Maximizing Value and Reducing Risks in Information Systems
As we venture further into the digital era, the importance of managing information systems effectively and compliantly cannot be overstated. This endeavor requires meticulous navigation through numerous local, state, federal, international, and industry requirements. Simultaneously, we are tasked with the challenge of extracting valuable insights from these systems, while responsibly eliminating any content that lacks business value. Microsoft has historically focused on the storage of and collaboration around information assets, but more recently has turned its focus toward more automated governance capabilities. The extraction of data, analysis against templates and various other automation, and the assembly of net-new content is now possible using Microsoft’s latest AI and Microsoft Syntex capabilities.
Even with this new technology, there is plenty of work to be done to prepare for them. Here’s a closer look at how we can optimize these processes.
Automating Core Records Management Processes
The sheer volume of data and records generated daily necessitates a more efficient approach to records management. By automating these processes, we not only increase efficiency but also ensure compliance and reduce human error.
Using technologies such as AI and machine learning, we can develop systems that automatically classify, store, and manage records based on predefined rules and criteria. These systems can ensure that records are retained for as long as required by law and industry standards, while also identifying when records can be safely discarded.
Responsible Elimination of Non-valuable Content
Excessive data isn’t just a storage issue, it can be a significant legal and financial burden. By systematically eliminating non-valuable content, we can decrease storage costs and reduce litigation risks.
Data lifecycle management tools can aid in identifying and categorizing data based on its business value. Once identified, non-valuable content can be responsibly deleted in accordance with legal and industry requirements, ensuring a balance between cost-effectiveness and compliance.
Leveraging Semantic Technologies for Value Extraction
Semantic technologies offer promising capabilities for mining static content repositories. They can help us not only in organizing and understanding data but also in deriving valuable insights.
By using Natural Language Processing (NLP) and semantic search technologies, we can extract meaningful information and gain new insights from previously untapped resources. For instance, an analysis of customer feedback could reveal trends and patterns that were previously overlooked, leading to more informed business decisions.
Embracing Social Systems without Increasing Business Risk
The adoption of social systems, while advantageous, can pose potential risks to businesses. To tap into their benefits without increasing business risk, governance policies and procedures must be put in place.
Transparent and enforceable social media policies can guide employees on the acceptable use of these platforms, reducing potential risks. Furthermore, utilizing social media monitoring tools can help businesses track and manage their digital presence, identifying potential risks in real-time and allowing for prompt action.
Navigating the challenges of information systems governance necessitates a strategic approach. By automating core processes, responsibly discarding non-valuable content, harnessing semantic technologies for value extraction, and managing social systems effectively, we can ensure not only compliance with various regulations but also the extraction of maximum business value from our information systems.