The resurrection of Knowledge Management in the digital workplace

Introduction

Knowledge is one of the most valuable assets in an organization. Yet, many companies do not think strategically about their organizational knowledge. Most companies don’t know what they know. They haven’t mapped out which knowledge is key to future success, how critical knowledge should be managed, or which areas of knowledge should be nurtured.  

The definition of Knowledge Management (KM) has been the subject of many academic articles. But in simple terms, it is the systematic process of generating, organizing, sharing, storing and accessing knowledge within and between organizations. KM is an approach to thinking strategically about organizational knowledge and harnessing it to be more efficient, innovative and competitive. 

Initially hailed as a panacea for myriad organizational challenges, it was later dismissed as a management fad, with many former proponents sounding its death knell. And in a way, it did die. It declined because traditional approaches to KM could not keep up with the emergence of new technologies and methodologies. 

But today, KM is very much alive and kicking. Digital transformation and the need for organizations to stay competitive in a rapidly evolving landscape have driven a resurgence in KM. Now, more than ever, organizations need to be able to identify their strategic and critical knowledge, and to manage it as well as any other organizational asset. KM as a field has evolved and is now a strategic pillar for any organization wanting to stay ahead. 

The evolution of Knowledge Management

The origin of KM can be traced back to the era of ‘knowledge workers’ in the 1960s, identified by renowned management theorist, Peter Drucker. Increasingly, there was a recognition of the value of ‘intellectual capital’ – a term still used today. 

The concept of KM became more defined in the 1990s, with contributions from Nonaka and Takeuchi, bringing KM into the strategic spotlight. Their views on how knowledge is generated and managed within organizations inspired a series of strategic knowledge management initiatives that paved the way for Knowledge Management as a discipline. 

As Nonaka and Takeuchi’s work gained traction, knowledge-intensive sectors such as management consulting, oil and gas, pharmaceuticals and engineering were the first to embrace formal KM programmes. Between the late 1990s and early 2000s, KM expanded across industry. It was adopted as a key strategic asset and incorporated into other initiatives such as organizational learning. 

New KM roles emerged, including that of the Chief Knowledge Officer (CKO). This demonstrated the strategic positioning of KM and its central role in organizational growth and development. 

Over the decades, KM has evolved significantly. Initially, the emphasis was on documenting organizational knowledge and storing it in a database where it could be easily accessed. Knowledge Managers focused on capturing best practices and lessons learned, and IT departments invested in repositories and databases. Document management and information retrieval were the main areas of focus. 

By 2000, the issues with this approach were becoming clear. Databases were where ‘lessons learned’ went to die. ‘Best practices’ were seldom extracted and re-used. It wasn’t easy to get people to contribute to the repositories, and few people utilized previously captured knowledge. Content quickly became outdated, and the value of repositories and knowledge databases declined. 

Soon, the idea of knowledge as ‘social’ started to gain traction. The concept of Communities of Practicegained popularity. Borrowing from Toyota’s ‘just-in-time’ approach to manufacturing, Communities of Practice created a way for companies to facilitate the exchange of knowledge at the point when it was needed. 

At the same time, ‘social collaboration’ was the hottest of topics, and KM trailblazers were adopting digital collaboration platforms such as Yammer. The intranet became ‘social’, and the role of the Knowledge Manager started to incorporate intranet management, community management and facilitation. The focus was on harnessing collective knowledge. 

As we move deeper into the digital age, KM is once again seeing a revival. KM roles are being advertised in sectors where the field previously didn’t exist – including technology, transport, manufacturing, construction and entertainment. 

Drivers of the revival

The revival of KM is influenced by several key factors reshaping how organizations capture, store and utilize knowledge. These drivers are crucial for businesses seeking to maintain a competitive edge, foster innovation and improve operational efficiency.

Technological advancements

The rise of artificial intelligence (AI) and machine learning offers new opportunities for KM. Generative AI tools,  such as ChatGPT and Copilot, have been rapidly adopted across industries. Yet, most organizations are still grappling with what this means for their industries and how best to utilize and regulate AI in the day-to-day work of their employees. 

KM plays a critical role in supporting the rollout of generative AI. Organizational information and data on which an AI model is trained must be accurate, up-to-date and well organized. The adage of ‘rubbish in, rubbish out’ still applies. KM processes ensure the integrity of AI model data inputs, impacting the outputs. For AI and machine learning to work well in organizations, they must be implemented using KM principles.

Some of these include:

• creation and management of taxonomies 
• development and execution of data and information standards 
• ongoing testing, measurement and refinement 
• associated change management and training.

The integration of AI and machine learning into KM systems has affected how organizations manage knowledge. These technologies facilitate the automation of knowledge processes, enabling more efficient data capture, storage and retrieval. AI-driven analytics help organizations to gain insights from vast data, improving decision-making and innovation capabilities.

Increased competition and market dynamics

In an increasingly connected and homogenous world, organizations are under pressure to innovate and differentiate themselves. Effective KM allows companies to leverage their knowledge assets to respond quickly to market changes and customer demands. It builds the capability and knowledge to navigate the evolving global business landscape. This agility is crucial for maintaining a competitive advantage and driving business growth. For many companies newly adopting KM into their organizations, this is the key driver. 

Collaboration and connectivity
The shift to remote working following the recent pandemic has created a need for improved knowledge sharing and collaboration across geographically dispersed teams. KM is essential for facilitating digital collaboration and creating opportunities for connection in the digital workplace. This connectivity is vital for fostering innovation and improving overall productivity.

The classic collection, organization and dissemination of critical knowledge and information is even more important in geographically dispersed organizations.  With more and more people working remotely, the need for better management and organization of digital assets is obvious.

Renewed executive interest
There is a growing recognition among business leaders of the strategic value of KM. This renewed interest is partly driven by the shift towards remote and hybrid work models, which require robust KM systems to ensure seamless knowledge sharing and collaboration. Additionally, the focus on AI has further highlighted the importance of KM in leveraging technology to enhance business processes.

These factors underscore the importance of KM as a strategic asset in the digital age, enabling organizations to harness their knowledge for improved efficiency, innovation and competitive advantage.

The future of KM

AI and machine learning are set to play a pivotal role in the future of KM. These technologies will continue to automate and enhance knowledge processes, making information more accessible and actionable. AI-driven analytics will help organizations to identify and prioritize valuable knowledge assets, improving decision-making and operational efficiency. The integration of AI in KM systems will also enhance search capabilities, enabling more precise and relevant information retrieval. 

As organizations gather more data about their employees and customers, KM systems will become more personalized. This personalization will ensure that users receive relevant information tailored to their specific needs and roles. Additionally, there will be a greater emphasis on user-generated content, encouraging employees to share their expertise and experiences through interactive platforms.

The shift towards cloud-based KM systems will continue, offering scalability, cost-effectiveness and ease of access. These platforms will facilitate real-time collaboration and knowledge sharing among geographically dispersed teams.

Organizations will prioritize identifying, mapping and retaining critical knowledge to mitigate the risks associated with employee (and freelancer) turnover and knowledge loss. Proactive knowledge retention measures will be essential, encouraging subject matter experts to document and share their knowledge as part of routine workflows.

 As KM systems store and process sensitive organizational information, data privacy and security will become top priorities. Organizations will seek solutions that ensure robust security measures to protect their knowledge assets from cyber threats.

The future of KM will see integration with emerging technologies such as blockchain and augmented reality. Blockchain can enhance the security and traceability of knowledge assets, while augmented reality can provide immersive learning experiences and knowledge-sharing opportunities.

The strategic value of KM is increasingly recognized by business leaders, leading to continued investment in KM initiatives. This interest is driven by the need for effective knowledge sharing in remote and hybrid work environments, and the integration of AI capabilities to support digital transformation efforts.

The revival of knowledge management in the digital age is a testament to the enduring importance of knowledge as a strategic asset. 

Related resources

• Why you can’t manage knowledge – and what to do instead
• Why robust information management is critical for digital workplace governance
• The Findability Playbook

Categorised in: Digital workplace, Knowledge Management