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The benefits of predictive analytics, a core capability of enterprise AI, are far-reaching and potentially game-changing. According to AI company C3.ai, incorporating process predictive analytics into your business can drive significant improvements, including lower costs, increased margins and profitability, increased safety and reliability, and reduced environmental impact. can.
In an era where data is more abundant than ever, modern businesses are increasingly turning to predictive analytics as a vital part of their strategy. This month, industry experts from a variety of sectors highlight the transformative impact of this technology and provide insight into its benefits, challenges, and future possibilities.
Modern companies invest in predictive analytics as part of their business strategy
Bret Tushaus, vice president of product management at software development company Deltek, explains that every minute counts when it comes to business decisions. “Whether it’s predicting the likelihood of success for future projects a client undertakes, allocating the right amount of resources to a task, or evaluating which activities are cost-effective, views of results can take days. , you get it instantly, not weeks or days, even though it might be too late after months,” he says.
“Predictive analytics gives businesses the opportunity to regain time and resources, which is a critical business investment to keep pace with competitors. It also addresses staffing efficiency.”
In today’s competitive business environment, foresight is as valuable as hindsight. “As someone deeply involved in AI innovation and technology that optimizes internal processes, I can attest that predictive analytics is the cornerstone of modern business strategy,” says Web3, a 3-degree technology expert at recruitment agency Spectrum Search. Peter Wood, Founder and CTO commented: “Companies don’t just want to understand current data; they want to predict future trends, consumer behavior, and potential risks. Predictive analytics allows companies to be proactive, not just reactive. This proactive approach is similar to how a chess grandmaster plans several moves ahead, making it easier to navigate market complexities and stay ahead of the curve. Become.”
Predictive analytics for compliance
According to Wood, predictive analytics does more than simply provide a crystal ball of market trends. This is a powerful tool to ensure compliance. “The regulatory landscape is constantly evolving, and the costs of non-compliance can be significant,” he says. “When I advise startups in his Outlier Ventures accelerator, compliance is often a major hurdle to clear for sustainable growth.
“Predictive analytics can identify patterns and flag potential areas of concern before they become serious issues. Doing so allows companies to adjust policies and practices in real time and You can effectively avoid the pitfalls and their financial implications.”
Compliance is becoming more thorough as regulators expect companies to comply with more complex requirements and provide evidence of compliance, said Martin, professor of management practice at Frerick Business School.・Mr. Butler explains. “With the increasing digitalization of internal processes and interactions with customers and business partners, the scope of non-compliance has increased significantly. Predictive analytics data models and algorithms enable processes and data movement to be faster and more accurate. identification and monitoring, allowing us to quickly identify potential nonconformities and take immediate action.”
AI and data quality challenges
When building AI, data quality is paramount. As Tushaus explains, a predictive model is only as good as the data used to train it.
“Organizations need to invest in data collection, cleaning and preparation to avoid issues such as bias and misleading correlations,” he says. “Building and maintaining models requires advanced analytical skills, which are in short supply. Therefore, for companies where investing in the required technical knowledge in-house is prohibitive, leveraging off-the-shelf tools is , is a viable way to reap the value of predictive analytics. However, it can be difficult for organizations to learn about and successfully implement the tools available to them.
“To alleviate this challenge, companies must leverage the knowledge and involvement of a wide range of people across the organization. Knowledge about this technology can come from unexpected places within the company, and the use of tools It is important to ensure that those expected to be involved in the evaluation, selection and implementation.”
Companies are beginning to realize the benefits of predictive analytics
Today, businesses of all sizes are adopting predictive analytics, and industries are beginning to see early benefits in terms of additional time, resources, and business efficiency.
“Already a business priority, we expect to see even more investment in technology in the coming years,” says Tushaus. “In fact, our Clarity: Trends and Insights for Architecture, Engineering and Consulting Firms report shows that investing in new technology is a top priority for project-based businesses. As it continues to be used more and more accurately to estimate cost, schedule, and risk, more and more companies will realize its potential.
“Integrating predictive analytics across operations, combining predictive power with human experience, increases business value. As a result, this technology not only helps prevent budget and schedule overruns, but also improves the outlook for project success. projects are more likely to proceed in the first place. This could improve industry performance. Companies that do not take advantage of these capabilities could be left behind by the forecasting pioneers. It is no exaggeration to say that it is sexual.”
Meanwhile, Butler predicts that the most exciting trend in predictive analytics will be the power of AI across the entire data value chain. “AI helps with data ingestion, wrangling, and processing,” he says. “AI is creating customized visualizations for individual users at a scale never possible for enterprise analytics teams. Leverage AI to surface the right insights in a fit-for-purpose way. Self-service analytics is the ideal future of predictive analytics that is slowly becoming a reality.”
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