Baby Steps: The Adoption of BI & Analytics

The explosion of big data has fueled companies’ search for better ways to beat their competitors and please their customers via business intelligence and analytics. Buoyed by cloud computing and advanced analytics capabilities, the business intelligence market is projected to reach $26.9 billion in 2021, growing by more than 50 percent in just 5 years.

Despite major recent advances in the BI and analytics field, however, adoption has been lagging behind. According to Gartner, even with modern self-service BI and analytics tools with mobile and embedded capabilities, user adoption has only increased 7 percent over last 10 years.

These slow adoption rates continue to hold companies back, preventing them from finding constructive insights and making smarter, data-driven decisions. This article will discuss why organizations must focus on adopting BI and analytics, and how they can work to expand the role of BI and analytics.

Why BI and Analytics Must Be a Business Priority

Collecting data is a necessary, but far from sufficient, condition for getting real analytical insights. Business intelligence is the art and science of turning mass quantities of raw data into usable, valuable information for the enterprise. Mature, sophisticated BI solutions allow users to discover historical trends and find hidden connections between different facets of the business.

BI and analytics also improve the visibility of each component of the business, providing a centralized platform from which users can observe all of the goings-on within the organization. This makes it easier to identify areas that are performing well or underperforming, and to understand the most efficient allocation of resources.

Automated BI software programs can crunch the numbers orders of magnitude faster than any human analyst, giving the entire company a massive productivity boost. As a result, employees will spend more time making the business run and less time worrying about the best way to analyze it.

How to Expand BI and Analytics Within Your Organization

Each company travels its own path towards widespread adoption of business intelligence and analytics. However, there are a number of recommendations for adopting BI and analytics that have served enterprises of all sizes and industries well:

• Meet your business goals: Don’t get caught up in flashy BI software that tries to promise you the moon. The right BI and analytics solution for your business is the one that best fits your needs and objectives. Understand your users and their requirements – for example, managers and executives may want to see dashboards with key metrics and the overall health of their business operations, while business analysts are looking to explore data and gain insights from trends and anomalies.
• Performance matters: Sometimes it’s easy to think that you’ve come across the perfect BI solution: the features are exactly what you need, the price is reasonable, and it’s even mobile-friendly for your workers on the go. If the software isn’t easy to use and doesn’t perform well in production, however, users won’t be willing to adopt it. Large volumes of data and high numbers of ad hoc queries are just two issues that can negatively impact performance. According to Gartner, ease of use is one of the primary factors that affects the adoption of a new BI solution.
• Create a single version of the truth: Problems with reliability and accuracy can plague BI solutions, causing employees to be wary of using them. By choosing a BI platform with capabilities for data cataloging and data governance, you can ensure that your data will always be accurate, complete, consistent, and up-to-date.

Final Thoughts

While many companies have a long way to go before widespread BI adoption, the benefits are well worth the effort. By selecting the right solution for your users and objectives, and focusing on a few important business outcomes, you can help usher in the deployment and adoption of a modern, intelligent BI and analytics platform within your organization.