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Five Challenges to Overcome for BI Deployment Project

by | Oct 27, 2020 | Articles

Business intelligence (BI) is starting to get more attention and higher than before deployment projects. At the same time, companies of all sizes are also experiencing a number of challenges during BI deployment projects.

In this article, we’ll highlight the top five BI deployment challenges. If executives don’t take these challenges seriously, this can lead to a failure and the waste of company’s resources.

1. Poor data quality before BI deployment 

First and foremost is poor data quality. Regardless of a BI application, if you have low-quality data, you’ll face challenges.

A company needs to make sure that it has high-quality data before starting a BI project. If some parts of available data are poor, it’s better to go back and sort out the issues before anything else. When companies neglect the quality of their data and rush into projects, they will likely end up in trouble.

It’s important to understand and solve the root cause of this problem. This can lie in a lack of the proper data management policies across an organization. One of the ways to fix this problem is the integration of company-wide data collection, management and storing practices.

2. Too many data silos 

Some organizations have their data overly siloed and not accessible by other departments within the organization. This can be a big challenge, because one needs to have access to all the data in a company. When there are multiple permission levels and security settings, it can lead to inconsistent analysis and multiple versions of the truth.

“This is one of the hardest things to overcome because a lot of definitional work needs to be done spanning business functions,” said Cameron Cross, a technology expert from IT consultancy West Monroe Partners.

Often companies don’t have proper internal standards or different business units follow their own separate standards. This can lead to inconsistent data management and data silos, which can impair a BI deployment project. To avoid this, data management teams should break down silos and harmonize the data.

3. Lack of data-driven culture 

The two previous points are closely related to the lack of proper data culture in a company. The right data culture is essential for a successful implementation of BI.

“One of the ongoing challenges is around creating a data-driven culture, not just at the executive level, but at the front lines,” said Sudheesh Nair, CEO of BI and analytics software vendor ThoughtSpot.

To build that kind of culture companies need to provide workers with all the right tools. Companies should also empower them to apply the results of these tools in business processes. When implementing a BI project, it’s important to not only engage all business leaders in a company, but also include mid-level managers. This kind of inclusion into the project can drive a corporate shift toward prioritizing the right use of data and making data-driven decisions.

4. User training after BI deployment

Even best projects can be unsuccessful when management fails to provide proper training for end users. It can be hard for some end-users to master modern BI tools. Most people tend to take the path of least resistance and keep using old, familiar tools to perform their tasks. They may even understand the benefits of new tools, but old habits and the fear of new technology can result in low acceptance.

One of the ways to a smooth transition can be the use of tools within the same ecosystem, such as Office 365 and Power BI. People who already use Excel will likely find Power BI to be intuitively familiar than other BI tools. The similar layout, functions, and the options to embed Excel reports into Power BI can shorten the learning curve.

Another advice is to constantly monitor user activity to identity potential issues and adoption problems. These problems must be solved timely. The poor BI deployment, when end users are left alone without proper training, can lead to a chaotic environment and confusion. As a result, this leads to the abandonment of the new technology.

5. Bad visualization and design practices 

Humans rely on visual imagery more than anything. When visualizations are poorly designed, it is hard to understand information they’re trying to tell. At the end of the day, a BI dashboard is only useful when a reader can quickly understand and navigate through the information.

That is why it’s essential to think about the right design and UX every time you’re build a report. The general rule should be the easier the better. Dashboards that are cluttered and show too much information can quickly become unreadable and, therefore, useless. With the increasing popularity of mobile BI applications this becomes particularly important.

Overall, BI managers should find the right balance between simplicity and complexity. They must also promote the data-driven culture, ensure proper data management, and provide security all at the same time.

When it comes to demonstrating the value of BI applications, it’s necessary to engage end users and show quick results as fast as possible. Together with training and continuous product improvement, a new BI tool will eventually stick and become a key part of a company’s technology stack.

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BI
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