• Written by Azhar Aliyar, Director

A maintenance supervisor checks the work order system to see which jobs are pending and finds that the data is inconsistent, with some fields missing and others containing incorrect information, which makes it difficult to get a clear picture of the current state of operations.

Field-level meaning and why column names are not documentation

The problem here is that the meaning of each field is not clearly defined, leading to confusion and errors, and column names are not sufficient to convey the necessary information, as they can be ambiguous or open to interpretation, and most people get wrong that column names are a substitute for proper documentation, but they are wrong because without clear and concise definitions, the data is essentially useless.

For example, a field named "status" could refer to the status of a work order, a project, or an equipment, and without further context, it is impossible to know what it actually means, and this lack of clarity can lead to mistakes and miscommunication, which can have serious consequences in an operations setting.

The systems that get left out of scope and the partial answers that follow

When implementing a system like AsscherAi, it is common to focus on the main systems and databases, but often, smaller systems and spreadsheets are left out of scope, which can lead to partial answers and incomplete information, and this can be particularly problematic in operations, where having a complete and accurate picture of the current state is crucial.

A shift supervisor checks the maintenance log and finds that some information is missing, because the system used by the maintenance team is not integrated with the main system, and this lack of integration can lead to delays and mistakes, and it is not uncommon for systems to be left out of scope, especially if they are not considered "critical" or if they are used by a small team, but this can still have significant consequences.

The operations data this depends on: process and exception records, project status, budget consumption, supplier performance

To get a complete picture of operations, it is necessary to have access to a wide range of data, including process and exception records, project status, budget consumption, and supplier performance, and this data must be accurate, up-to-date, and easily accessible, and it is not just about having the data, but also about being able to analyze and interpret it, and operations teams must be able to use this data to make informed decisions and take corrective actions.

For instance, a category manager compares two suppliers and finds that one of them has a higher defect rate, which can inform the decision to switch suppliers, and this kind of analysis can have significant consequences for the organization, and it is not just about saving money, but also about improving quality and reducing risk, and having access to this kind of data can be a major advantage.

What it changes about: anomalies only visible in combination and projects consuming budget faster than progress

One of the key benefits of having access to this kind of data is that it allows for the detection of anomalies that may not be visible when looking at individual systems or datasets, and this can be particularly useful in identifying problems that are only apparent when looking at the bigger picture, and it can also help to identify projects that are consuming budget faster than they are making progress, which can be a major problem in operations.

For example, a project manager reviews the budget consumption of a project and finds that it is running ahead of schedule, but the progress is not matching the expenditure, and this can indicate a problem with the project, such as inefficiencies or scope creep, and having access to this kind of data can help to identify these problems early on, and take corrective actions, and it is not just about identifying problems, but also about being able to take action to fix them.

Measured with: on-time delivery, exception rate, expediting cost

To measure the effectiveness of operations, it is necessary to track key performance indicators, such as on-time delivery, exception rate, and expediting cost, and these metrics can provide valuable insights into the performance of the organization, and help to identify areas for improvement, and it is not just about tracking these metrics, but also about being able to analyze and interpret them, and take action to improve them.

For instance, a logistics manager reviews the on-time delivery rate and finds that it is below target, and this can indicate a problem with the supply chain or the transportation system, and having access to this kind of data can help to identify the root cause of the problem, and take corrective actions, and it is not just about fixing the problem, but also about preventing it from happening again in the future, and contacting us can help to get started with implementing a system like AsscherAi.

What this does not do, or when it is the wrong choice

This system is not a substitute for proper planning and management, and it is not a magic solution that can fix all problems, and it is not suitable for all organizations or all situations, and it is not just about having the technology, but also about having the right processes and people in place, and it is not a one-size-fits-all solution, and it requires careful consideration and planning to implement effectively, and it is not just about implementing the system, but also about maintaining it and continually improving it over time.