Overcoming the ‘last mile problem’ in knowledge management: A guide for IT teams

Overcoming the ‘last mile problem’ in knowledge management: A guide for IT teams Scott Litman is an entrepreneur in search of new ways technology can advance organizations' mission. From the early days of the Internet to business portals of the dot com era and then 1:1 marketing, and now the latest generation of AI—Scott has a broad history of building businesses that help clients take advantage of cutting-edge digital transformation. Most recently, Scott serves as a founder and managing director of Lucy, an AI-powered answer engine®, where he helps Fortune 1000 organizations democratize their corporate knowledge, enabling employees with the information they need and driving productivity.


The concept of the “last mile problem” is widely recognised across various industries as the challenges faced in the final stage of delivering services or products from a central system to the end user’s location. Although typically associated with telecommunications and transportation, its application extends far beyond these domains.

In the realm of Knowledge Management, we are now witnessing the emergence of the last mile problem. About a year ago, ChatGPT captivated millions of users worldwide, prompting businesses to explore the potential impact of this groundbreaking technology. Knowledge Management quickly became a focal point of interest, with vendors like OpenAI and Microsoft developing APIs and tools for developers to create their own applications. Since then, Fortune 1000 IT departments have been actively experimenting, testing, piloting, and implementing solutions to address productivity inefficiencies.

The possibilities presented by available APIs and services are truly revolutionary. We are witnessing remarkable examples of knowledge repositories being accessed through generative AI, enabling functions that were once considered nearly science fiction.

However, Knowledge Management encompasses far more than an internal dataset complemented by generative APIs that extract knowledge. It encompasses information derived from documents, dashboards, reports, and even expertise found within a company. Additionally, knowledge may be obtained from third-party systems and subscriptions. Enterprises often operate multiple systems and technologies from various providers such as Microsoft, SAP, Box, Google, ServiceNow, Salesforce, and Workday. Each system has its own access controls and data types, and none were designed to be universally searchable.

Consequently, enterprises face significant last mile challenges in Knowledge Management. Different business units or departments within the same company may have distinct needs. Use cases, data sets, and requirements can greatly vary. For example, sales may require document storage and CRM, while operations may need document storage, ticketing systems, and project tools. HR, on the other hand, may rely on document storage, learning management systems, and ERP solutions. Furthermore, groups like marketing or research & insights may require access to external tools and subscriptions, in addition to internal data. A one-size-fits-all approach to Knowledge Management cannot adequately address the diverse range of tools, data, and departmental needs found in the typical enterprise.

“Enterprises often operate multiple technologies and systems from various providers. Each system has its own access controls and data types – and none were designed to be universally searchable”

Support is another critical aspect of the last mile problem. Who is responsible for understanding the unique business requirements and data dependencies of each unit? Who provides user training, onboarding, and ongoing support? Who develops custom glossaries, maps out ontologies, and fine-tunes the AI? In this rapidly evolving technological landscape, how can features and functions be tailored to meet the specific needs of each business unit?

While dedicating internal IT resources to solve these challenges is a viable solution, it may not be the most efficient approach if Knowledge Management is not the primary focus of the business. In such cases, alternative strategies can better support the last mile for different business users, departments, or teams.

To this end, Enterprise Knowledge Management vendors specialize exclusively in KM. Their platforms and capabilities are built on years of experience working with customers, understanding their real-world needs. They offer a wide range of data connectors that seamlessly integrate with various enterprise technologies, constantly evolving to keep pace with the latest advancements. These vendors have dedicated customer success teams to assist with user onboarding, training, and support. They optimize their AI models to suit each customer’s requirements and provide ongoing assistance.

Ideally, business units and departments should either possess internal IT resources with the capacity to address these challenges or collaborate with approved vendors offering vertical market solutions.  Solutions should seamlessly integrate with existing standards, policies, access controls, and technologies within the enterprise, ensuring comprehensive support for Knowledge Management.

As we move forward into the future of Knowledge Management, the emphasis should be on collaborative efforts between internal IT resources and external vendors. By leveraging the strengths of both, enterprises can navigate the complexities of the last mile problem more effectively. In doing so, they not only enhance productivity and efficiency but also unlock the true transformative potential of Knowledge Management in the digital era. The last mile, once a formidable obstacle, becomes a pathway to seamless collaboration, innovation, and success in the knowledge-driven landscape of tomorrow.

Editor’s note: This article is in association with Lucy.

Photo by Bruno Saito

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