CIOReview | | 9 FEBRUARY 2024Eventually, these will guide predicting future challenges and how to navigate them. Taking it one step further, with cognitive analytics, a machine can learn from experience and generate its own hypotheses, drawing connections from a wide range of data by reaching beyond the constraints of human thinking.2 Into the right hands Once a company puts the right data infrastructure and technologies in place, the question remains: Will the workforce embrace or resist it?It is critical that the data evangelist who champions the data analytics program has the organizational clout and authority to inspire others and break down silos. Once they have taken up the cause, the next step is to work toward building a workforce of the future through talent development programs that upskill workers to leverage data in every corner of the business. Employees must trust in the validity of data-derived insights. The best way to instill this trust is by transparently educating employees on the inputs that inform data-backed decisions.3 With the right business case Reaching data analytics maturity requires investment in people, processes, and technology.Clearly stating potential ROI from the onset of the project is critical to help leaders and employees across the organization recognize the value in the proceeding. Starting small goes a long way. Begin with proofs of concept, generating internal success stories that fuel enthusiasm, adoption, and continued investment.What is Possible with Data Analytics MaturityWhen correctly leveraged, a mature data analytics program will save businesses time, reduce risk, and boost financial returns. Consider the following advantages of mature data analytics initiatives in action:Create New Revenue Streams A parking lot operator was able to unlock a new revenue stream by employing a computer vision model to track open parking spaces at a mall. The cameras identified the make and model of arriving vehicles--feeding that data to the mall for highly targeted advertising powered by machine learning. Based on this information, shoppers received promotions within their vehicles or on their mobile phones.Detect Fraud A healthcare company used deep learning to review its accounts payable records to ensure there were no errors. Through this audit, they spotted one vendor and one year that stood out as abnormal. The invoice line and invoice header did not add up, all to the tune of 13M dollars. Through deep learning, AI was able to find the unexpected without humans having to tell the machine exactly what to look for. In contrast, it can be challenging for humans to sniff out fraud and identify outliers.Spot and Resolve Gaps A healthcare system was able to reduce patient no-shows by leveraging AI and robotic process automation to send personalized text messages to patients with high predictions of not showing up. With the assistance of automation, it allowed for the rescheduling of the first appointment and finding a new patient to fill the original appointment time within 4 hours. The solution resulted in improved patient care and increased billable revenue for the hospital.Predictive MaintenanceWith AI, a railroad company was able to predict which wagons were going to need maintenance checks prior to the scheduled appointment, automatically scheduling an earlier appointment. The maintenance team was able to expedite service and reduce downtime in wagon operations.Reduce Invoice Late PaymentsA financial institution was able to predict which invoices would be paid late by using AI and robotic process automation. The institutions sent personalized text messages to those with the highest likelihood of paying their invoice late and were, therefore, able to reduce late payments and increase monthly cash flow.Why NowRegardless of where your organization sits today, future-proofing your business depends on laying the groundwork for data analytics maturity. Your competition may not currently have the sophistication to anticipate the hazards that could derail profits or drive new revenue streams using customer data. But in the proverbial data arms race, there will be limited survivors. By starting now, you can ensure that your most valuable asset--your data-- is used to edge out the competition. Employees must trust in the validity of data-derived insights. The best way to instill this trust is by transparently educating employees on the inputs that inform data-backed decisions
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