Advanced Software (return to the homepage)
Menu

How to integrate the human & AI in your logistics workforce

20/12/2023 minute read OneAdvanced PR

Digital transformation is key for distribution and logistics leaders looking to drive efficiency and cultivate a competitive edge. While a move to cloud computing has dominated change agendas over the past few years, all signs point to artificial intelligence (AI) as the next key innovation to prioritise.

Through 2024, it is predicted that 50% of supply chain organisations will invest in applications that support artificial intelligence. For logistics and distribution firms wanting to join the wave of change, the most successful will be those who consider the interaction points between their current workforce and new technology. AI will be most powerful as an ally to a brought-in team.

The human touch

AI refers to computer software analysing huge amounts of data and using this to inform its own “decisions” or offer insight. The logistics and distribution use cases are many and varied, from AI-enabled robots stocking warehouses to predictive analysis, where historical data is processed to inform accurate demand forecasts.

At its best, AI expands human capabilities and turbocharges progress.  At its worst, it can replicate human biases in the training data, “hallucinate” false facts and cause mistakes via missing intuition and common sense. As a relatively new technology, it needs the input of workers to ensure it is effective.

No AI strategy, therefore, should be introduced without an accompanying people strategy. Leaders must ensure their team will help new technology reach its full potential – and make the investment worth it.

AI as team member

When introducing AI, logistics and distribution managers must educate employees about its mission.  Leaders often advocate for AI using performance metrics around the efficacy of the technology, discussing automation potential, accuracy, precision and recall. However, framing AI around its impact metrics – how it will increase customer satisfaction, save costs, and ultimately increase revenue – emphasises how it will help the team accomplish their goals. The narrative becomes one of augmentation rather than replacement.

This message can be enforced further with a strong User Interface (UI) that clearly shows employees how the AI is working in real time. For example, when using AI to forecast stock requirements, a strong UI can create visualisations of inventory, changing graphical sizing in line with demand, and provide summaries of complex data sets, also known as pivot tables. It allows employees to explore why the algorithm is making recommendations, demystifying its decision making. When they can clearly see its processes, the workforce will be more receptive to the new technology and ready to act on its outputs.

Transforming roles

AI evolves individuals’ job roles, building on their knowledge and competency rather than devaluing it. Take your team along with you on this journey. To help them rethink their roles and feel empowered, involve them in the implementation process.

For example, one of the most established examples of applied AI in logistics is route optimisation for fleets. AI can create more efficient, safer routes based on real-time traffic, weather and road conditions – but often faces resistance from drivers used to following their own favoured routes. It can be helpful to present AI as a tool to offer alternatives to choose from, rather than diminishing the route-finding abilities drivers have built up with years of experience. Improve both your AI and the cooperation of your employees by involving drivers in testing and refining the algorithm, asking for feedback and tailoring it to their preferences.

By mapping out the role AI will play in the organisation clearly for all employees, and investing in tools and features to actively involve them in roll out, logistics and distribution leaders achieve a double win. The workforce will be more cooperative, and planners can rest assured they have not missed out on the opportunity to maximise AI using human insight.  Carefully think about blending AI and human capabilities at the early stages, for a strong union of people and technology.