31 Dec
Build organization-wide Knowledge Management system using AI and cognitive DMS
Over the years, digitalization has become an indispensable component of business. With the mass shifting of employees to remote working locations, the number of apps required to perform everyday business functions and resolve unique business challenges seamlessly has grown at an unprecedented rate.
Such apps infuse agility in operations and ensure effective employee engagement. But, the amount of unstructured data (in the form of images, videos, PDF, spreadsheets, etc.) generated from these apps and other external sources is growing exponentially. While organizations recognize the value of such data, it often gets locked away in multiple systems and siloed apps, making it challenging to find, explore, organize, and understand this information. Over time, such data loses discoverability and becomes dark.
Projections from IDC show that 80% of worldwide data will be unstructured by 2025. However, knowledge is and will continue to be an essential competitive differentiator when it comes to stimulating and driving an organization’s performance. In a survey conducted by Deloitte last year, 75% of surveyed organizations stated that creating and preserving knowledge across evolving workforces is important or very important for their success over the next 12-18 months. Still, only 9% claimed they were ready to address this trend.
Knowledge workers spend 30% of their time finding the information they need leading to millions of dollars in lost productivity. Since enterprises cannot store unstructured data in a database and tag and organize it properly, it becomes difficult to search, edit, and analyze. Moreover, unstructured data gone dark may contain personally identifiable information (PII), which, if left undiscovered, may lead to compliance violations and hefty fines.
Knowledge Management Challenges in a Remote Working Setup
- A growing number of business apps generate a vast amount of unstructured data.
- Difficult to search, analyze, and work with unstructured data
- Time to find information increases, leading to a significant loss in employee productivity and a poorly engaged workforce.
- With time, valuable enterprise knowledge may go dark and lose discoverability.
- Personally Identifiable Information (PII), if left undiscovered, may lead to serious compliance issues.
- Employees waste too much time trying to replicate files that they cannot find.
Hence, it’s becoming increasingly vital for organizations to build a robust knowledge management system (KMS) using artificial intelligence and a cognitive document management system (DMS) to harness the untapped value of unstructured data and find information faster.
Let’s explore further.
Building an organization-wide KMS using AI and cognitive DMS
Before we delve deeper into how organizations can leverage AI and cognitive DMS to develop a well-rounded knowledge management system, let’s first understand what knowledge management is.
Knowledge management refers to an organization’s ability to capture, store, structure, and distribute knowledge found in an organization’s internal network and capitalize upon the experience and expertise of its employees.
The problem with data that isn’t structured and floats around unorganized on SharePoint, local drives, emails, and siloed third-party apps is that employees need to spend too much time tracking such information. Additionally, employees may try to create duplicate files for data that they cannot find.
A well-organized, cognitive document management system (DMS) is a prerequisite for teams to manage knowledge and relevant data. A document management system is a central repository of data generated within an organization’s internal apps and other external sources. Information findability and knowledge management necessitate organizations to tag files, documents, and other content accurately using metadata.
The challenge with manual metadata management is that it’s error-prone, time-taking, and expensive. The average cost of manually tagging an item runs from $4 to $7. IDC says that an organization must spend $180 to recreate a document that isn’t found.
Problems with a Traditional Knowledge Management System
- Without the proper tags and classification, unstructured data like images, videos, PDFs, and spreadsheets are difficult to find in a sea of enterprise knowledge.
- Traditional knowledge management calls for manual data classification and meta-tagging
- Manual meta-tagging is a tedious and time-consuming task that is prone to frequent errors and inconsistency.
- The average cost to recreate a document that an employee cannot find is $180.
How does AI-powered knowledge management work?
The advent of AI has made it easier for organizations to leverage the treasure trove of knowledge within their systems. AI powered knowledge mining tools can crawl through files and documents and automate metadata generation, tagging, and classification and ensure consistent taxonomy usage – all this at lower costs and higher speed.
Mesh 3.0, our modern SharePoint intranet, provides knowledge mining tools powered by Microsoft’s Azure Cognitive Services to illuminate hidden knowledge and derive value from unstructured data.
Our five-step approach to knowledge mining includes the following processes –
1. Ingest: Centralize knowledge with flexible app integrations
Knowledge exists in structured and unstructured formats in both legacy and modern enterprise systems. Our knowledge mining tools leverage pre-built connectors to integrate first and third-party applications and bring all your data together on a single platform. Whether Office 365, CRM, LoB, or legacy ERP systems, get all your information on a single platform.
2. Enrich: AI provides you with the right meta tags!
In contrast to traditional knowledge management systems, AI-driven knowledge management tools ensure consistent and error-free enrichment of enterprise knowledge. As discussed above, AI-powered knowledge mining tools crawl through information, analyze data, assign it the right meta information, and classify it with the relevant tags. Such type of data enrichment improves information discoverability and helps employees find patterns and understand data better.
Moreover, since the bots analyze, interpret, and classify all content, there is consistency in the document tagging and classification process.
3. Organize: Create comprehensive topic pages with VIVA Topics
As a Microsoft Gold Partner, we integrate VIVA Topics into Mesh to compile all information related to a subject, including sites, files, videos, a brief description, and learning resources into Topic Cards. Such topic cards can be easily discovered when a user hovers over the word or phrase.
VIVA Topics uses AI to reason over content present in an organization’s KMS and organizes it into relevant categories like products, processes, projects, and customers. When a particular topic is mentioned in news and SharePoint pages, it is highlighted by the system. The user may merely move the cursor over it to find all the related knowledge on a single topic card.
4. Explore: Get personalized content at your fingertips with a cognitive search engine
By integrating Azure Cognitive Enterprise Search with your organization’s DMS, we leverage AI and NLP to improve search relevance and make data easily searchable. Our tools recognize the context in which the user searches and surfaces the most relevant search results from structured and unstructured data spread over multiple file formats. Features like auto-complete, geospatial search, keyword search, synonyms search, multimedia search, expertise finder, and multilingual search provide a rich user experience. Moreover, the system’s machine learning capability produces personalized search results based on past interactions with the user.
5. Share knowledge, collaborate over information, and access data from anywhere.
Mesh 3.0 offers social capabilities like enterprise messaging apps (Slack, Teams), channels, communities, and discussion forums that allow the one-click sharing of knowledge. Additionally, AI-powered knowledge bots help employees access files, documents, and other data instantly and on the go via natural language conversations.
In short, Mesh creates a powerful organization-wide KMS using AI and Microsoft’s Cognitive Services that lets information find you.
Indeed, a solid organization-wide KMS allows quick access to valuable knowledge, improves productivity and decision-making, enhances employee engagement, and reduces operational and compliance costs. And AI and cognitive DMS helps you build just that!
In other words, one can say that a robust, foolproof KMS ensures “the right information finds you.”
To know more about this topic, please feel free to schedule a personalized consultation with our knowledge management and digital workplace experts.
Poonam Chug is AVP - SaaS Strategy & Business. She has worked in various areas, right from designing and executing sales & account management strategies to reengineering digital workplace solutions. With her determined focus on our mission and progressive approach, she has achieved customer delight in the space of AI, Knowledge Mining, Content & Collaboration, Virtual Assistants, RPA and more. Backed with a deep understanding of customer needs and technology, she leads the SaaS business unit with an upshot of maximizing revenue while ensuring customer satisfaction.
Poonam Chug