As more companies aim to drive strategy with data, Business Intelligence Tools (BI) becomes more and more integral to performance — across teams, departments, companies and wider ecosystems. The unprecedented ability to capture, store, analyze and disseminate data is changing the way enterprises are operating in both the short and long terms.
The role of BI in the modern organization is to inform better decision-making. What does “better” mean in this context, exactly? As one expert writes for CIO, high-value BI can help the decision maker by improving efficiency, power and accuracy — to name a few of the leading benefits.
Here’s more on how BI tools today directly enable improved decision-making by the workforce.
Connecting the Right People with Relevant Insights
The first challenge self-service Business Intelligence Tools are capable of addressing is how to get the right information into the right people’s hands within an effective timeframe on which to act.
Efficiency:
Companies used to have to settle for premade reports compiled by data experts and delivered to business users — a process that could easily take weeks or months with a backlog.
Modern Business Intelligence Tools aim to ramp up efficiency by connecting business users directly with interfaces to query data and create custom reports as needed.
Power:
These interfaces are also powered by platforms capable of bringing formerly incongruent data sources together, both from inside and outside the company. This helps alleviate delays and jurisdictional challenges caused by the previous, more siloed approach to BI.
The aim here is to help users access a wider variety of insights that could possibly help them in the decision-making process without bogging down the timetable or requiring extra legwork to chase down data stowed away in silos.
Accuracy/Relevancy:
Sometimes the first time is the charm when it comes to querying data. That is, someone knows what question they want to ask and how to ask it, meaning they can get the exact insight they need in seconds.
Other times, a query represents just the beginning of the fact-finding process. One question could lead to another… could lead to another, etc. Without the ability to access self-service tools, drill down as much as needed, and keep creating reports/charts, users may only be getting part of the picture.
Thus, modern Business Intelligence Tools fuel more well-rounded decision-making by helping users leave no stone unturned on their search for answers. After all, follow-up questions can be numerous and just as important as the original question — so interactivity is a must when it comes to accurate and relevant decision-making.
Pushing Insights & Recommendations via Machine Learning
Business Intelligence Tools and analytics systems today are going beyond allowing users to ask questions and create reports based on their findings, though. Advanced artificial intelligence (AI) analytics platforms are harnessing machine-learning algorithms “to provide interpretations and recommendations.”
Machine learning enables these tools to keep track of user preferences over time and spot potentially useful nuggets of information submerged in massive stores of data — insights that might very well be missed by humans, who are understandably busy and often seeking out specific insights rather than conducting exhaustive searches for these needles in haystacks.
By pushing these recommendations to relevant users, it gives them the ability to act accordingly or follow up without requiring them to do the manual legwork of digging for it. The more feedback they’re able to provide to the system, the better the machine-learning algorithms can hone relevancy, too.
Business Intelligence Tools are making decision-making better in a couple of ways, namely by connecting everyone with timely, interactive insights as well as using AI and machine learning to spot additional insights and bring them to awareness.