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A company can lose up to 40% annually due to inefficiencies and work flow. Companies often seek out Artificial Intelligence (AI), scheduling algorithms, to solve this problem. It is a useful tool that can be used to improve business models, which depend on efficiency and speed. This includes delivery services and logistics.
Although AI is certainly helping with the tedious and unpredictable task of scheduling employees across different departments, it’s not perfect. It can sometimes make the problem worse than it solves.
The human capacity to see beyond optimizing business efficiency is lacking in AI. This means that AI cannot take into account “human” factors such as worker preferences. AI scheduling limitations can lead to unhappy workers and unbalanced shifts, which could result in AI helping HR to create smoother workflows.
If optimization fails, AI cannot see the humans behind data points
In recent years, auto-scheduling artificial intelligence has been gaining a lot in popularity. The global AI scheduling market will grow at a 13.5% CAGR between 2022-2027. 77% of businesses are using AI, or looking to implement it in their business.
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It is important to remember that AI can’t yet create schedules without humans being involved. Human resources professionals must still review schedules generated automatically by AI. This is because the AI algorithm lacks “human parameters”.
AI excels at sorting data and finding efficient business processes. The best way to optimize workflow is using algorithms that make use of historical data. This allows you to project order volumes and worker requirements based on weather patterns and marketing promotions.
AI is unable to recognize “human parameters”, which AI perceives as decreases in efficiency, rather than improved business practices.
If a company employs Muslims, for example, it may need to allow them small breaks during work in order to attend prayer time. A business may need to provide breastfeed times for new mothers. These things are beyond AI’s current capabilities. AI cannot utilize empathy or human reasoning to determine if these inefficient schedules are better for long-term happiness.
It’s not always efficient; can there be a better way?
Auto-scheduling software can currently only draw data from limited sources like workflow histories and timesheets to ensure that work hours are evenly distributed in the best way possible. AI scheduling tools will need to understand why the same worker should work one shift and return the following day for the first shift. These tools are not able to account for worker preferences and varied availability.
This problem can be solved by adding more parameters to the algorithm, which has its problems. The first is that every parameter you add to an algorithm decreases its performance. Algorithms only function as good as the data that they receive. Incomplete, inaccurate, or inexact data can cause scheduling problems and increase workload for HR managers. It won’t work more efficiently if you add filters to it or place limitations on its operation.
What is the solution to this problem? We will always need humans to schedule workers until AI can be infused with empathy reasoning abilities.
Companies can still work towards a positive and synergistic relationship with AI scheduling tools, as well as the people who use them.
Delivery companies, for example can use AI tools to feed past data into their schedule software in order to improve the efficiency of their first schedule outputs. This eases the load on scheduling and HR managers. The human scheduler has an optimized schedule from which to work, so that they are able to spend more time fitting employees into their time slots.
While AI may be extremely efficient, it needs to have human support in order for employees to feel happy.
The human race is working to develop AI with “general intelligence.” This refers to intelligence that is seen in both humans and animals. This AI combines problem solving with emotional and common sense. These are two qualities that AI has yet to replicate.
AI is a great tool for automating repetitive tasks and analyzing large amounts of data in order to identify inefficiencies or better methods. As AI adds nuance and emotion to tasks such as scheduling, however, human beings will need to make the final decision to ensure that optimized workflows are balanced with employee satisfaction, long-term company growth, and optimal work processes.
Vitaly Alexandrov, serial entrepreneur, is the founder and CEO at Food Rocket in America.
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