Leveraging Business Intelligence to Improve Business Operations

Organizations are constantly on the lookout for how to best improve their operations. Case in point, companies have been leveraging Business Intelligence (BI) to gain actionable insights that will strengthen their performance.

Leveraging BI to Improve Business Operations

However, to improve your company’s overall efficiency, rather than looking at the next big solution that hits the market, the answer might be to simply reorganize your existing BI system.

Centralize Data, Re-Engineer if Needed

While BI offers many benefits for an organization, a remake of its infrastructure could substantially improve your company’s overall success. The key lies in re-engineering your BI system through Data Warehouse Automation (DWA). This transforms parallel data sources and various platforms to a centralized, unified system. With a centralized platform, companies deploying a BI solution, even from the ground up, can know it will be done right the first time.

Business Intelligence has proven to be a competitive advantage, allowing companies to they look at and correlate data from different company operations such as, inventory, finance, production, and other stakeholder groups. BI has greatly impacted, not only corporate reporting, but overall business performance for the short and long terms.

Different Environments Can Lead to Problems

Approximately 60% of users are using data from two or more different environments. Having reporting systems reside in various departments makes it cumbersome to access critical data and can lead to flat-out inaccuracy. This typically means a company is storing information in various data warehouses, data marts, Excel spreadsheets, portals, databases and so on. Doing so often causes inaccurate reporting, information duplication, incongruent goals, existing components that aren’t tied to the BI ecosystem and increased necessary maintenance and upgrade time.

Often times, the two or more reports do not coincide with each other, which can lead to arguments over the validity of a data source. It is virtually impossible to have a true version of the company’s performance when departments and functions can’t agree on what constitutes accurate information.

Improve Your BI System by Centralizing

By building a strategic BI system through DWA, users will be able to have a holistic view of the company and take advantage of more accurate reporting and analytics.

Here are a few considerations for organizations looking to improve their BI systems by shifting from parallel reporting to a more centralized, single view.

Many companies have disparate data stored in various locations for different departments and groups that use numerous technology programs to access it. Having local control might make the manager or decision-maker more comfortable, but it has many limitations and liabilities company-wide. Consolidation through business intelligence enables a company to organize and centralize all its data within a data warehouse. Having a centralized BI system significantly helps an organization discover hidden patterns and trends that individual systems often do not uncover.

Integrate Data from Various Technology Platforms

With a single, centralized data system in place, a company can integrate data from all its technology sources such as ERP, CRM, payroll, and more. The 360° view of the business from analytics and generated reports enables staff members of all levels to have a more accurate picture of how the organization is performing, and where it’s falling short with key performance indicators.

Companies waste a lot of time trying to determine what the correct numbers are for its business when multiple data systems are involved. For example, manufacturing might issue a report on sales that doesn’t match the sales report issued by the accounting department. A centralized BI eliminates this by allowing a company to have one single source for reporting and analytics that can be considered true and accurate. Instead of spending time on trying to determine which report is correct, staff can spend its time on analyzing the report and making trustworthy, data-driven decisions.

Nimbler, Faster, Clearer BI Performance

Organizations that use analytics are nimbler, faster, and can make clearer strategic decisions. Having better data quality as evidenced by the centralized reporting enables the company to determine its strengths and weaknesses, identify trends and new business opportunities and avoid potential risks. Companies can find the root causes of problems and take immediate, corrective action quicker than an organization without a centralized hub for its disparate data sources.

With the proper data warehouse tools, historical or legacy system data can be integrated into the centralized data warehouse efficiently. Drag and drop features allow users to easily provide maintenance and access data for reporting. Selecting the right tool can also help increase ease-of-use, empower end-users without IT support and decrease downtime during implementation and maintenance.

In the end, organizations are constantly looking at ways to improve performance and decrease costs. Technology and modern business practices play a significant role in doing so. Maximizing the bottom line can only come from better performance and stronger decision-making. Business Intelligence can be a main factor in accomplishing these objectives. Especially if implemented in a way that allows users to fully leverage its capabilities and to see information that is often hidden due to the fragmentation and decentralization of its platform.

Author Bio: Heine Krog Iversen is the CEO of TimeXtender, the largest provider of data warehouse automation software for the Microsoft SQL Server. He can be reached at hki@timextender.com.

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  1. Hi,

    Really impressive post :).

    With re-engineering the Bi system, through Data Warehouse Automation that helps in improving the company’s overall success.
    Data visualization that is a member of BI stack can also help in the enhancement of a business. Only a few people are aware of this fact that it is used for transformation of raw data into meaningful form, for the purpose of business analysis.


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