The Hidden Value: Why Unstructured Data is a Game-Changer in Asset Manangement

Physical asset management is the process of managing an organization's physical assets, including its plants, equipment, and other resources. Managing physical assets can be a complex task, particularly when it comes to managing data related to those assets. Traditionally, asset data has been managed in structured formats, such as databases, spreadsheets, and other structured data management tools. However, the growing volume of unstructured data related to assets is becoming a critical component in asset management. In this blog, we will discuss the significance of unstructured data for physical asset management and highlight why it is critical for managing legacy data, maintenance, and new asset development.

Unstructured data is any data that is not organized in a pre-defined manner. It can include text, images, emails, documents and other forms of media. In the context of physical asset management, unstructured data can provide valuable insights into the performance, maintenance, and development of physical assets. In this blog, we will discuss the significance of unstructured data for physical asset management and provide data and analysis on why it is critical. We will also provide a list of key aspects to address in the transformation and management of unstructured asset data.

The Significance of Unstructured Data for Physical Asset Management

Legacy Data

Many organizations have been collecting structured data on their physical assets for years. This data can include information such as the age of the asset, its maintenance history, and its performance metrics. While this structured data is useful for understanding the basic characteristics of an asset, it does not provide insights into the root causes of asset failures or other issues. Unstructured data, on the other hand, can provide these insights.

For example, if a machine is experiencing frequent breakdowns, structured data might tell you how often it has been serviced and how long it has been in use. However, unstructured data such as machine logs and sensor readings can provide a more detailed understanding of the specific conditions that are causing the breakdowns. This information can be used to identify the root cause of the problem and develop a more effective maintenance strategy.

Maintenance

One of the key benefits of unstructured data for physical asset management is its ability to improve maintenance processes. Traditional maintenance approaches involve a schedule of regular maintenance activities that are performed at predetermined intervals. This approach can be costly and inefficient, as it does not take into account the actual condition of the asset.

With the help of unstructured data, organizations can implement more effective maintenance strategies. For example, machine logs and sensor data can be used to monitor the actual condition of an asset in real-time. This data can then be used to develop a predictive maintenance strategy that identifies potential issues before they become serious problems. This approach can reduce downtime and improve asset performance.

New Asset Development

Unstructured data can also be used to improve the development of new assets. By analyzing data from existing assets, organizations can gain insights into the design features that are most effective in improving performance and reducing maintenance requirements. This information can then be used to inform the design of new assets.

For example, if a particular type of machine is experiencing frequent breakdowns due to a specific design feature, this information can be used to inform the design of a new machine that avoids this issue. Similarly, if sensor data shows that certain conditions are associated with improved asset performance, these conditions can be incorporated into the design of new assets.

Data and Analysis on the Criticality of Unstructured Data

A study conducted by Accenture found that the use of unstructured data in asset management can lead to significant improvements in asset performance and maintenance. The study analyzed data from over 50 industrial companies across various industries, including oil and gas, mining, and manufacturing.

The study found that organizations that used unstructured data to inform their asset management strategies experienced an average increase in asset performance of 20%. Additionally, these organizations were able to reduce maintenance costs by an average of 10%. These improvements were attributed to the ability of unstructured data to provide more detailed insights into asset performance and maintenance needs, enabling organizations to implement more targeted and effective strategies.

Another study conducted by SAS found that the use of unstructured data in asset management can also lead to improved safety outcomes. The study analyzed data from the oil and gas industry and found that organizations that used unstructured data to monitor safety performance experienced a 27% reduction in safety incidents.

These studies demonstrate the criticality of unstructured data in physical asset management. By providing more detailed insights into asset performance and maintenance needs, unstructured data can lead to significant improvements in asset performance, maintenance costs, and safety outcomes.

Key aspects to address in the transformation and management of unstructured asset data:

Data capture and storage:

The first step in managing unstructured asset data is to capture and store the data effectively. Organizations must identify the sources of unstructured data and develop processes for capturing and storing this data. This may require the use of specialized tools and technologies to capture and store data in various formats, such as email, PDF files and images.

Data processing and analysis:

Once data is captured and stored, organizations must process and analyze the data effectively. This may require the use of specialized tools and technologies to extract valuable insights from unstructured data. Organizations may also need to develop processes for integrating structured and unstructured data to gain a comprehensive view of asset performance.

Data governance and security:

Unstructured asset data can be sensitive and may contain confidential information. Organizations must develop policies and procedures for governing and securing unstructured data to protect against data breaches and cyber-attacks.

Data quality and accuracy:

Effective management of unstructured asset data requires a high degree of data quality and accuracy. Organizations must develop processes for verifying the accuracy of data and ensuring that data is complete and up-to-date.

Why is unstructured data critical?

The importance of unstructured data for physical asset management can be highlighted by several factors:

Volume:

Unstructured data represents a significant volume of the data generated by physical assets. As the volume of data generated by assets continues to grow, organizations must find ways to leverage unstructured data to gain insights into asset performance and maintenance requirements.

Variety:

Unstructured data comes in various forms, including text, images, videos, and email files. The diversity of unstructured data requires organizations to use specialized tools to analyze and manage this data effectively.

Velocity:

Unstructured data is often generated in real-time, which requires organizations to capture and analyze this data quickly to gain insights into asset performance.

Complexity:

Unstructured data can be complex, making it challenging to analyze and manage. For example, images and videos may contain multiple data points, such as temperature, vibration, and sound levels, making it difficult to extract valuable insights from this data.

Value:

Unstructured data can provide valuable insights into asset performance and maintenance requirements, enabling organizations to optimize asset performance, reduce maintenance costs, and extend asset life.

Innovation:

Unstructured data is essential for Unstructured asset data can be challenging to access and analyze, particularly if it is stored in various formats. Organizations must develop processes for making data accessible to the relevant stakeholders and ensuring that data is easy to search and analyze.

Data integration:

Integrating structured and unstructured data is essential to gain a comprehensive view of asset performance. Organizations must develop processes for integrating data effectively, which may require the use of specialized tools and technologies.

Data visualization:

Data visualization is critical for making sense of unstructured asset data. Organizations must develop processes for visualizing data effectively, which may require the use of specialized tools and technologies.

Conclusion

Unstructured data is becoming an increasingly critical component of physical asset management. By providing more detailed insights into asset performance, maintenance needs, and safety outcomes, unstructured data can enable organizations to implement more targeted and effective strategies. However, managing unstructured data requires a comprehensive approach that addresses key aspects such as data acquisition, processing, integration, governance, change management, skills and capabilities, and continuous improvement. By addressing these aspects, organizations can effectively manage unstructured data and realize the benefits of more effective physical asset management.