Knowledge management (KM) is no longer seen as a support function but has the potential to act as the catalyst to reap the real benefits of digital transformation.
Traditional Knowledge Management (KM) models focus on codifying knowledge nuggets derived from processes and projects and encourage stakeholders to share tacit and explicit knowledge, thus building knowledge repositories that can provide access to organisation knowledge to all stakeholders connected with the business. With the availability of digital tools for access and new modes for dissemination of knowledge, KM is no longer seen as a support function but has the potential to act as the catalyst to reap the real benefits of digital transformation of businesses.
Very often when digital transformation is considered, the aim is to consider one of the critical functions such as marketing or operations or an entire process which is reengineered with the help of digital interventions. We have come across successful case studies of enhanced customer experience or enhanced productivity resulting from integration with the digital ecosystems. The success in each of these cases is primarily on account of the ability to generate and analyse the data and use these insights to transform the way businesses are able to function.
The potential advantages arising out of data is driving the investment decision towards IoT, Robotics, AI and embedded systems which are throwing up a variety of data leading to exhaustive analytics. With the help of AI and advanced analytics, the signals and cues businesses are in a position to get, bring more precision to the decision making process.
In this context, it is important for KM practitioners to examine their current systems supporting KM and make their platforms intelligent by adding the cognitive power to it. While businesses may be creating intelligent systems to aid in their respective functions, it is important to create linkages of data, knowledge and business need and redesign the systems such that they are able to deal with dynamic situations.
The other challenge businesses have often experienced is how to convert tacit knowledge to explicit knowledge. Patterns are discernible from the transactions that take place via emails, portals, social networking sites and other such avenues and companies have the tools and the ability to tap and maximise access to hitherto unavailable tacit knowledge in easy-to-interpret formats.
KM today is not just about being able to support the just-in-time needs of the decision making process or making managers more savvy in being able to anticipate and proactively change course on the strength of insights derived from time to time, but when coupled with digital transformation, it also has the propensity to alter the business model and reposition businesses.
A good example of this is the possibilities that exists with primary health care centres. These health centres have access to a lot of data related to their patients gathered over a period of time but most of the data has so far not been digitally catalogued and accessed to get more understanding about the population they cater to. While there is definitely a need to digitise such data as the first step, the entire value chain connecting the medical equipment providers, the patients, the hospitals, the pharmacists and the insurance agencies will have an enormous potential to generate huge volumes of data at every stage of connecteness. This data when layered with cognitive tools could be used to service the customers better by being able to predict illnesses in the families and prevent occurance of diseases.
This would help in delivering patient centric solutions which are affordable and timely and enhance the overall wellbeing of the citizens. Another advantage is to enable all those engaged with the services to develop skills in those areas where there is a demand. Thus learning becomes purposeful and aligned with the core expectations and needs of the community.
KM has developed tentacles in its adjacencies and thus has become more responsive. In order for KM to occupy the centre stage of business, KM practitioners have to redefine what is knowledge meant to be for the business and make the knowledge acquisition and refreshing process dynamic.
The conventional approach of viewing the KM journey as one of capturing data, conversion of data to knowledge and knowledge to wisdom is giving way to the emerging model centred around data, data together with cognitive tools leading to insights, combination of insights leading to new knowledge and the ability to tap and apply the knowledge wisely creating winners in the marketplace.
Uma Ganesh is CEO, Global Talent Track, a corporate training solutions company.