AI-Powered Predictive Analytics Driving Business Success
A core function of enterprise AI, the benefits of predictive analytics are wide ranging and potentially game changing. According to AI company C3.ai, when embedded in business, processes predictive analytics can drive significant improvements such as reduced costs, increased margins and profitability, better safety and reliability, and lower environmental impact.
In an era where data is more abundant than ever, modern businesses are increasingly turning towards predictive analytics as a pivotal element of their strategy. This month, industry experts from various sectors highlight the transformative impact of this technology, offering insights into its benefits, challenges and future potential.
Modern businesses investing in predictive analytics as part of their business strategy
As Bret Tushaus, VP of Product Management at software development company Deltek explains, when it comes to business decisions every minute counts. “Whether it’s forecasting the likelihood of future project success to take on a client, allocating the right amount of resource to a task, or assessing which activities are cost efficient, a view of the outcome is available in moments, rather than days, weeks or even months down the road when it might be too late,” he says.
“Predictive analytics hold the opportunity to give businesses back time and resource – a crucial business investment to maintain pace with competitors. With businesses navigating not only the cost of doing business in a global downturn, it also addresses staffing efficiencies.”
In today's competitive business environment, foresight is as valuable as hindsight. “As someone deeply involved in AI innovation and technology that optimises internal processes, I can attest that predictive analytics has become a cornerstone in contemporary business strategies,” comments Peter Wood, three-time tech founder and CTO at Web3 recruitment company Spectrum Search. “Businesses aren't just looking to make sense of their current data; they aim to predict future trends, consumer behaviours, and potential risks. Predictive analytics allows companies to not just react but proactively adjust their strategies. This proactive approach is akin to a chess grandmaster planning several moves ahead, making it easier to navigate the complexities of the market and stay ahead of the curve.”
Predictive analytics for compliance
According to Wood, predictive analytics doesn't just offer a crystal ball for market trends; it's a powerful tool for ensuring compliance. “Regulatory landscapes are constantly evolving, and the cost of non-compliance can be crippling,” he says. “When I advise emerging companies at Outlier Ventures accelerator, compliance is often a major hurdle they need to clear for sustainable growth.
“Predictive analytics can identify patterns and flag potential areas of concern before they escalate into significant issues. By doing so, companies can adjust policies and practices in real-time, effectively sidestepping legal pitfalls and the financial repercussions they carry.”
Compliance is becoming more exhaustive as regulators expect businesses to comply with more complex requirements and provide proof of this compliance, describes Martin Butler, Professor of Management Practice at Vlerick Business School. “With increased digitisation in internal processes and customer and business partner interaction, the surface area for compliance breaches has increased substantially. Predictive analytic data models and algorithms enable quicker and more accurate identification and monitoring of the processes and data movements to quickly identify potential non-compliance and create immediate responses.”
AI and the data quality challenge
When it comes to building any AI, data quality is paramount. As Tushaus describes, predictive models are only as good as the data used to train them.
“Organisations must invest in data collection, cleaning and preparation to avoid issues like bias and misleading correlations,” he says. “Building and maintaining models requires advanced analytics skills that are in short supply. Therefore, for companies where investing in the necessary technical knowledge in-house is prohibitive, leveraging off-the-shelf tools is a viable way to reap the value predictive analytics holds. However, it can be challenging for organisations to educate themselves on the tools available and execute successful implementations.
“To mitigate this challenge, companies should leverage knowledge and engagement from a broad group of people throughout their organisation. Knowledge around this technology can come from unexpected places in a company and it is important to ensure that the people expected to use the tools are involved in the evaluation, selection and implementation.”
Businesses beginning to see the benefits of predictive analytics
Today’s businesses of all sizes are adopting predictive analytics, and the industry is starting to see the early benefits in terms of additional time, resource and business efficiency.
“While already high on the business agenda, we expect to see the investment in technology increase even more over the coming years,” Tushaus says. “In fact, looking at our Clarity: Trends and Insights for Architecture, Engineering and Consulting Firms Report, we know that investing in new technologies is the number one priority for project-based businesses. As predictive analytics continues to be used to estimate project costs, timelines, and risks with increasing accuracy, more and more businesses will realise its potential.
“Integrating predictive analytics across operations and combining predictive power with human experience will drive business value. As a result, this technology will not only help prevent budget and schedule overruns, it will also lead to better line of sight into project success making it more likely for projects to proceed in the first place. This can, in turn, lead to better industry performance. It is safe to say that companies not leveraging these capabilities could be left behind by predictive pioneers.”
Butler meanwhile predicts that the most exciting trend in predictive analytics will be the power of AI across the entire data value chain. “AI will help with data ingestion, wrangling and processing,” he says. “AI is creating customised visualisation for individual users at a scale the enterprise analytics teams could never do. Self-service analytics, powered by AI, displaying the appropriate insights in a manner perfectly fit for purpose is the idealised predictive analytics future that is slowly materialising.”
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