Any Chief Information Officer (CIO) who has gone through at least one round of outsourcing will agree that one of the most understated levers for success of outsourcing programs is around the efficacy of the Knowledge Transition process. When an incumbent team executes work over several years, the knowledge to perform these tasks develops and grows over time. This knowledge needs to be effectively transitioned to the incoming team during transition. The success of the outsourcing program depends on how well the knowledge transition process is executed. Challenges of a good transition are amplified if the outgoing team is not supportive or hostile to the change in service ownership. An existing well-maintained knowledge repository increases the chances of a successful transition by several notches as it provides the necessary starting point for the new team to learn, disseminate and build their knowledge of the operations. It also helps reduce the dependence on individuals for the success of the transition.
Types of Knowledge
When an incoming team takes over work from an incumbent team performing the required tasks, they need to move up an accelerated learning curve to ensure that they are able to deliver the same level of services as the incumbent team in the shortest time. This understanding also forms the foundation of any future transformation programs that may be planned.
A key to attaining this goal is a very good understanding by the new team of the “What’s, When’s and How’s” of delivering the expected service. Such understanding requires capturing knowledge developed by the incumbent team over the years which can be classified as:
- Structured and formal knowledge: Knowledge that exists in documented form and has a structure to it. Examples could be runbooks and product support documentation.
- Unstructured and informal knowledge: Knowledge that exists in an unstructured form across sources like e-mails, forum posts, minutes of meetings and smaller related sets of data across the enterprise.
- Tribal knowledge: Knowledge that is most often existing with tenured individuals based on their experience of delivering services. This is often undocumented and sometimes even unknown to the holder of the knowledge until they need to use it, which makes it more challenging to deal with.
Setting Up Knowledge Management Processes
Recognizing this, several enterprises have put in efforts to build a knowledge management process, the core to which is some sort of repository to archive such knowledge. The idea is to capture as much structured knowledge as possible and also convert some of the unstructured knowledge into structured knowledge. Efforts to convert tribal knowledge into structured knowledge are trickier because such information is tacit or invisible. The very existence and extent of such knowledge can never be known for sure even by the people who keep them in the safest place of them all – in their heads!
While organizations have tried building knowledge management systems, the success rate of having an effective and active knowledge system is low for several reasons:
- Lack of sustained focus due to competing operational and business priorities.
- Difficulty in defining the full scope and extent of the “knowledge sprawl” within an enterprise.
- Greater difficulty in keeping such knowledge current over time. Several organizations start their efforts to have a robust knowledge base but fail to focus on developing a process to ensure that the knowledge base is updated periodically. This is the single biggest challenge that needs to be addressed. In my experience of over two decades with some of the largest global enterprises (and mid-sized ones too), I am yet to come across an enterprise that has been able to address this critical issue consistently.
- In large enterprises, siloed knowledge islands are not unknown, which presents a case for knowledge repository consolidation before value can be extracted through such efforts.
Changing Requirements and Drivers
The changing services models have brought about new knowledge management needs. It is no longer sufficient to have a single dimension keyword-based lookup in a knowledge management database. With the move toward outcome-based service levels, the knowledge captured should also be context sensitive and searchable based on the context and business scenario; this is significantly more substantial than simply a keyword search. This makes the traditional way of capturing and searching knowledge bases challenging.
Another evolution has been the need to make knowledge bases available to multiple teams instead of the traditional use of a given knowledge base by a single team. As teams work in an agile framework there’s a greater need for several teams to share access and even update a single set of knowledge base. This brings in new requirements in the way the data is captured, stored, archived, accessed, updated and usage audit trails established.
With the automation charter bringing on bots in several areas like a service desk, it is very important to have a strong knowledge base that is regularly updated so that users can be provided updated solutions by the bots. As bots are getting smarter and even executing solutions for users, a good knowledge base really underpins the success of increased automation and improved user experience.
Additionally, with agile DevOps at play and deployments on cloud, users are accessing applications almost as soon as they are released. This provides little time for support teams to build a comprehensive knowledge repository. It is hence important to include some of these activities within the development efforts to ensure user support quality does not become a reason for low adoption or user activity.
Further, with outsourcing deals getting smaller in Total Contract Value (TCV) and contract period, a lot of support has to be enabled on a self-service or remote-assist mode as the costs of high touch or in-person support are no longer justified. A good knowledge base plays at the center of such support models in which users can be assisted in alternate models.
Another strong case for sustained investment in a strong knowledge management system comes out of the impact on service levels with high staff attrition. A knowledge repository can certainly help reduce the impact of staff attrition or even staff rotation where a service provider may keep rotating some key staff across multiple clients.
What’s the Best Way to Start?
Given the criticality, need, challenges and changing requirements of having a robust and “living” knowledge management process, enterprises that have seen greater success have done the following:
- Accepted that it is not possible to have a knowledge management process that can capture all existing knowledge. With the right focus and effort, most of the structured, unstructured and even some of the tribal knowledge was captured over time.
- Drove the focus on a knowledge management process at a time when the incumbent team had at least 12 to 18 months to develop and build a knowledge base. Efforts to build a knowledge base in a few weeks or months before an imminent change in service ownership are always rushed and too tactical to succeed.
- Assigned a Knowledge Leader, a role that can be rotated among the leaders from the teams that are ultimately the consumers of this knowledge base. This ensured that the approach was driven toward the customers of the knowledge process and repository being built.
- Invested in a robust web-enabled platform, making it accessible and intuitive to use. Keeping it on a cloud based platform ensured it was easily and cost-effectively accessed, stored, secured and backed up.
- Built the process to keep the knowledge base current, aligned its success to the performance of the teams responsible to build and use it, audited the knowledge repository periodically and tracked its progress at the same level as other critical business technology indicators.
- Linked employee training to the knowledge base. Industry experts suggest this is a great way to ensure that the knowledge management process is active with additional focus to ensure new employees are not trained on older systems and processes.
While investing time and resources in setting up and managing a knowledge management process cannot guarantee against challenges during service transition, it surely helps mitigate the risk substantially and also insulates the enterprise from service quality issues when changing service providers and when staff attrition occurs. By retaining the ownership of such a knowledge repository, enterprises are less likely to be forced to continue with incumbent teams to avoid transition turmoil. An enterprise-owned knowledge management repository allows enterprises to freely exercise the choices in changing service ownerships to ensure the highest quality of customer experience.