Knowledge management leaders offer their predictions for 2021
As everyone looks to rebound from the COVID-19 pandemic, approaches are being put in place to improve processes and leverage new technologies. Use of cloud platforms, analytics to understand employee and customer experience, greater emphasis on smart collaboration, and understandable AI and machine learning are some of the strategies organizations are banking on to help them leap ahead in 2021.
Here, KM leaders offer their predictions for critical steps to achieve success in 2021.
Agility is critical. Year 2020 has gone perfectly according to plan" said no one ever. If 2020 has taught us anything, it’s just how imperative agility is to the success of companies trying to maintain momentum during uncertain times. Many organizations have had to “pivot” their business models, inventing new products and approaches to service delivery, rethink their supply chain, and revise the strategic plans drawn up just months ago. The performance gap will broaden between companies that have modernized their IT infrastructure with cloud collaboration and SaaS low code platform, and the ones who are still relying on legacy on premises systems.—AODocs CEO Stéphan Donzé
Leverage information from user behavior. One of the key prerequisites for forward-looking knowledge management is the capacity to extract data from the typically hundreds and thousands of data silos scattered throughout a company and link them together to create meaningful insights. For this purpose, “connectors” have long been used to retrieve data from siloed applications and move it to a kind of meta-level, where it can be correlated and contextualized. Knowledge management providers are now turning their focus toward analyzing factors that are found specifically in the way information is used. In technical parlance, this is known as the behavioral model for information retrieval system design. These factors include the importance of activities, past actions taken in connection with a particular piece of information, specific search behavior, and even the emotions that users associate with information—a topic that is very strongly related to customer experience or the “experience economy.” On the basis of behavioral analysis, today’s knowledge management systems can deliver exactly the information users need without overtaxing them. Or, to put it another way, the system personalizes the relevance of a given piece of information.—Daniel Fallmann, CEO of Mindbreeze
There will be growing demand for explainable AI/machine learning. Expect developers and business users to demand more insight and reasoning into AI and machine learning algorithms and how they are applied. Wide-scale adoption of these solutions will occur after we build trust in the underlying technology, which can only happen if the drivers for a given prediction are explained to the end user. For example, in the context of machine learning in recruiting—why a given candidate is recommended for a particular role is important both to allow the hiring manager to make an informed decision and also to expose the risk of unintentional (or malicious) bias in hiring practices. Because most AI/ML models are somewhat of a black box, users and developers don’t have visibility into why the models make the decisions they do. More insight into this process will ensure people understand the factors on which the model is basing its decision, and it will also help developers prevent an adversary from exploiting it.—Jim Stratton, CTO, Workday
The pandemic has sparked a new wave of digital transformation for businesses everywhere. Remote work policies have spurred the adoption of additional software to fill in gaps and, for many businesses, these policies seem unlikely to lift anytime soon. Working from home has led to a greater need to integrate across the tech stack than ever before – without integration, mission-critical data will remain siloed, making remote-work collaboration even more of a challenge. In addition, companies whose digital transformation initiatives have lagged and continue to rely on costly on-premises workstations and servers at their offices will more acutely feel the pain of those ongoing sunk costs as their teams continue to work from home. As a result, it will be more important than ever for companies to hasten their migration to the cloud to ensure their teams, which are likely to remain distributed throughout the year, can work from anywhere. Projections suggest the market for digital transformation will grow 22.7% annually to $3.3B by 2025. By integrating these cloud services, we expect businesses to increase productivity by more than 200% by the end of 2021.—Rich Waldron, CEO and co-founder, Tray.io
Knowledge management will finally find its place among business-critical business functions in 2021 as the business imperative for collaboration drives KM higher up the board agenda. With the overnight switch to a dispersed workforce, firms have come to starkly realize the business importance of collaboration, in the absence of office-based interactions. Additionally, in many firms, access to important documents, information and the collective "experience" was restricted—be that due to poor VPN and connectivity issues, security and data protection protocols embedded in firms’ document and wider content management systems, which were configured for an office-based work environment, or a lack of a formal and structured approach to enterprise-wide KM. In 2021, the imperative for secure access to and re-use of intellectual property for business efficiency and meaningful collaboration, will drive the need for KM. Recognizing the importance of KM at par with the other business-critical functions in the organization.—Javier Magaña, Technical Director at Lexsoft Systems
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