Business Intelligence Best Practices – and What to Avoid

Business Intelligence Best Practices – and What to Avoid

What is Business Intelligence?

Business Intelligence combines data science with artificial intelligence, resulting in rich, factual information that informs business decisions and streamlines processes. This information is ideally gathered from multiple sources and will typically involve data mining, analysis, performance metrics, reporting, visualisation and more.

The benefits of business intelligence are so notable that BI is fast becoming a standard investment for businesses that aim to compete in the modern market. Business Intelligence benefits include informed decision-making, faster analysis on more reliable data, and improvements in overall efficiency, customer service and employee satisfaction.

It all sounds great, but the fact of the matter is that in order to achieve these benefits, BI has to be implemented correctly. This article will point out the main areas in which those new to BI tend to go wrong so that you can succeed with business intelligence, and avoid the pitfalls others have faced.

Business intelligence: What not to do

In order to succeed with technical advancements like business intelligence, it helps to first address errors that are commonly made by those starting out. Knowing what not to do helps us identify how and why BI works so well for some, while others seem to struggle. So, let’s dive in and look at what not to do when starting out with BI.

1. Poor quality data collection

Those new to data collection have a tendency to collect all the data they possibly can, without knowing what they are looking for and why. This leads to hoards of data being collected, which then has to be cleaned, organised, analysed and stored. On the other hand, if you fail to collect data from reliable sources, your data will be poor and reports will fail to account for the missing data sets. For example, if your social media is connected to your BI tools but your own website is not, then rich, targeted data is not being mined and your reports will be inaccurate.

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The best practices for data collection in business intelligence are to limit the data you collect, and to mine from reliable sources. Only collect what you need, otherwise you must pay for data warehousing and data protection for all that excess data, which doesn’t even serve to improve your business.

Cut out the ‘noise’ and only focus on what you need, and ensure you are collecting from reliable sources, such as your website and social media channels.

2. Unclear business cultures and structures

Prior to implementing business intelligence, it is important to have a clear understanding of your business structure and your company culture. Those who enter BI without these fundamentals bring unclear business objectives to large, overcomplicated data sets, and cause overwhelm where it need not be.

The same thing can occur when a company tries to answer too many questions through their data; clarity is lost and time is wasted on potentially irrelevant queries. Best practice is to narrow down your enquiries and really focus on what insights or automations your business would truly benefit from.

Encouraging a data-led culture within your company, and allowing employees to raise their concerns and suggestions, leads to a more robust, efficient and informative BI system. It goes without saying that establishing this open culture benefits the company through more intuitive and tailored systems.

3. Not providing training

data analytics training

The points above are all well and good, but without adequate training, that resource will be lost. When integrating BI, all staff should be informed to ensure all data points are connected and collected. By involving your entire staff, they may become aware of potential data points that have not yet been integrated, and thereby find ways to further enrich your data.

Training is essential for all those who will actively work with or contribute to the BI data and operations, whether their role is big or small. For example, say an electronic till is connected to the BI system and recording the sales, but a series of power cuts occur. All sales and returns done while the system was offline will reach the finance team, but if the finance team does not know how to communicate their offline sales to the IT team, that data will not be recorded in the reports, resulting in inaccuracies. Best practice would be to train your entire company as the first step toward encouraging a data-led culture.

4. Avoiding specialists

BI uses data and Artificial Intelligence to allow you to make smart, evidence-based business decisions within a shorter period of time. Data, AI and BI are all highly specialised fields of IT, so hiring a business intelligence specialist is strongly recommended. The implementation of BI into various systems can take time, particularly if there are a number of data sources to connect and integrate, and this is a complex process best performed by a professional who understands how to integrate your systems.

Once the initial implementation is complete, the BI platform should provide an intuitive, automated system that reduces effort and maximises the time available to employees for human-centric tasks. Theoretically, the system will run itself and you will have the answers you need. However, specialists can update the system as technologies advance, and quickly integrate new data sources or company programmes as and when they are added into your business. If your business objectives or queries change, a specialist can refocus onto the appropriate data and enable insights into different areas of the business.

5. Choosing Excel over BI platforms

There are a wide range of business intelligence tools available, but Excel is certainly not purpose-built for this task. Best practice would be to avoid Excel, particularly for critical data, as it has a tendency to lose data and throw up error messages in its place. There are plenty of BI platforms out there to choose from, which have been engineered to preserve and protect data

To learn more about which BI platform to use, click here.

Best practices for business intelligence

Business intelligence is a vast topic, so it can seem hard to understand at times. However, the information, efficiency and automation it provides renders it well worth the time and effort. Now you’re aware of the five common mistakes above, let us conclude with some of the best practices in BI.

1 – Only collect the data you truly need and can justify, and ensure it is gathered from as many reliable sources as possible. This includes your company’s own website and social media accounts.

2 – Have a robust company structure in place to ensure you know exactly what information you need from the data, and why. Promote a data-driven culture in your company.

3 – Train your employees in at least the basics of the systems they will be using, or gaining information from. They need to know what data is, where it’s gathered from, why it’s been gathered, and why it’s important. They can only help enrich and utilise your company’s data if they understand how to do so.

4 – Hiring a specialist to implement and maintain your BI system is strongly recommended, to ensure an efficient and reliable setup which can be updated and adapted as time goes on.

5 – Use a purpose-built business intelligence platform to protect and preserve your data.

To get started with business intelligence for your business, simply post your project requirements on Pangaea X’s platform for freelance data, AI and BI specialists.

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