How Knowledge Mismanagement is Costing Your Company Millions - SPONSOR CONTENT FROM BLOOMFIRE

Harvard Business Review

24-04-2025

Executives are laser-focused on optimizing their most valuable assets – people, intellectual property, and proprietary technology. But many overlook one asset that has the power to drive revenue, productivity, and innovation: enterprise knowledge.
Inefficiency directly costs a business an average of 25% of its annual revenue, according to Bloomfire's Value of Enterprise Intelligence 2025 report. For a Fortune 500 company with $9 billion in revenue, that can translate to $2.4 billion in enterprise value annually—hurting revenue and productivity, stifling innovation, and increasing operating costs.
Many organizations regard knowledge as an afterthought rather than a business asset that drives financial performance. Knowledge often remains unaccounted for on balance sheets, hidden in siloed systems, and mismanaged to the point of becoming a liability. Redundant, trivial, conflicting, and outdated information can cloud decision making that fails to deliver key results.
It's not knowledge itself that's the problem, but how it's managed, accessed, and activated.
Embracing the strategy of Enterprise Intelligence can represent a fundamental shift: instead of treating knowledge as something to store and retrieve, Enterprise Intelligence transforms knowledge into a continuously evolving, revenue-driving force. Organizations that can fully activate their knowledge through AI-powered insights, intelligent search, and dynamic knowledge orchestration can see a network effect delivering measurable business results, such as:
• 47% higher success in achieving objectives and key results (OKRs)
• 39% improvement in teams' speed and efficiency
• A 23% lift in productivity as measured by revenue per employee
Without a plan to optimize Enterprise Intelligence, companies may be leaving billions of dollars on the table. The good news? A solution is within reach.
Knowledge on the Balance Sheet
Some organizations that attempt to account for their knowledge assets typically lump them in with intangibles like brand value and goodwill. This lack of precision undervalues the role of knowledge in driving revenue and operational efficiency. Even worse, it allows critical knowledge to depreciate, just as a physical asset would—but without oversight or maintenance.
The financial impact of poor knowledge management (KM) is staggering:
• Employees waste an average of 10% of their workweek searching for information they need to do their job.
• Siloed knowledge slows cross-functional collaboration up to 30%, leading to redundant work and misalignment.
• The average company loses $12.9 million annually due to poor data quality, according to Gartner.
With knowledge disconnected, organizations lose efficiency and revenue in unrealized opportunities across every critical business function.
The Value of Enterprise Intelligence 2025 report, based on six months of data from 10,000 customers at 115 companies, quantifies the potential revenue gains of optimizing knowledge-sharing and accessibility:
• $685 million from increased workforce engagement
• $384 million from higher-quality work and better decision-making
• $106 million from employee motivation to learn new skills
Knowledge Fractured Across Silos
When your employees seek critical information scattered across shared drives, email threads, customer relationship management (CRM) systems, wikis, and individual workers' minds, they spend an average of 21% of their work time searching for knowledge and another 14% recreating information they couldn't find.
Instead of treating enterprise knowledge as a dynamic, interconnected ecosystem, most organizations have built a patchwork of disconnected tools. Each tool solves a problem in isolation but creates friction at the intersections.
The results?
• AI models surface outdated knowledge with confidence, creating misinformation.
• Chatbots give contradictory answers based on siloed department documentation.
• Employees make strategic decisions using incomplete or incorrect data.
Companies adopting an Enterprise Intelligence mindset can recover at least 50% of their employees' search efforts and, in turn, see a 30% increase in cross-functional collaboration. Instead of relying on fragmented systems that act as barriers, organizations that embrace Enterprise Intelligence create a unified digital infrastructure where knowledge flows seamlessly between teams, platforms, and workflows.
Passive Storage to Active Intelligence
Traditional KM and enterprise search (ES) practices are no longer enough. Simply capturing and storing information in a searchable system doesn't solve the bigger challenge of surfacing the right insights at the right time in the proper context.
That's where the pathway to Enterprise Intelligence becomes clear.
Many companies still view KM as a discipline and ES as a feature, with a layer of AI. Applying Enterprise Intelligence can combine these elements to move from static information storage to dynamic, AI-powered knowledge orchestration.
Enterprise Intelligence is an evolution of knowledge management. It is the convergence of traditional knowledge management, enterprise search, and business intelligence with AI-driven automation to create a dynamic, continuously improving knowledge ecosystem.
With Enterprise Intelligence, knowledge no longer sits in isolated repositories waiting to be retrieved. Instead, it:
• Surfaces relevant insights automatically, reducing search time
• Identifies and corrects outdated or redundant information
• Ensures decision makers have contextualized, high-quality data at their fingertips
By applying Enterprise Intelligence, organizations unlock a compounding network effect resulting in faster innovation cycles, higher revenue growth, improved employee retention, improved customer retention, and a stronger competitive edge.
Companies implementing the principles of Enterprise Intelligence report:
• 32% faster issue resolution in customer service teams
• 28% average improvement in Net Promoter Scores (NPS) from hyper-personalized AI insights
• 42% increase in service consistency across departments and geographies
As the foundation for Enterprise Intelligence solidifies, organizations need to actively identify gaps, flag inconsistencies, and eliminate the redundant, outdated, conflicting, and trivial content that erodes decision-making over time.
The next generation of enterprise platforms must be built around a self-healing knowledge base—one that not only stores knowledge but constantly improves it. This intelligent foundation supports AI-powered automation, streamlines workflows, and ensures that every insight delivered is accurate, up to date, and ready for action.
Maintaining knowledge quality isn't just operational hygiene—it's the key to unlocking long-term digital transformation and sustainable competitive advantage.
What Stands in the Way Becomes the Way
Most organizations already have the information necessary to unlock these benefits, solve big problems, drive strategy, and gain a competitive advantage. The challenge is ensuring this knowledge is connected and contextualized, actively drives decision-making, and is always accessible to every employee. Recognizing and codifying knowledge as a business asset is the first step to embracing Enterprise Intelligence.
Leaders who don't recognize knowledge as a core business asset risk stagnation, inefficiency, and missed opportunities. Those embracing Enterprise Intelligence, treating knowledge as a critical, revenue-driving asset, can unlock greater agility, profitability, and long-term resilience, potentially opening the door to millions of dollars in revenue from productivity growth and operational efficiency.
The question is: Where does your company's knowledge fall on the balance sheet?