Most business leaders are familiar with the concepts of business intelligence and machine learning and know that these technologies have the potential to revolutionize their business operations. However, many of them don’t know exactly how to leverage these tools to their fullest potential. This intelligence gap can prevent you from capitalizing on countless opportunities.
The members of Forbes Technology Council are at the forefront of studying and adopting the latest technologies to improve their businesses. If you’re looking for creative uses of business intelligence and machine learning, check out their expert recommendations below.
1. Connect insights to actionable notifications and flows.
A creative way of leveraging business intelligence and insights—themselves derived from machine learning using vast amounts of historical data—is to connect those insights to actionable layers of business operations. This includes notifications and an automated flow of actions that can inform many of the business stakeholders, leading them to act on the gained insights. – Henry Peter, Ushur
2. Map out and neutralize threat patterns.
I believe the best use of machine learning in this digital age is preventing cyberattacks from happening at an early stage. We have been relying a lot on digital, which has made our lives easier yet more vulnerable. With the help of AI, machine learning, big data and threat intelligence, we can further understand and map out threat patterns to neutralize threats early.
3. Automate routine, repeatable tasks.
One easy starting point for applying ML is in automating routine and repeatable tasks. Many organizations are on a pathway for data maturity such that effectively applying business intelligence isn’t a near-term possibility. Leveraging ML to ease administrative burdens and automate tasks can help build up internal consensus for its return of overall business value. – Trisha Swift, ZeOmega Population Health Solutions
4. Make it easier for users to access and consume information.
Focus on the information consumers need to improve their processes. Whether it’s someone in an internal company role or an external customer, provide them with easily accessible, easy-to-consume information that is timely, accurate and has already integrated data from the various internal corporate systems to provide actionable information. The good news is technologies have evolved, and they should be embraced and shared. – Sherlock Holmes, Genware Computer Systems Inc.
5. Rethink your payment processes.
Thanks to ML, leaders are rethinking their customer relationships when it comes to ordering and payment. Traditionally seen as siloed or back-office processes, finance and sales have been transformed by ML into a unified operation. With ML-powered order-to-cash processes, you get predictive analytics, better cash forecasting, and ML-generated selling and dunning strategies that increase the top and bottom lines. – Rob Harvey, Sidetrade
6. Leverage advanced predictive analytics.
The speed of innovation and AI’s sizable economic impact will render businesses that are ignorant of their opportunities obsolete. Business leaders should therefore keep up with the sheer speed of innovation and make quick investment decisions in technology. The one creative use of BI and ML that leaders can benefit from is to turn data into efficiency through advanced predictive analytics. – Julian Jewel Jeyaraj, Julian Jewel’s AI Bot (JJAIBOT)
7. Find, prioritize and deliver tasks.
AI and machine learning have simplified our personal lives to the point that in many cases, we don’t even need to think. They can do the same for us at work. They can find and prioritize tasks and automatically deliver them—along with the insights and information we need to execute—to eliminate tasks that frustrate us and allow us to focus on meaningful work that keeps us engaged and productive. – Meerah Rajavel, Citrix
8. Improve the customer experience.
Improving customer experience is one area that will greatly benefit from machine learning and BI. Leaders can apply analytics to predict customers’ support needs in real time, identify the root cause of service-impacting issues and more efficiently triage outages. The data is being generated, and the tech is available to analyze it. Most importantly, customers are demanding five-star experiences. – Chris Menier, Vitria Technology Inc.
9. Personalize experiences through identified behavioral patterns.
ML identifies patterns in behavior that are otherwise difficult to see. In healthcare, this might mean identifying risks of diseases before a patient shows symptoms. In retail, it means doing better than “people who bought this also bought that” recommendations. Personalized suggestions timed to the customer’s needs on the channel through which they most want to be reached is what ML is for. – Kevin Parikh, Avasant
10. Get to know your customers better.
For most companies, customers are their biggest assets. So I would focus on leveraging business intelligence and machine learning on customer data. Once the data is available in a single consolidated platform, businesses can get a 360-degree view of customers using BI. Companies can then look at AI models like customer lifetime value and churn. The outcomes will be improved by customer satisfaction. – Yasim Kolathayil, HGS Digital
11. Vet your job candidates.
We leverage deep learning and artificial intelligence to help vet engineering candidates for remote work. Today AI, ML and BI can combine to evaluate far more than simply test scores. We use AI to compare performance on tests as well as how—and how fast—questions are answered to understand how skilled a developer is. We then find matches where they’re most likely to succeed when placed. – Jonathan Siddharth, Turing
12. Innovate your back office.
Machine learning is a significant driver of innovation for back-office teams like finance that are modernizing their tech stacks. Just as today’s marketing teams rely on “martech” to operate more strategically and efficiently, finance departments are seeing emerging technologies like machine learning become part of daily processes. – Michael Praeger, AvidXchange
13. Forecast and adapt to demand.
In the current environment, machine learning can provide demand forecasting using self-learning to rapidly adapt to unstable conditions, learning from prior accuracy and/or inaccuracy. This is especially helpful when past trends are not as predictive of future trends as expected. We use this to predict where our efforts will be most rewarded now. – Nina Vaca, Pinnacle Group, Inc.
14. Tap into real-time intelligence.
While business intelligence has been around for a while, the new era is all about real-time intelligence. This means being able to use real-time data to create more engaging customer experiences. One creative example is real-time personalization where you can use real-time user behavior, combined with past transactions and lookalike customers, to create a personalized online shopping experience. – Shruti Bhat, Rockset
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