Overcoming the ‘last mile problem’ in knowledge management: A guide for IT teams - Artificial Intelligence - NewsOvercoming the ‘last mile problem’ in knowledge management: A guide for IT teams - Artificial Intelligence - News

Last Mile Problems in Knowledge Management

The concept of the “last mile problem” is becoming increasingly recognized across various industries, including Knowledge Management. This challenge refers to the difficulties faced in delivering services or products from a central system to the end user’s location. While typically associated with telecommunications and transportation, it has expanded to encompass knowledge repositories accessed through generative AI.

However, Knowledge Management is about much more than just an internal dataset complemented by AI tools that extract knowledge. It involves information derived from documents, dashboards, reports, and expertise within a company. Additionally, knowledge can be obtained from third-party systems and subscriptions. Enterprises often use multiple systems and technologies from various providers like Microsoft, SAP, Box, Google, ServiceNow, Salesforce, and Workday. These systems have their own access controls and data types, making it challenging to search them universally.

As a result of these challenges in Knowledge Management, enterprises face significant last mile difficulties. Different business units or departments within the same company have distinct needs, use cases, data sets, and requirements. For example, sales may require document storage and CRM (Customer Relationship Management), while operations might need document storage, ticketing systems, and project tools. HR relies on document storage, learning management systems, and ERP (Enterprise Resource Planning) solutions. Marketing or research and insights teams may need access to external tools and subscriptions in addition to internal data.

Support is another critical aspect of the last mile problem. Identifying the unique business requirements and data dependencies for each unit, providing user training, onboarding, ongoing support, developing custom glossaries, and maps out ontologies are essential. In this rapidly evolving technological landscape, features and functions must be tailored to meet the specific needs of each business unit.

Enterprise Knowledge Management vendors specialize in KM (Knowledge Management) and offer platforms built on years of experience working with customers, understanding their real-world needs. They provide a wide range of data connectors that seamlessly integrate with various enterprise technologies and constantly evolve to keep pace with the latest advancements. These vendors offer dedicated customer success teams for user onboarding, training, and ongoing support, optimizing AI models to suit each customer’s requirements.

To address the last mile problem effectively, businesses should either have internal IT resources with the capacity to tackle these challenges or collaborate with approved vendors offering vertical market solutions. Solutions should integrate seamlessly with existing standards, policies, access controls, and technologies within the enterprise to ensure comprehensive support for Knowledge Management.

As we move forward into the future of Knowledge Management, collaborative efforts between internal IT resources and external vendors will be crucial. By leveraging their strengths, enterprises can navigate the complexities of the last mile problem more effectively, enhancing productivity and efficiency while unlocking the transformative potential of Knowledge Management in the digital era.

By Kevin Don

Hi, I'm Kevin and I'm passionate about AI technology. I'm amazed by what AI can accomplish and excited about the future with all the new ideas emerging. I'll keep you updated daily on all the latest news about AI technology.