More than half (54%) of business leaders cite cloud-based business intelligence (BI) as being vital to their current and future initiatives. For many of these leaders, the need for BI was fueled by the pandemic, which rapidly moved their operations online. For others, the movement toward BI has been more gradual. 

Either way, BI tools are here to stay, and they’re growing stronger and smarter by the day. In fact, BI is being paired with AI and machine learning tools, as well as ERP and CRM software platforms.

Today, we’re looking at the connection between business intelligence and AI. What new trends can companies expect as we round out the last quarter of 2021 and look ahead to next year? Also, how can you develop a strategy to take advantage of these technologies?

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Modern Data Analysis

Data analysts have a tricky, albeit critical, job function. They must organize and sort through massive amounts of data, mine it for insights, and report on the findings.

This data analysis can be slow and ineffective. In a world where executives need critical insights in real-time, it can be far too laborious to sort through information to spot trends and make predictions.

AI makes this process much easier. Analysts can quickly spot anomalies in their data and identify critical situations that require immediate attention.

AI also provides what’s known as “prescriptive analytics.” This enables organizations to input hypothetical scenarios and allow the AI to calculate possible outcomes and suggest alternative solutions.

In order to perform any of these functions, AI needs access to data sources, such as your ERP system, cloud applications, IoT devices, mobile devices, etc.

As AI-enhanced business intelligence systems become more advanced, it’s expected that data analysts will not be the only ones who know how to use them. The average business user will be able to perform sophisticated BI functions with just one click. From forecasting to predictive analysis, users can perform a variety of functions within a user-friendly interface.

From Dashboards to Stories

Data insights are only beneficial when users understand their significance. While BI systems have long been able to generate interactive dashboards filled with numbers, they looked more like a foreign language to most stakeholders. The reports might be colorful and sleek, but what do they really mean?

Newer BI systems, especially those that are augmented with AI capabilities, deliver more than just sets of numbers. They can identify trends, spot outliers, and find patterns in large quantities of data. As a result, analysts are left with more than just raw outputs.

Now, they can more clearly understand how those points work together to tell a story. How do the findings affect our enterprise-wide strategy and what can we learn from them?

As we move away from generalized findings and obscure stats, it’s this type of well-rounded visibility that will move a business forward. 

Advancements in Natural Language Processing

Performing a data search query might be a walk in the park — if you’re a trained data scientist. However, everyday users have yet to tap into this technology to ask simple questions and get quick answers. 

Newer BI systems are integrated with AI technology that facilitates natural language processing. While speech-to-text devices have made use of this function for years, most BI systems haven’t followed suit. As a result, operability has been limited to experienced team members who know how to manipulate the technology to get the insights they need.

With the addition of AI, these systems are making impressive leaps toward a more accessible, user-friendly interface that allows virtually every employee to make use of the intelligence at their fingertips.

While the functionality still has a long way to go until it’s error-free and accurate, it’s an exciting prospect. 

ERP and CRM Integration

Another way that BI and AI are working in tandem? Take a look at some of the top ERP systems and CRM platforms. While some vendors are developing these intelligence functions organically, others are enhancing their systems via BI acquisitions and mergers.

What benefits can these technologies offer? They help companies streamline and simplify their workflows by integrating all their disparate systems. When these systems are “speaking” to one another, it becomes much easier to share data and collaborate on projects. 

Another advantage is that many business processes can also be automated through AI/BI integration. This reduces manual work, increases speed, and improves overall employee performance. 

Real-Time BI Operation

Traditionally, BI technologies are utilized on a routine schedule. For instance, an analyst might pull a specific report every Friday afternoon, or the 15th of each month.

This means that real-time needs often go unmet, and data may not be available to support urgent strategic decisions. This is where a new type of BI, known as Operational BI or Operational Intelligence, comes in. With this approach, BI is treated as an around-the-clock effort, rather than a task reserved for certain time periods.

It’s also more encompassing, gathering inputs on everything from consumer buying behavior to supply chain disruptions.

With these insights, a BI system can be set to refresh every few hours or at another fixed interval. This way, needs don’t go unmet, and executives can make quicker, better informed decisions. 

How to Define a Business Intelligence Strategy

Before you select a BI solution or an ERP system with BI functionality, you should develop a business intelligence strategy so you can evaluate AI functionality in light of your business needs. Here are five steps that will prepare you for the ultimate AI and BI mashup:

1. Determine Key Stakeholders

Contrary to popular belief, the IT department isn’t the main stakeholder in a BI initiative. Business intelligence should be owned and accessed by all areas of your organization. Executives, of course, have a vested interest in business intelligence, but so do department managers.

2. Assess Your Current State

What is your current portfolio of enterprise systems and your current IT infrastructure? What are your current business processes? Answering these questions will help you determine what’s working and what’s not.

For example, maybe you’re storing data in multiple places, but you need one version of truth. Pain points like this are an opportunity for improvement to include in your business intelligence strategy.

3. Set KPIs

You probably have more data than you know what to do with. You can prioritize this data by determining what KPIs you need to track based on your business goals. Creating a data dictionary can help you align stakeholders when it comes to calculating and interpreting different KPIs.

4. Evaluate Your Options

Your organization might need an entirely new ERP system with enhanced BI functionality and advanced AI. Alternatively, you might need a BI solution that fits with your current best-of-breed portfolio.

Other variables to consider include scalability, level of customization, and on-premise vs. cloud deployment.

5. Obtain Buy-In

Business intelligence is only beneficial if employees use it. They won’t use it unless they know how and understand why it’s important.

Once you have executive buy-in, you should develop a change management plan to help employees understand why you’re investing in a new BI solution. This plan should also address cultural barriers and end-user training.

The Future of Business Intelligence and AI

For years, business intelligence systems have helped companies make better sense of the data that passes through their organizations. However, that intelligence was largely unactionable and only accessible to those with an advanced background in data science and analytics.

The merger of business intelligence and AI opens new doors for organizations. Now, business users across departments can not only access data points, but they can apply them to their specific job function. This functionality is made even more powerful when integrated with ERP software

Many analysts are hoping to convince executives to invest in advanced analytics, but this can be a hard sell. Our enterprise software consultants can help you develop a business case and convince your boss to invest in AI-driven BI. Contact us below for a free consultation.

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