Choosing the right software will go a long way in creating the capability for knowledge management. The key parameters to be considered during the process of shortlisting the tool are as follows:
Define your company requirements
Who would be the users of the KM system? Will it be used internally or be exposed to external customers as well?
Are you looking for a cloud-based solution or on-premise or a mix of both?
Does the tool provide customization ability and integration layer to connect to other subsystems of the organization?
Features provided by KMS
Evaluate the list of features that the tool provides by default and how much you will need to customize to meet your requirements.
Key features that a typical software vendor will provide are listed in this document but other vendors may provide added features like mobile app solution, unlimited capacity, discounted licensing fees, slice and dice analytics and so on. You need to consider these factors before deciding your final choice of the vendor
How is the user interface implemented for your usage? It needs to be intuitive. Does the interface provide you at a glance how to do basic functions like search, reporting and content management?
Training and Support
Assess the learning curve for the users of the system. Does the company offer good technical support, user support, guides, tutorials and training? Is there an online forum of the user community to share tips and solutions to common problems? Do you have visibility of the product roadmap and upgrade cycles, communication through various channels like voice, email, chat and so on?
Total Cost of Ownership
The cost of implementing a good and robust KMS involves not only the cost of the software but also necessary infrastructure to deploy and the people who are required to maintain it. Cloud-based solutions would have lesser overheads and more suited to mid-tier companies. But companies who need an on-premise solution need to consider additional costs.
Also, investment in KMS is a long term decision and hence ongoing cost would have a bearing.
What are the challenges in adopting Knowledge Management Software?
You have to ascertain whether you have the need to invest in formal Knowledge Management Software considering the size of your company, the complexity of the projects undertaken and the diversity of the departments involved in the overall workflow. How does the manual effort currently function and does it necessitate the need for automation?
Knowledge Management is a means, not an end
Training and rollout to all relevant stakeholders are of prime importance in adopting the software. Each and every stakeholder should be comfortable with using the software on the expected lines.
The software vendor needs to have a good track record of technical and user-based support and training for the users of the software. As stated above, this could pose a major challenge if not given its due importance.
For the first time users of the Knowledge Management System, they should brace for resistance from people within and outside the organization. The organization must use a top-down approach to communicate the benefits and value of the KM system in terms of efficiency, productivity and cost savings. This management of change is extremely important to ensure that all the involved stakeholders are on the same page.
Once the system is in place, the other challenges will be around keeping the momentum going, ensuring that all stakeholders understand its value and accepting it as part of their work and always keep it current and relevant. Often, KM is considered as a peripheral activity and hence needs constant motivation, incentives, and senior management support,
Trends in Knowledge Management System?
The use of social media is very widespread and provides a rich source of information that can be mined for usable knowledge. The Knowledge Management System can integrate with the social media and leverage the content for the organization’s benefit
Business Intelligence and Analytics
The latest BI tools and technologies like Artificial Intelligence and Machine Learning can handle large data sets and thus enable the processing of patterns, trends, insights, and other useful information. Organizations that harness such BI tools for their knowledge management will have a better success rate with their business decisions, productivity, and operational efficiencies.
KM Maturity Model
KM Maturity Model is a structured approach to implement Knowledge Management System. It would be helpful if you are able to arrive at an analysis of your current and to-be state of knowledge management. How does your KM system measure against the industry models and frameworks? Your assessment would indicate the current maturity state and you can then plan for improvements to the system for higher maturity