13 Creative And Productive Ways For Companies To Combine BI And ML

Business intelligence and machine learning can be powerful tools for companies—and even more powerful when they’re combined. They are, indeed, an ideal pairing: The data analysis that is the foundation of business intelligence can be streamlined and sped up through the ever-improving processes of machine learning, giving companies valuable insights and information faster than ever before.

Together, this blend of processes and technology can help companies improve across a range of areas, from customer service to cybersecurity. Below, 13 industry experts from Forbes Technology Council share creative ways a company can leverage a combination of BI and ML. 

1. Answering Established Questions

To leverage the combination of BI and ML, we must focus on the question to be answered first, then go get the data and build the dashboards. Too often, we focus on gathering massive amounts of data, but focusing on the question to be answered informs all else (for example, how often to collect data, the needed format and the type of data required to provide answers and insights). A good example of this is medical staff asking, “Should we admit this patient?” That is the question to answer and the decision we need BI and ML to deliver. – Christopher Larkin, Concord Technologies

2. Detecting And Prioritizing Cybersecurity Alerts

In cybersecurity, a well-designed model, output and interface can be the difference between detecting a threat or missing one. The modern security operations center processes terabytes of data each day. The combination of machine learning and business intelligence provides insights that can reveal hidden patterns in massive datasets, allowing real-time categorization and prioritization of alerts for security analysts. – Kevin Lynch, Optiv


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3. Improving Existing Processes

The key to the successful adoption of machine learning is to integrate it into workflows, systems and processes that are already in the hands of business users. For instance, integrating ML into existing planning and forecasting processes and leveraging corporate performance management and BI tools to analyze the results of ML models can lead to more effective decision making. – Tom Shea, OneStream Software

4. Rapid Analysis Of Large Data Sets

Machine learning can help business intelligence professionals process a large amount of customer data—especially unstructured data, which would be nearly impossible to process manually. This combination can orchestrate faster and more accurate insights into customer expectations and intent, thus enabling better decisions to significantly improve customer experience. – Vasudeva Akula, VOZIQ

5. Automating Burdensome And Tedious Tasks

BI and ML are a powerful combination when trying to find optimal solutions to known problems. ML is often talked about as some kind of magical way to uncover untapped gold, but the reality is that ML is most powerful for automating tasks that humans either aren’t very good at—such as sifting through and understanding the relationships between data sets—or are easily bored by. – Alexander Hill, Senseye

6. Tracking Employee Morale

In every company, a huge amount of “words” flow through daily. Marketing departments have used sentiment analysis for years to identify issues with their company’s brand, but the most forward-thinking leaders are turning this inward, identifying the mood of their employees by using the company’s productivity software to anonymously identify pain points. – Heather Wilde, ROCeteer

7. Improving The Customer Experience

Customers have become more demanding, and their expectations around timely, quality interactions have increased. Harnessing the power of BI and ML can provide a huge advantage when it comes to improving the customer experience. Every business generates powerful data; now the tech can analyze that data and apply the results to help predict customers’ needs and support them in real time. – Pete Hanlon, Moneypenny

8. Anticipating Hackers’ Methods

Let’s reverse this and look at it from the perspective of a cyber attacker. We’re seeing more hackers use AI to scrape company details to engage in personalized spear-phishing campaigns. With the rise of ransomware and increasingly sophisticated cyberattacks, businesses can learn from the ways attackers are innovating and copy that out-of-the-box thinking by using BI and ML when establishing their own cyber defenses. – Ian Paterson, Plurilock Security Inc. (TSXV:PLUR)

9. Predicting Customer Behavior

We’ve seen smart firms analyze product usage data to identify both highly engaged customers who are ripe for upsell and poorly engaged customers who present churn risks. The next step would be using machine learning to pattern-match for telltale signs of customers poised to become either power users or churn risks and addressing those accounts’ needs immediately while identifying repeatable strategies to grow engagement tomorrow. – Rich Waldron, Tray.io

10. Spotting Anomalies In Real Time

Machine learning gives companies the ability to spot real-time anomalies, which can support anything from mitigating cloud overspend to stopping security breaches before they spread. Business intelligence provides a historical record that may illuminate important, relevant context. Ultimately, combining the two helps companies make rapid, informed decisions that support stability and longevity. – Kim Huffman, Elastic

11. Prioritizing New Product Features

Combining BI and ML to review a product backlog can help a company determine the priority of the best next product features. This will help your team focus and deliver a product your customers want, and it decreases waste and increases revenue opportunities. Additionally, this strategy aligns an organization around a single shared vision. – Thomas “Ai Nerd” Helfrich, System Soft Technologies

12. Streamlining High-Volume Processes

If implemented correctly, business intelligence, machine learning and AI tools can help a company streamline its contracting process, gain efficiencies and provide mission-critical business insights. By cutting the time and resources spent on contract review and drafting, these tools provide significant value, both to companies with a high volume of contracts and companies with more routine transactions. – Olga V. Mack, Parley Pro

13. Implementing Digital Twins

For the past year, the chip shortage has impacted industries across the board with varying degrees of severity. This challenge presents an opportunity to leverage one creative way of combining BI and ML: digital twins implementation. The concept of digital twins uses BI and ML to run simulations and predictions to help businesses improve their decision-making while navigating the shortage. – Nicola Morini Bianzino, EY

https://www.forbes.com/sites/forbestechcouncil/2021/11/03/13-creative-and-productive-ways-for-companies-to-combine-bi-and-ml/

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