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Six Business Intelligence Challenges IT Teams Need to Resolve

By Apoorva Kasam - January 02, 2023 4 Mins Read

Six Business Intelligence Challenges IT Teams Need to Resolve

Business intelligence allows companies to procure insights from a high volume of data. Sorting and analyzing the data can be tedious. Business intelligence software helps businesses to streamline the right data into informed decisions.

A strong business intelligence strategy can help organize the flow and ensures that business users have the access to actionable insights. Disorderly business intelligence approaches can lead businesses to reach a minimum value and will restrict them from achieving business goals. Here are six common business intelligence challenges that businesses face.

Choosing the Right Business Intelligence Delivery Method

With many traditional IT-managed ways to deliver reports and insights, companies are more intuitive about utilizing self-service business intelligence tools to streamline processes that derive an increase in business value. However, there are a few challenges to taking the self-service approach. Having extensive access across various departments in the company leads to data security problems. To overcome this, businesses need to adopt central and standardized control over the business intelligence tool by governing the data accurately. As a result of these trade-offs, organizations must ensure they choose the best-suited business intelligence approach.

Also Read: How Decision Intelligence Can Empower Enterprises

Data Integration

Effective business intelligence process integrates predictive analytics, reporting, and management of operations. The demand to simplify a variety of data from on-premises and cloud is a complicated process and can be time-consuming.

Organizations must ensure that quality issues are identified during the data extraction process and should restrict the irrelevant data from propagating to the end results. An effective combination of integration and analytics strategy can be established for efficient data integration.

This will ensure consistency and quality which can be readily utilized for decision-making.

Insufficient User Adoption Rates

Organizations understand the benefits of business intelligence tools to get buy-in from all stakeholders, but at the same time is difficult to convince the users that business intelligence will aid in making legitimate data-driven decisions. As a result, there is an initial reluctance to adopt business intelligence tools which leads to low adoption rates. To gain buy-ins, businesses must build business intelligence dashboards to connect and interact with their data in a meaningful way, displaying benefits to the users. This will enable the user to understand the value of adopting the business intelligence tools.

Consistent Data Governance

Organizations need to ensure that mature data governance strategies are deployed. A solid data governance process allows businesses to make transparent decisions based on trustworthy data. Having certified metrics and a centralized governed set of key performance indicators (KPIs) lined up allows for standardizing the tools and platforms creating proficiency around them.

Considering “Perfection” Over “Good Enough”

Businesses desire to obtain perfect data as they spend time gathering as much relevant data as possible by fixing incomplete data or correcting formats. It is highly possible for businesses to translate imperfect data into useful business insights to significantly improve the supply chain. The key to achieving a perfect data structure is a step-by-step process.

Also Read: Strategies to Optimize Enterprise Resource Planning (ERP) 

Hesitant to Adopt Change

Organizations having dealt with complex traditional software have a negative impact on the new software and show resistance to adoption. If the software is difficult to handle and is being managed by a specific group of IT experts, the chances of adoption of new software would not expand beyond a certain group of people in an organization. Businesses need to make sure to pick the right solution which is beneficial for the company. At the same time, employees should be trained as a part of the implementation process which will help them to adapt to the new phase.

Businesses need to ensure that the underlying business intelligence architecture can scale and incorporate new tools as required. Business intelligence managers need to create a process for updating and maintaining metrics and data models. This allows the company to delete the data which is no longer beneficial.

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Apoorva Kasam

Apoorva Kasam is a Global News Correspondent with OnDot Media. She has done her master’s in Bioinformatics and has 12+ months of experience in clinical and preclinical data management. She is a content-writing enthusiast, and this is her first stint writing articles on business technology. She has covered a wide array of crucial industry insights like Blockchain, strategic planning, data analytics, supply chain management, governance, compliance, and the latest industry trends. Her ideal and digestible writing style displays the current challenges, and relevant mitigation strategies businesses can look forward to. She has a keen interest in the latest enterprise trends like digital transformation, cloud, and enterprise resource planning. She looks for minute details, while her excellent language skills help her deliver a crisp-looking, niche-specific message through her articles. She is looking forward to exploring her writing styles and portraying her thoughts that can help enhance organizational effectiveness, business performance, and sustainability. Apart from writing, she enjoys spending time with her pet and reading oncology publications.

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