Stay ahead of technology changes with task management

New task management software powered by machine learning is revolutionizing the entire global supply chain. There is a tremendous opportunity to use these next-generation solutions to increase business agility and competitiveness across the supply chain.

The magic of AI-based task management

First, AI-based task management software does more than just automate routine tasks. As you gain experience working with organizations, you will be able to automate more functions.

Start by automating obvious, low-level chores that don't require discretion, such as moving files elsewhere when their status is updated or deleting copies of redundant or outdated information. It makes the most sense to focus on Generating reports automatically when certain conditions are met is also a common use. Simple administrative tasks that your organization's team members need to perform on a daily basis are good candidates to start.

However, the magic of machine learning algorithms is that over time they can gain competency in a business' operating procedures. For example, if AI senses that a particular employee regularly organizes their work according to a certain priority, it can automatically start placing new assignments in the correct order as the employee comes in. .

Additionally, these algorithms collect and analyze increasingly complex datasets, allowing them to run simulations and predict strategies to reduce costs, better utilize resources, and improve overall processes. . For example, the software can analyze historical data and identify important patterns in demand, allowing businesses to better manage inventory, reduce lead times, and minimize stockouts. Similarly, the system examines production schedules and equipment usage and suggests ways to make them more efficient.

How to reduce transfer time with next-generation task management

Combined with radio frequency identification (RFID), Industrial Internet of Things (IIoT) sensors or other technologies, next-generation task management systems can also identify transportation bottlenecks and suggest new, more advantageous routes. For example, if a traffic jam occurs along one major artery, the system can automatically flag the problem and suggest alternative routes, all in real time, allowing companies to respond to changes on the ground as soon as they occur.

Similarly, this technology can also alert operators to unusual conditions and potential threats to the supply chain. Consider the recent Baltimore Bridge disaster. With next-generation solutions, route drivers and freighters can instantly receive guidance to steer away from the scene and be shown the best new route to their destination.

Next-generation task management software also allows you to store shipments in the optimal configuration. For example, some items may be heavy or require refrigeration, while others will be shipped to a new location soon and should be kept on top for immediate handling. AI-based systems can analyze an organization's capabilities and crunch the numbers to ensure optimal use of space and minimum labor at all times.

Transparent task management across the supply chain

At the same time, next-generation task management technology facilitates end-to-end visibility across the supply chain. When combined with his RFID and his IIoT, this software can track the movement of raw materials and goods, giving retailers a solid source of origin to show to their customers. You can use this transparency to prove that your products are legally and ethically sourced.

Additionally, one of the most important benefits of these solutions is that widely distributed teams can collaborate in real time. Cloud-based computing, automatic status updates, intelligent alerts, etc. are examples that can enhance communication within an organization and between business partners.

Speaking of communication, today’s AI-based systems have better communication capabilities. Not only are they trained to identify and effectively respond to human emotions, they are also able to accept feedback and adapt over time to learn the tendencies of individual team members.

Best practices for implementing new task management tools

However, many companies that could benefit from these cutting-edge technologies are not taking advantage of them. Their leaders may feel attached to legacy systems or despair that their operations are too complex to update. But with careful planning, collaboration, and a step-by-step approach, successfully integrating these tools is easier than many fear.

The first step in planning is for an organization to assess its current systems and processes in the most comprehensive way possible, including understanding the strengths and weaknesses of existing systems. In particular, companies should look for areas where new AI-based systems can bring the most value.

Second, collaboration with IT professionals and users is key, so companies should engage with all kinds of stakeholders during the planning process, so they can not only share their insights and concerns, but also take ownership of the success of the migration.

It's better to take a step-by-step approach than trying to change everything at once. Divide the integration into manageable stages, with clearly defined goals and benchmarks for each stage. This allows for thorough testing and allows companies to address issues that arise along the way and minimize potential disruption to ongoing operations.

maturing software

Unlike traditional software that becomes obsolete over time, new AI-driven machine learning systems become increasingly sophisticated over time, increasing in value as they learn, adapt, and mature. That's why business leaders should consider moving to next-generation tools now.

brianna van zanten customer success manager in check.