, you may need a tool that can provide real-time analytics. Some of the universally applicable tools include Microsoft Power BI and Tableau.
Microsoft Power BI is an interactive data visualisation platform which allows for multiple data sources to be combined so that vital business insights can be dispensed in a manner that will drive success.
Tableau is a visualisation platform which allows business to explore and manage data in an expeditious manner, allowing them to discover and distribute accurate insights with ease.
Both tools can be applicable to a range of functions.
Overcoming budget constraints
Budget constraints can be a significant obstacle to implementing BI tools, as the products with increased functionality are often more expensive. Many entrepreneurs may feel that BI is too expensive or not a priority. However, the benefits of BI can far outweigh the costs, considering the contribution they make overall to a company. Evaluating the ROI of BI tools and considering the long-term benefits they can provide is essential. There are also many cost-effective BI solutions available, such as open-source BI tools, that can help entrepreneurs overcome budget constraints. Start-up companies and small businesses can take advantage of affordable BI tools such as Fourth Dimension, which offer a similar range of functionality to higher-end tools for a reduced cost.
To overcome budget constraints, a business could use their existing resources in a more efficient manner, prioritize the more important matters and learn from how other companies have managed their money.
Limited technical expertise
Another common challenge entrepreneurs face is limited technical expertise. Implementing BI tools requires technical expertise, and many entrepreneurs may lack the necessary in-house skills. One solution is to hire a BI consultant or outsource BI implementation to a third-party provider. This can help entrepreneurs overcome technical challenges and ensure their BI implementation is successful. However, this may be too costly for some businesses just starting up. Alternatively, it may be simply beneficial to self-teach by reading up on trustworthy websites. Check out our other blogs on all the basics of business intelligence for some handy tips in relation to getting started and gaining some technical experience. We can help develop your skills and get you on your feet in no time!
Data security and privacy concerns
Data security and privacy are critical concerns for entrepreneurs implementing BI tools. With the increasing amount of data being collected, it is essential to ensure that data is secure and private. With protected data, both the business and the customers can feel at ease. Entrepreneurs must evaluate their BI tools’ security features and ensure they comply with data protection regulations. This may involve implementing encryption, access controls, and other security measures.
For Australian-based businesses, the Commonwealth Privacy Act provides that you must only collect personal data if it contributes to the purpose of your company’s operation and must erase this data when it is no longer needed. Essentially, try to handle data in a manner that society would deem appropriate and hold the security of said data as a matter of the utmost importance. This is especially critical considering the nature of the digital age and the ease in which data may be hacked.
Leveraging Business Intelligence for Growth
Once entrepreneurs overcome the common BI challenges, they can leverage BI tools to drive growth and profitability. BI tools can provide insights into customer behaviour, market trends, and performance metrics. This information can help entrepreneurs make informed decisions that drive growth and profitability. For example, BI tools can help entrepreneurs identify new market opportunities, optimize pricing strategies, and improve customer retention. Once a business has overcome the issues that have been identified previously, they will be able to leverage their BI tools in a manner that will drive the company to success rates beyond their competitors.
Best Practices for Successful Business Intelligence Implementation
To ensure a successful BI implementation, entrepreneurs should follow best practices. These include:
- Clearly defining business requirements and goals
- Evaluating and selecting BI tools that align with business requirements
- Ensuring data quality and integration
- Providing training and support to employees
- Establishing a data governance framework
- Continuously evaluating and improving BI implementation
Conclusion
Navigating the BI maze can be challenging for entrepreneurs, but it is essential to overcome these challenges to make informed decisions that drive growth and profitability. Entrepreneurs can successfully implement BI tools by addressing common BI challenges such as data quality, data silos, and limited technical expertise. Leveraging BI tools can provide valuable insights into customer behaviour, market trends, and performance metrics, enabling entrepreneurs to make informed decisions that drive growth and profitability. Following best practices for BI implementation can help entrepreneurs ensure a successful implementation and achieve their business goals.