Artificial intelligence (AI) has required a shift in the way we view technology, as it challenges individuals to trust that a computer can be as smart as a human. Unfortunately, human bias can creep in and unless the AI tells us what we want to hear, we may not trust its suggestions. But AI can and is helping when it comes to developing solutions for better people management, simply because it can help with many things that we are notoriously bad at as humans.
As human beings, we understand context and we are good at building relationships. Still, we often come undone when we are stressed and move into a state of paralysis when required to divide ourselves into multiple ‘pieces’ to ensure better project management. Where AI comes in is it's excellent at connecting the dots of unrelated possibilities and when combined with machine learning and Robotic Process Automation (RPA) these dots become automated.
Better planning and service
When added to software, neural networks are great tools to help with creating optimal schedules for people. Our partner IFS has been successfully using neural networks in its IFS Planning and Scheduling Optimisation tools for over a decade to help create the optimal schedule for field workers. The evolution of this has been to add more advanced AI techniques to the mix and help organisations determine where resources are needed instead of simply where they are scheduled to be.
We mean that AI can help remove the angst involved in creating schedules based on deciding where field workers need to be at any given point. AI can help track urgent needs against simple maintenance needs and then advise a manager where to send or place a resource.
Another excellent use case for AI is in the realm of customer service. IFS has several customers who are using AI to expand customer self-service options through the adoption of technology such as chatbots. These tools help the client reduce the frustration associated with repetitive, straightforward activities such as appointment scheduling or frequently asked questions. An employee can now focus their time on customers who need real support, not just those who have simple queries but clog up the support queue.
Remove unpredictability
We all know that people are unpredictable, which is another reason that AI is so attractive. Using AI that is embedded and built-in to your applications (not just relying on it as a fringe technology) allows an organisation to develop more consistent processes.
Human error can come at a high cost. A simple mix up in a purchase order (PO) where something is allocated in Rands and not Dollars, for example, can create an auditing nightmare. But AI can spot incongruencies and anomalies because it doesn't get distracted by a call or has to hop on a quick meeting to solve a crisis.
One area where we see its benefit is by simply matching an invoice to a PO. Usually, people spend hours trying to track simple tasks like these manually. Still, when AI is applied simply, individuals are freed to use their unique talents and not waste them on admin.
In a supply chain environment, matching a Goods Receipt to a PO when a system has not been configured to make these matches will cost time and money. When AI is injected into this process, payments generated and allocated can be quickly and seamlessly aligned. It shouldn't sound hard because it isn't. This is all low hanging fruit as to how AI can help streamline and improve processes for the benefit of the company and its people.
A good example of these types of technologies in action is that IFS is embedding machine learning, RPA and operational optimisation within its application to enable the automation of more processes. A great use case where IFS has combined these technologies is its use of RPA technology to help a North American food manufacturing customer, Cheer Pack, to optimise its production operations and create a competitive advantage.
This involves orchestrating the movement of a fleet of autonomous vehicles fitted with sensors, such as laser scanners and 3D cameras, to navigate the factory in response to a shop order production process generated by the IFS app. When a robot needs to recharge it hands off its existing tasks to other robotic vehicles that can optimise themselves and ensure the most efficient flow of data and parts throughout the factory. As a result of this move, the company has saved over $1,5 million annually, while every employee affected will be re-tasked to a higher position, significantly helping to address current labour shortages.
Buying time
Garry Kasparov, the first human to lose a chess match to an AI was famously quoted: “With so much power now brought by machines, we have to find a refuge in our humanity. It’s about our creativity, our intuition, our human qualities that machines will always lack. So, we have to define the territory where machines should concentrate their efforts. This is a new form of collaboration where we recognise what we’re good at and not interfere with machines where they’re superior—even if it hurts our pride.”
The bottom line is that AI is no longer a fringe technology and it is now already established in many of the software solutions we have at our disposal. We use it in scheduling and planning, financial analysis, time and attendance, materials handling and goods processing, security anomaly detection, chatbots and even in social media ad servers. Using AI in data analytics is also allowing us to make edge and IoT devices more intelligent.
When it comes to using AI in people management, the opportunities are unlimited. But critically, it buys our people time to do what they need to do more effectively and it buys the business peace of mind that what is being done is being done effectively and efficiently.
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