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Unlocking the Power of Business Intelligence: Best Practices and Case Studies

Unlocking the Power of Business Intelligence: Best Practices and Case Studies

By israelipanda

In my 16 years as a BI implementation and consulting professional, I grew accustomed to treating the term “best practices” with extreme caution, as it frequently amounts to nothing more than a pretty word meant to pique the interest of the audience. For readers who are about to begin their BI implementation projects, I have decided to share my method for distinguishing apparent from genuine business intelligence best practices in this article.

Business intelligence best practices, which simply provide general organizational tips that are applicable to any IT solution, should not be given too much time. If you spend more than five minutes and get as much as “get organization-wide buy-in,” “don’t build everything on day one,” or “define the strategy first,” you should switch to another source of knowledge and get really useful information.

Although BI-specific, best practices are still superficial. For instance, I doubt that the phrase “identify preferred data integration method” will be of much use to businesses. This advice leaves too many questions unanswered, including “What general integration methods are available? Whose preferences ought to we prioritize first? “Implement an easy-to-use BI application that integrates with desktop applications” is yet another illustration of a similar best practice.

Where can I find useful BI best practices?

Check the BI initiatives that have been chosen and implemented by industry leaders for helpful insights. For instance, if you’re a retailer, you can see that major players in your sector are focusing on initiatives like demand forecasting, customer churn prevention, and a 360-degree view of the customer. If you are a manufacturer, you will most likely learn about supply chain optimization and predictive maintenance. At the moment, this kind of information can be found in a lot of places. There are a lot of articles that talk about real-world use cases in good detail, often including numbers about how much money they made or how satisfied customers were.

Examine BI initiatives for small and midsized businesses It is helpful to look at BI initiatives for small and midsized businesses (especially if your company falls into one of these categories) to look for use cases that are specific to that category and to look at examples of business reports and dashboards. You can get this information from vendor case studies like the one in our project portfolio, which is about a management consultancy’s implementation of BI.

Investigate BI trends It makes sense to read about the most recent BI developments and trends as well. You can find these kinds of insights by reading comprehensive whitepapers from research and advisory firms like BARC, McKinsey & Company, TDWI, and Gartner. For instance, the list of BI trends that will be significant in 2019 includes aspects such as data quality management, data visualization, self-service BI, modernization of data warehouses, agile BI development, and advanced analytics, as stated by BARC, which reflects the opinions of more than 2,600 respondents. You can also look to reputable media sites like and, which also frequently publish articles about data analytics and business intelligence trends.

In conclusion, if you’re looking for useful information, look at initiatives by industry leaders, use cases specific to a particular company sector, and most recent BI developments and trends. They will assist you in better defining and implementing your BI requirements.

  • Get buy-in from across the organization Disjointed BI practices and unsuccessful universal adoption are quick ways to fail with BI. Obtaining organizational buy-in is essential for maximizing BI success. Everyone will benefit from it; BI will ultimately benefit every department, particularly Finance, Management, Sales, and Marketing. As a result, the appropriate parties ought to be involved right away. This best practice calls for CMOs and CIOs to work together right from the start!

Another important stakeholder that you should involve right from the start is IT. Yes, IT work won’t be necessary with the right SaaS BI tool. This does not mean that IT should not be a part of the processes for purchasing, implementing, and managing analytics. The IT and development teams have useful knowledge bases that should be used. They are able to guarantee that the proper security and governance procedures are followed. Knowledge transfer and retention can both benefit greatly from IT. IT does not necessarily have to manage the BI, but they should be informed.

  • Having a plan from the start can save you a lot of money, time, and stress if you approach analysis without a plan. Prior to selecting a BI tool, you must first determine your company’s top requirements and set of objectives. Don’t just work on these at the executive level or in a vacuum. because you already have buy-in from across the organization (right?!) consult with all important parties, including operations, marketing, finance, and sales. In the end, a successful BI adoption will be guided by clearly defined objectives and key performance indicators (KPIs).
  • Start small There are probably a lot of business-related questions and insights you need to learn. It’s easy to become overwhelmed when compiling these requirements and considering the total size of your data. When every employee demands data right away, this only gets worse. The following business intelligence best practice follows from this: Begin small. Begin with a short list of important questions. Try to respond with data that is readily available. It would be wonderful if you could provide answers. It’s likely that this procedure will prompt additional inquiries that you can incorporate into your road map. Additionally, this procedure will assist you in determining which data sources you need to compile or which data you lack altogether. We support the best practices of the Agile methodology when it comes to BI rollouts, which advocate taking an iterative approach and constantly involving stakeholders. Build, test, and repeat! Collect requirements and feedback.
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