AI Makes Enterprise Mobility Management Proactive Rather Than Reactive

Problems with apps, a lost scanner, a dead battery, or dropped connections: such seemingly minor issues can significantly disrupt a tightly planned logistics operation. In warehouses, distribution centers, and delivery networks, scanners, PDAs, tablets, and handheld devices serve as the link between employees, orders, inventory, and customers. Yet there is often a lack of complete visibility into what is happening with that mobile fleet. Which devices are in use? Which software versions are out of date? And does the mobile fleet comply with current laws and regulations? AI makes it possible to eliminate these blind spots and shift device management from reacting to predicting. Reverse IT supports organizations in this effort with mobile managed services, mobile device management (MDM), and consulting on enterprise mobility.

Wouter Turpijn, Customer Solutions Architect at Reverse IT, sees this reverse approach reflected in the company’s name. “We don’t approach clients with the message: ”Here’s what we have—take your pick,“” he says. “We first identify all the pain points and then determine which solutions are a good fit.” Sometimes this means that Reverse IT first sets up a platform to collect data and then applies AI solutions to it. In other cases, an existing platform is already in place, and Reverse IT helps integrate AI into it in a targeted manner.

Control over devices

“In a traditional setting, problems only become apparent after processes slow down, equipment fails, or employees experience disruptions in their work. AI makes it possible to take proactive action, which can prevent all kinds of disruptions.”

AI can translate data collected from mobile devices into actionable insights. “For example, AI identifies which devices are actually being used, where anomalies occur, and which devices are at risk of failure,” says Turpijn. “AI can then make recommendations. The great thing is that it does so in plain language.”

Significant cost savings

This approach can result in significant cost savings, Turpijn explains. “Not only do you prevent downtime, but you also avoid a loss of customer trust. In addition, you reduce the risk of motivation issues among employees, because poorly functioning business applications are unpleasant to use. An organization can also save on device purchases. Whereas you might previously have replaced all devices due to performance issues, AI can now tell you that only the slower Model A devices need to be replaced, since the newer models are still functioning just fine.”

Real-world evidence

Using a few customer case studies, Turpijn explains what centralized device management and a robust data layer can deliver in practice. “At DynaGroup, a specialist in customer-focused logistics services, we revamped the device management system for their mobile devices. Onboarding time dropped from fifty to seventeen minutes per device, and the number of management tasks decreased from fifty to eleven.”

Picnic also achieved excellent results. “At Picnic, we implemented SOTI and Waizu management solutions for nearly 9,000 Android and Windows devices. The new devices are now up and running in three minutes, whereas it used to take twenty minutes. By simplifying, integrating, and automating daily management tasks, and by giving operations managers the insight and tools to manage employees and devices, delivery drivers and logistics staff can count on having devices that work with up-to-date software.”

Laws and Regulations

A comprehensive and reliable data layer ensures that AI has sufficient information to identify trends, compliance risks, and disruptions earlier. This is also relevant in light of NIS2, the GDPR, and information security. AI can convert technical device data into understandable reports and concrete recommendations in seconds. This makes it possible, for example, to quickly determine the extent to which the mobile fleet complies with internal policies, security requirements, or audit conditions. AI can also help prepare reports for auditors more quickly and consistently, without requiring administrators to manually comb through various systems. In this way, compliance shifts from a time-consuming snapshot to a continuous process of insight, monitoring, and targeted improvement.