• Written by Sonali Subhadarsini, Product Manager

Can we really automate the process of answering the same policy questions every week, or is it just a matter of throwing more staff at the problem, as the human resources manager often asks in our meetings with organisations looking to implement AI process automation for human resources? The truth is, it's hard to answer these questions without first understanding the current process, and this is where most organisations go wrong, as they often try to automate the decision itself rather than the steps around it.

Mapping the current process

Before automating any part of the human resources process, it's essential to map out the current workflow, including all the steps involved in answering policy questions, from the initial query to the final response. This involves identifying the roles and systems involved, such as the shift supervisor checking the employee handbook or the category manager comparing different employee contracts. By doing so, organisations can identify areas where automation can have the most significant impact, and where it's likely to fail, as we have seen in our experience with AsscherAi, a platform that enables organisations to query their own data in natural language and get answers in real time.

This process mapping exercise can be time-consuming, but it's crucial in understanding how the different components of the human resources process interact with each other, and how they can be automated to improve efficiency. For instance, the process of answering policy questions may involve multiple handoffs between different teams, such as the HR team, the finance team, and the management team, each with their own systems and processes.

The handoffs that create most of the delay

The handoffs between different teams and systems are often where the process breaks down, causing delays and inefficiencies. For example, when an employee submits a query to the HR team, it may need to be reviewed by the finance team to ensure that it aligns with the organisation's budget and policies. This handoff can cause a delay, as the finance team may not have the necessary information or may need to consult with other teams, such as the management team. By automating these handoffs, organisations can reduce the delay and improve the overall efficiency of the process, as we have seen in our work with AsscherAi.

Furthermore, these handoffs can also lead to errors and miscommunications, as information is passed from one team to another. By automating the process, organisations can reduce the risk of errors and ensure that the correct information is passed to the correct team, which is a key aspect of AI process automation for human resources.

The human resources data this depends on

The automation of the human resources process depends on the availability and accuracy of certain data, such as the policy library, headcount and skills, attrition history, and hiring plan. This data is essential in informing the automation process and ensuring that the correct decisions are made. For instance, the policy library provides the necessary information on the organisation's policies and procedures, while the headcount and skills data provides information on the organisation's workforce and their capabilities.

The attrition history and hiring plan data are also crucial in informing the automation process, as they provide insights into the organisation's workforce trends and future hiring needs. By analysing this data, organisations can identify areas where automation can have the most significant impact, and where it's likely to fail, which is a key consideration for AI process automation for human resources. For more information on how to manage human resources data, please visit our human resource page.

What it changes about the same policy questions every week

The automation of the human resources process can significantly change the way organisations answer the same policy questions every week. By automating the process, organisations can provide faster and more accurate responses to employees, reducing the delay and improving the overall efficiency of the process. This can also free up staff to focus on more strategic tasks, such as planning and development, rather than simply answering policy questions.

Furthermore, the automation of the process can also improve the consistency of responses, as the same information is provided to all employees, reducing the risk of errors and miscommunications. This can also help to reduce the volume of repeat questions, as employees are provided with accurate and consistent information, which is a key benefit of AI process automation for human resources.

What it changes about planning that runs on impressions

The automation of the human resources process can also change the way organisations plan and make decisions, moving away from planning that runs on impressions and towards a more data-driven approach. By analysing the data and trends, organisations can make more informed decisions, rather than relying on intuition or guesswork.

This can also help to improve the accuracy of planning, as organisations are able to make predictions based on actual data, rather than assumptions. For instance, the hiring plan can be informed by the attrition history and headcount and skills data, ensuring that the organisation is hiring the right people with the right skills, which is a key aspect of AI process automation for human resources.

Measured with repeat question volume, time to answer, attrition by tenure

The success of the automation process can be measured in a number of ways, including repeat question volume, time to answer, and attrition by tenure. By tracking these metrics, organisations can see the impact of the automation process and make adjustments as necessary. For instance, a reduction in repeat question volume may indicate that the automation process is providing accurate and consistent information to employees.

Furthermore, a reduction in time to answer may indicate that the automation process is improving the efficiency of the process, while a reduction in attrition by tenure may indicate that the organisation is hiring the right people with the right skills, which is a key benefit of AI process automation for human resources. If you would like to learn more about how AsscherAi can help your organisation, please contact us.

What this does not do

It's also important to note what the automation of the human resources process does not do. It does not replace the need for human judgement and decision-making, but rather augments it by providing faster and more accurate information. It also does not automate the decision itself, but rather the steps around it, such as the handoffs between different teams and systems.

Furthermore, the automation of the human resources process is not a one-size-fits-all solution, and organisations need to carefully consider their specific needs and requirements before implementing an automation solution. By doing so, organisations can ensure that they are getting the most out of the automation process, and that it is aligned with their overall goals and objectives, which is a key consideration for AI process automation for human resources.