Seven Poor Practices Affecting Your Business

Business intelligence (BI) applications are gradually becoming the basis of many organizations today, big or small. Then, there is a problem. When some BI software collates data and warns you of possible business issues, it is your onus to take action. This is where most businesses falter; they often overlook the signals from the BI tools or simply are unprepared to take the right steps when the problems look at the CEO’s face. In simple words, many businesses stick to poor BI practices that affect their operations adversely. 

Many organizations misuse BI, thus making it less effective or fully ineffective. In this blog article, we are going to walk through the seven poor BI practices that could affect your business in a bad way. Read on to learn more.

1. The use of Excel as a business intelligence tool

Did you know that most businesses even today use Excel as their BI instrument? To be candid, Excel is a bad BI tool. Some experts in the industry do not consider it as a BI instrument at all and for all the valid reasons.

Excel is ineffective because pulling out system information and then manipulating or formatting that data takes much of your time, many times requiring hours or days to pull out all data. An effective BI application places data at your fingertips so that you can access useful information and make informed business decisions without any additional time and effort.

Excel data is also prone to mistakes. With more people accessing Excel, the chances of erroneous entries increase manifold. A study revealed that 80 percent of Excel data has considerable mistakes, which is the last thing you would want.

Excel is not secure. Both business and customer data are at risk because you do not who will share the spreadsheet with whom. You cannot make out how many employees modified the data.

2. Focusing on un-actionable information

There are two kinds of un-actionable data. Your business has actionable data that you are not ready to take the right action. Again, you have the second type of data that you cannot drive any action. These are called vanity metrics, the data making you feel great, but does not prove useful in bringing about any change for the benefit of your business. It is as simple as that. Therefore, before you measure any factor, make sure you ask, “Is this data useful?” “What we should do with such information?”

3. Giving access to BI data to all at once

It is one of the common blunders businesses make, giving access to BI data to all people at the same time. If some employees are not using the system or do not need to see the information, avoid providing access to them. When you give access to BI data, ensure the employees accessing it are trained in the right way and proper compliance exists in your organization.

When it comes to proper governance, it must make certain that all assets are used, based on agreed business strategies as well as processes. Governance should ensure the apt management and maintenance of assets. Moreover, these assets must support your business strategies and goals now and in the future.

Today, when more and more businesses are switching to the cloud environment, it might prove challenging to ensure complete control when it comes to the placement, de-provisioning, as well as infrastructure operations. It is one of the key reasons to involve your IT team in choosing, brokering, and administering BI applications or tools. You also need to work with a partner that offers BI support tools and solutions to make sure you are implementing the best practices.

4. Using BI data backward

Many businesses use BI data backward or they use it to validate a pre-existing situation. The businesses make their decisions initially, and then they go back, discover data to validate their decision. It is a serious mistake and fails the entire purpose of BI data for your organization.

According to experts in the industry, your business must avert BI results to validate and highlight pre-existing situations.

5. Not implementing automation or failing to do so

When you take some action based on BI data, it is fine. Again, allowing such data or information to take some action for your business is even better. Think of this situation, when your BI application shoots you an email or for that matter, some text message when certain particular information or data reached a pre-definite level. Isn’t it simpler than performing all tasks manually? Yes, automation in business always makes things simpler and convenient, and therefore, if you are not using automation, you are wasting much of your time.

When inventory is low at one of your business locations, you can create an order for authorization, and once approved by the business manager, the order is processed automatically. If you find the sales figures low in a specific area, all you need to do is right-click on the chart and initiate a call to the area manager to discuss sales figures and take necessary steps. Therefore, implement automation for the benefit of your business.

6. Making things right at the start and then leaving it

Your BI is not perfect all the time. If you think so, you are mistaken. When it comes to big data, it gives you real-time information so that you can make amends right away when you notice some trend is materializing. Change is the right word. Your competition, market, target audience, organization, and the landscape of your business matter. In the same way, your BI will have to. Stay agile by focusing on your drawing board periodically. You need to scrape entire dashboards sometimes, and then implement new strategies based on your BI data. It is the key to the success of your BI implementation in your organization.

7. More focus on forecasting at the cost of understanding

The success of BI is when you can make better business decisions. The data helps you get a better understanding of your enterprise operations so that you can make improved decisions in the days to come. Then, some businesses make the blunder of using BI as a forecasting application or tool without taking time to understand data. For example, you cannot see sales-related data and predict a 15 percent increase in sales without figuring out what are the essential factors that helped in driving sales. 

Final words

When you have a business to run, you need to collate more data and understand the same. Applying BI data inaccurately will fail its whole purpose. Avoid these BI mistakes at all costs for the benefit of your business. 

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