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SmartData Collective > Big Data > Why Business Intelligence and Design Theory Must Merge
Big DataBusiness IntelligenceExclusive

Why Business Intelligence and Design Theory Must Merge

Ryan Kh
Ryan Kh
6 Min Read
business intelligence design theory
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The term business intelligence was coined by IBM researcher Hans Peter Luhn early 40 years before the World Wide Web became a mainstream platform. Of course, it has evolved significantly over the past half century, largely due to advances in digital technology. Cloud computing and big data are also driving the future of business intelligence in unexpected ways.

Contents
How Does Design Affect Business Intelligence?Design Considerations Should Be a Central Part of Your BI Model

While the technology behind business intelligence has evolved in unimaginable ways, many brands still haven’t updated their strategies accordingly. Andy Cotgreave, a consultant and contributor for Computer World, says one of their biggest mistakes is failing to seamlessly incorporate the right designs into their business intelligence models.

How Does Design Affect Business Intelligence?

Most people believe that design and business intelligence as separate functions. Cotgreave states that business intelligence and design are closely intertwined, so brands need to use them together to create a competitive advantage.

There are several ways that providing a better design benefits your BI.

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Collect More Actionable Data on Customers

You can’t collect actionable data on your customers without getting them to interact with your platform. Your platform needs to be inviting and user-friendly.

“The second level of processing is behavioral,” Cotgreave writes. “When someone wishes to use an everyday thing, such as a door at an entrance to a building, they have an objective (enter the building). Using that object, can he or she successfully complete the task at hand? Are the things the object can do apparent and obvious? Don Norman shares many failures in the book, including examples of poorly designed doors where a lack of hinges and push/pull signs thoroughly confuse people.”

Improving your design improves both the amount and quality of your data in several ways:

  • More customers will be able to use your platform.
  • Customers will engage with your platform for longer periods of time.
  • They will be able to access key features of your platform, which are necessary for gathering data.

The UX design plays a larger role than you may expect, so make sure it is properly executed.

Design Improves Engagement With Offline Strategies

Every online marketing and data research campaign requires a great design. However, a great design is equally important and more overlooked with many offline strategies, such as trade show marketing.

If you are using lightbox displays, you need to use the right aesthetics to engage your customers long enough to collect data. Using the right trade show displays can have a profound impact on the success of your campaigns.

Designing a More Easily Implementable BI Dashboard

The front-end design isn’t the only factor that influences your BI model. You also need a well-constructed back end model to access your BI data.

The evolution of big data and cloud computing has made it easy for brands to collect, extract and organize any data they need in a matter of seconds. However, this technology is useless if your BI dashboard isn’t designed with these considerations in mind. In 2008, Mike Psenka of CRM Magazine wrote that new BI dashboard designs were necessary to ensure anyone could access BI when needed.

“Most enterprise-level business intelligence (BI) platforms are too complicated for the average user to employ effectively. As a result, these tools are often exclusively used by small groups of trained technology specialists — despite the fact that individuals at all levels of the enterprise make more-efficient, informed decisions if they have direct access to data mining, reporting, and analysis capabilities. The limited accessibility of these offerings prevents organizations from fully leveraging their BI investments.

To empower a larger pool of decision-makers, BI platforms must possess a self-evident, customizable user interface (UI). In fact, they must become more user-obvious — and there are four design considerations that are paramount in achieving user-obvious status. Incorporating these elements as tenets of BI architecture may start to debunk the widely held industry belief that BI capabilities can only reside with a privileged few.”

Unfortunately, poor BI interface designs are still a problem in 2017. Ensuring the functionality of your dashboard isn’t enough. You must also:

  • Make sure the system is easily navigable by anyone in your organization, even if they don’t have a background in data analytics.
  • You must make sure anyone using the interface can easily access and filter the data that you need.
  • The interface shouldn’t have unnecessary features that confuse or overload the user.

Creating a simpler, yet more effectively designed BI dashboard can significantly improve your BI model.

Design Considerations Should Be a Central Part of Your BI Model

When it comes to developing a BI model, too much emphasis is often placed on data. While data is undoubtedly a key aspect of business intelligence, design elements are also very important. You need a front-end design that encourages interaction with your users and a BI dashboard design that is easy to use.

TAGGED:business intelligencedesign theorydeveloping BI model
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ByRyan Kh
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Ryan Kh is an experienced blogger, digital content & social marketer. Founder of Catalyst For Business and contributor to search giants like Yahoo Finance, MSN. He is passionate about covering topics like big data, business intelligence, startups & entrepreneurship. Email: ryankh14@icloud.com

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