Our technological world changes by the minute, so it’s no surprise that business intelligence technologies are no longer limited to pre-set views, limited search and visualization features, and specific data sources.

But just because companies have options at their disposal doesn’t mean organizations are exploring those options. In recent years, some businesses have begun shifting from their on-premise hardware to cloud infrastructure while others are starting to leverage the latest BI tech.

But in most cases, it’s safe to say that companies haven’t reached that game-changing level with their business intelligence and analytics initiatives.

Below we’ll examine:

  • The top things companies miss out on when they neglect to implement modern business intelligence technologies into their workplaces.
  • Adoption roadblocks they’ll encounter.
  • How to get past those barriers and take advantage of new BI tools.

Top Things Companies Are Missing without Modern BI

Self-Service Insights

There are unlimited benefits when individual employees can use company data to find real-time answers to their questions. Historically, business intelligence software didn’t need to be all that user-friendly because only specific roles had access to them. But with natural language query (NLQ) technology, BI tools are self-service through text and voice search.

Some modern business intelligence technologies even allow for truly ad-hoc insights. Platforms like ThoughtSpot use in-memory calculation and fast query performance technology to analyze an enterprise’s data archive simultaneously and generate fast, accurate answers. When employees have access to this kind of technology, it results in an ongoing loop of search, analyzation, ideation and knowledge sharing.

Custom Visualizations

Looking at a sea of text-based data can be overwhelming for even trained eyes to analyze. When regular employees are expected to find information through complex data views, valuable findings are bound to be missed. Modern BI tools generate on-the-fly visualizations via charts, maps, graphs, tables and other interactive views to accelerate employee findings, as well as make it easier to share data and collaborate around it.

Self-Learning Data Assistants

No longer associated with trend pieces and dystopian forecasts, artificial intelligence (AI) and machine learning (ML) have arrived. Companies in industries ranging from retail and manufacturing to transportation, healthcare and more are leveraging these technologies to automate choice tasks and cut costs. The same is true in the data analytics space. New BI tools incorporate artificial intelligence to provide more insights and use machine learning to continue personalizing results to each user.

Multi-Cloud Capabilities

The days of a company having all their hardware on-premise are long gone. And while cloud technology might seem like the present-day based on our consumer lives, the business world hasn’t completely caught up. For companies to be successful in today’s dynamic business landscape, they need to have a multi-cloud strategy in place, especially for analytics.

Contemporary business intelligence tools integrate with more data sources and applications to reduce data silos and make information accessible through one interface.

Roadblocks to Modern BI Adoption (and How to Solve Them)

Company Culture Isn’t Based on Data

If an org isn’t prepared to communicate around data via one shared language, everything involving data will be more challenging to accomplish. Data fluency is a way of thinking about data, it’s a culture that starts with the C-suite and trickles down to every employee across the company. Data-fluent organizations cultivate cultures of continual learning. They use numbers to clarify discussions and save time. They share insights to foster collaboration. They make decisions based on empirical evidence instead of educated guesses.

Employee Won’t Adopt New Technology

Most employees aren’t accustomed to using data in their daily workflows. When companies try to introduce new BI technologies, it becomes apparent how much some people don’t like change. What’s more, employees who have a lot of experience in a role might prefer their hunch or business acumen to the cold hard numbers. This is because as humans, we don’t usually stray from the initial impressions we form.

Thinking we’re effective decision makers doesn’t make us good ones. That’s why achieving data fluency is so critical. All employees need to believe that the time spent searching and analyzing data will yield better results than critical thinking and the sum of their experiences.

Implementation Time Drags

Per BI-Survey.com, around one in ten BI projects can still take a year or more to complete. In general, implementation time increases with company size, but any organization can see its deployment spiral out of control if they fail to plan appropriately or forecast for setbacks.

Using an agile project management approach helps when implementing new BI technologies. But doing the homework ahead of time to structure data and choose a provider that integrates with a variety of applications should limit setbacks, at least the significant ones.

The business landscape is dynamic and complex for organizations of all sizes and industries. But instead of endless rolling hills with no landmarks or details to focus a gaze upon, modern business intelligence software gives companies an accessible and accurate way to mine insights and push positive business outcomes forward.