• Written by Muhammed Abdulla NC, CEO

A chief operating officer sits in a meeting, looking at a printout of the company's latest financial reports, and wonders why the organisation's new enterprise AI system is not being used to inform their decisions, despite its potential to provide valuable insights.

Attaching new capability to a routine that already exists

The problem is not that the system is not capable, but that it has not been integrated into the existing routines and workflows of the executive leadership team. Most people get wrong the idea that a new system will automatically be adopted and used, but this is simply not the case. For a system like AsscherAi to be used effectively, it needs to be attached to a routine that already exists, such as the weekly executive meeting or the monthly financial review.

This means that the system needs to be able to provide answers to questions that are already being asked, and to be able to do so in a way that is consistent with the existing workflow. If the system is not able to do this, then it will not be used, no matter how capable it is. A good example of this is when a category manager compares two suppliers, they need to be able to get the information they need quickly and easily, without having to change their existing workflow.

Who needs to be able to ask, not just who needs the answer

Another common mistake is to focus on who needs the answer, rather than who needs to be able to ask the question. In many cases, the people who need the answer are not the same as the people who need to be able to ask the question. For example, a shift supervisor may need to be able to ask questions about the maintenance log, in order to be able to make informed decisions about how to run their shift.

This highlights the importance of considering the needs of all users, not just those who will be receiving the answers. By doing so, organisations can ensure that their enterprise AI system is being used to its full potential, and that it is providing value to all users. The executive leadership team needs to be able to ask questions and get answers in real-time, in order to be able to make informed decisions.

The executive leadership data this depends on

In order for an enterprise AI system like AsscherAi to be effective, it needs to have access to a wide range of data, including consolidated financials, operational KPIs, sales performance, and headcount. This data needs to be up-to-date and accurate, in order for the system to be able to provide reliable answers to questions.

Without this data, the system will not be able to provide the insights and answers that the executive leadership team needs. This is why it is so important for organisations to have a robust data management system in place, in order to be able to support their enterprise AI system. The data needs to be consolidated and easily accessible, in order for the system to be able to provide value to the organisation.

What it changes about

The use of an enterprise AI system like AsscherAi can change the way that the executive leadership team operates, by providing them with the ability to ask cross-functional questions and get answers in real-time. This can help to break down silos and improve communication between different functions, by providing a single source of truth for all data.

It can also help to reduce the problem of each function reporting its own version of a figure, by providing a single, consolidated view of the data. This can help to improve decision-making, by providing the executive leadership team with a more accurate and complete view of the organisation. For example, when a question comes up about sales performance, the system can provide a quick and accurate answer, without the need for manual reporting or data analysis.

Measured with

The effectiveness of an enterprise AI system like AsscherAi can be measured in a number of ways, including decision latency, actions of the form come back with numbers, and definition conflicts resolved. By tracking these metrics, organisations can get a sense of how well the system is working, and where it may need to be improved.

Decision latency, for example, can be measured by tracking how long it takes for the executive leadership team to make decisions, and comparing this to the time it took before the system was implemented. By reducing decision latency, organisations can improve their ability to respond to changing circumstances, and stay ahead of the competition. If you want to learn more about how AsscherAi can help your organisation, you can contact us to discuss your needs.

What this does not do

While an enterprise AI system like AsscherAi can be a powerful tool for the executive leadership team, it is not a replacement for human judgement and decision-making. It is also not a solution to all of the organisation's problems, but rather a tool that can be used to support decision-making and improve performance.

It is also not a system that can be implemented overnight, but rather one that requires careful planning and implementation, in order to be effective. By understanding what the system can and cannot do, organisations can get the most out of their investment, and use the system to drive real change and improvement. Most people get wrong the idea that a new system will automatically solve all of their problems, but this is simply not the case.