Business analytics give everyone from project managers to C-suite executives the ability to make better business decisions. Such tools turn otherwise unintelligible data – on customers, trends, products, and more – into valuable insights that facilitate astute decision-making and financial success.
For all their popularity, traditional KPI dashboards and business intelligence (BI) tools have their limitations. Developing management reports or analytics dashboards is labor-intensive, and the subsequent information tends to be high-level summary data, pertaining to only a few key metrics. In fact, according to recent research, nearly half of enterprise decision-makers reported that the quality of data-based insights has decreased or plateaued over the past three years. Such is the symptom of KPI and BI systems that aren’t sufficiently scalable to handle the explosion of big data and the subsequently skyrocketing number of relevant metrics.
Traditional dashboards also usually present historical rather than real-time data. Historical data, while useful in observing trends over time, is rarely sufficient to inform decisions in the moment. Simply put, by relying on BI dashboards that don’t offer real-time, in-depth analytics, businesses are making decisions based on incomplete information – like a general fighting the proverbial last war.
Here’s how the proliferation of AI-powered analytics solutions is making business intelligence more intelligent than ever.
A Data Analyst in the Cloud
Roughly 80% of enterprise decision makers continue to rely on their number-crunching colleagues to manually perform data analysis and present their findings. The remaining 20% utilize enterprise BI applications, which, as we’ve said, are rarely up to the task.
What these dashboards lack are AI-powered analytics – an enhancement to dashboards that can seamlessly adjust automatically to encompass all relevant business data at any given moment. These analytic tools use autonomous machine learning (ML) to monitor vast quantities of data metrics in real-time, allowing companies to observe everything and detect anything, even trends they didn’t know they needed to look for – affably nicknamed the “unknown unknowns.”
By working with an AI-powered “data analyst in the cloud,” decision makers can closely monitor the minutiae of business operations as the organization evolves – details with often significant cascading effects.
Working with Data in Real-Time to Accelerate Decision Making
AI-powered analytics, with the ability to adapt and learn, are uniquely suited to understanding real-time data from multiple data sources. ML algorithms can spot outliers across this vast data, allowing decision makers to discover and address issues as they are happening rather than after the fact. They can then make near-instantaneous corrections, minimizing the potential negative impact to the business.
ML algorithms can also discern which anomalies are actually positive outliers, which indicate that something uniquely beneficial is happening and therefore do not warrant correction. Business leaders can quickly embrace these otherwise-unnoticed new trends and maximize the potential of any positive insight.
For example, take a case where a celebrity is endorsing a product on social media. The positive buzz generated by this mention can instantly drive up sales of that product, and if the business identifies this and responds in time, they can capitalize on the free attention. A large apparel conglomerate learned this lesson the hard way when their BI team discovered a celebrity endorsement days after it occurred. Had they discovered the sharp uptick in sales and the rapidly dwindling inventory in one of their regional warehouses in real-time, they could have capitalized on the opportunity by increasing the price or replenishing the inventory to keep the customer demand fed.
Working with Metrics on a Vast Scale:
Standard KPI dashboards typically track and present information on just a few-dozen metrics. AI-powered BI solutions can handle billions of metrics at once – a staggering scale that would overwhelm even the most adept of human analysts.
More metrics mean greater granularity of insights and more points of entry into understanding the business environment – i.e., invalid traffic, performance hindrances, minute changes in consumer behavior, and many other conditions that result in lost revenue.
Moreover, working with a vast array of metrics simultaneously can reveal related data-points that may not be obvious on the surface. But the only way to identify these subtle cause-and-effect trends is through such AI-powered analytics, which can automatically correlate metrics from numerous sources and uncover previously unknown relationships among data from across the entire breadth of business operations.
Don’t Predefine the Outcome – Let Data Tell its Own Story
Traditional dashboards typically require that a business sets pre-determined alerts to flag important issues. For these alerts to be effective, businesses must know what to look for before they even find it – a time-consuming and error-prone process. The ability to uncover previously unexpected insights in any set of data is a clear benefit of using AI-powered analytics.
AI-powered analytics can independently identify anomalous behavior and new trends without predetermined parameters, enabling executives to make more informed decisions without predefining what they want the data to reveal.
For example, a media giant was having difficulty discovering crucial incidents in their online business. The company had been relying on Google Analytics’ alert function to flag important issues. However, they had to know what to look for in order to set the alerts. This was a time-consuming and error-prone process, especially with millions of users across dozens of professional publications.
For the media company’s analytics team, spotting this issue would have required knowing what to look for in advance. After discovering this activity using AI-powered analytics, the company was able to block the spam traffic and free up critical resources for legitimate visitors. They were then able to accurately track the traffic that mattered the most, enabling business executives to make more informed decisions.
Putting Insights in Your Sights
With a truly intelligent business monitoring solution in place, companies can automatically find real-time hidden signals in multitudes of metrics, and action can be taken immediately – minimizing the negative impact of any given issue and amplifying positive trends as effectively as possible.