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Anyone who has ever worked for a large organization knows that information silos are a challenging fact of life. They’re evident internally: The left hand doesn’t always know what the right hand is doing, and employees who are supposed to be working in concert are out of sync.
Silos exist externally, too. Companies that are in business together often don’t have full information or a clear picture of their partnership. This can sometimes trigger an “us versus them” mentality among colleagues and collaborators. As a result, opportunities are missed and problems don’t get solved.
But as companies start to experiment with new technologies that break down silos, things might begin to look different. When adopted appropriately, new tools — powered by artificial intelligence, machine learning, and advanced analytics — can transform the ways in which employees communicate, collaborate, and coordinate their workflows. The result: greater efficiency, more synchronization, and less tunnel vision.
UPS, the Atlanta-based shipping giant, is a prime example of how companies can embrace new technology for operational efficiency and better outcomes. The company uses a network planning tool (NPT) to integrate its pickup and delivery system. A B2B customer’s package is categorized by a destination ZIP code, weight, and volume; it is then given a bar code label and placed on a conveyer belt, where it is scanned and loaded for delivery. The NPT organizes packages by final destination while also considering the type of parcel and time of year. Pharmaceuticals, for instance, are not routed via the desert, as extreme temperatures can affect the potency of certain medications, and NPT also considers the potential for congestion during peak holiday seasons.
The beauty of NPT, however, is not just its algorithm; rather, it’s that the app empowers human engineers to make better decisions. When a package reroutes, the app notifies a UPS engineer in the new location city about the revised plan. The engineer then looks at various options, evaluates them, and takes action. The engineer might let the plan remain in place or reroute the package based on new information. This human-driven decision becomes an update in the app, which in turn helps it learn from human oversight and get smarter about routing plans. Just as important, NPT also serves as a check on the engineer’s choice to ensure that it had the desired result. This not only saves UPS time and money, it’s also a boon to customer satisfaction.
Becton, Dickinson and Co. (BD), a global medical technology provider, is also integrating AI-powered solutions into its workflow. The company’s BD HealthSight Diversion Management Analytics application is designed to help hospitals and health systems improve their medication management processes at a time when addiction to prescription narcotics in the U.S. has reached epidemic proportions.
By monitoring hospital medication activity, the application allows health care institutions to identify anomalous and at-risk behavior associated with possible drug diversion by health care workers. Using machine learning-based algorithms and multiple dispensing activities — such as overrides and canceled transactions — the application recognizes behaviors that suggest a higher risk for diversion. It then assigns potential diversion cases to investigators.
“Hospital drug diversion is a complex challenge that can be difficult for hospitals to detect with potentially devastating impacts on both patient and health care worker safety,” says Ranjeet Banerjee, worldwide president of Medication Management Solutions for BD. According to Banerjee, “The BD HealthSight Diversion Management Analytics application is the next step in the company’s efforts to address drug diversion through integrated solutions and analytics.”
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Other companies are using AI to improve internal collaboration and coordination. San Francisco-based People.ai, for instance, is trying to tackle the enduring problem of misaligned sales and marketing departments. The company recently launched a tool to increase engagement and cross-functional communication between the two units and allow companies to understand which of their marketing campaigns work and which don’t.
The tool, Campaign360, provides real-time insights into the impact of meetings and selling opportunities generated via marketing campaigns. This creates more transparency around a company’s sales pipeline initiated by marketing and also instills accountability for lead follow-up by sales reps. According to People.ai — which integrates to a CRM, like Salesforce, and counts Lyft and Zoom among its clients — its revenue-intelligent AI platform enables organizations to recover 20% to 30% of a marketing pipeline that’s being wasted today in a typical enterprise.
The technology also has the potential to help break down information silos and other barriers. Giving managers a clearer picture of the business allows them to understand the constraints across functional units and facilitates collaboration that can transform the business culture over the long term.
To be sure, AI alone is not the panacea for the silo problems that afflict large organizations. AI has its own set of issues and limitations, including restricted training data, no assurance that the data will be understood, and flawed designs that lead to hidden biases transferred from humans to machines. And of course, the ultimate responsibility for eliminating organizational silos resides in human workers.
Still, many managers are already seeing AI’s promise to help create more connected, coordinated systems both inside and outside the organization. In the workplaces of tomorrow, silos may be a thing of the past.