The issue of personalisation and its impact on KM

Author Hal Kirkwood BIR Board member, Bodleian Business Librarian, Said Business School, University of Oxford. President, Special Lib Assoc. 2019

The current state of affairs was on full display at the last (November 2018) KM World Conference in Washington DC.  I had the opportunity to attend for several days to see first-hand what is happening in the knowledge management realm.  There were many themes prevalent throughout the conference; each day consisted of 3 tracks. The Day One tracks focused on KM & Culture, Digital Workspaces, KM Tools & Tech.  Day Two tracks focused on Knowledge-Sharing Processes, Content Management, and KM Culture & Collaboration.  Key takeaways and themes were the importance of collaboration; identifying the right tools to fit the problem and your organization’s culture; designing environments, both physical and virtual, for employees and clients; determining how to transfer knowledge; developing information ecosystems; and the implementation and impact of artificial intelligence and machine learning.  The clear underlying theme is the continuing intersection of people and technology.

One aspect that is gaining traction into KM is personalization; utilizing individual user data to provide a more focused recommendation or timely suggestion. Technology, in conjunction with access to massive amounts of data, is driving momentum towards ever greater personalization.  Personalization, not customization.  Consumers become weary of making choices when these systems can make relevant choices for them based on their prior experiences.  Consumers are showing preferences towards companies that provide effective, relevant personalization.  However, since knowledge management focuses on the internal management of a company’s knowledge personalization at the employee level has been slower to develop.

Personalization has primarily been within the purview of marketing and consumer buying habits.  The power of personalization relies on a combination of data that was once inaccessible; namely geolocation crossed with purchasing habits.  It has become especially powerful when the immediacy of time is included to deliver personalized information and recommendations to a potential customer at the most optimal moment to affect their behavior.  Artificial intelligence and machine learning will make significant inroads in the personalization strategies of companies marketing plans to provide more focused experiences for customers.  1

The challenge for many companies is to scale this personalization to the masses.  AI and machine learning will increase the capacity to track multiple data points for larger numbers of customers. This will increase the expectation of customers for improving levels of service that meet their exact needs and requirements.  Evidence shows that it is highly successful when implemented in increasing sales and customer satisfaction. but that most companies are not implementing it.

Every company is now looking for ways to gather customer data that can be used to make more informed, and more specific, decisions on individuals.  Many companies are also capturing terabytes of data on customer behavior to then sell to businesses for this very reason. There is the issue however, that the attempt at personalization will be wrong based on the AI processing poor or inaccurate information.  As personalization becomes more accurate, and more ubiquitous, it will seem all the more glaring when AI-driven personalization is incorrect. Consumers are likely to feel more uncomfortable about what data is ‘out there’ on them and its accuracy, or lack thereof.  This is a complicated issue of human perception of technologically driven services.  How much control we have over all of this data is also a major concern.  In Europe, GDPR is beginning to make an impact by providing consumers with more control over what data is collected and how it is used.  It remains to be seen how exactly this will impact the data collection and utilization process. Many consumers, when surveyed, approve of the use of their data if they will receive a tangible benefit. There are some conversations taking place about implementing some form of GDPR in the United States, but little in the way of concrete details have provided.

Companies such as Netflix, Spotify, Amazon, and several other key companies are pursuing, and leading, the development of even greater data collection to develop ever more enhanced services for individuals.  Areas like physical fitness, healthcare, and personal finance are becoming driven by apps that collect personal data to then provide recommendations relevant to an individual’s life.  Consumers will allow themselves to be tracked in this way because of the return on investment of their personal data.

The majority of personalization development has been in the B2C marketplace; there will likely be increased demand for it on the B2B side.  The key element will be systems that collect client-level data that can be assessed by AI applications.  Many companies are moving into this to deliver solutions for collecting and analyzing data.  Business intelligence systems will develop as AI and machine learning are layered into them for much greater personalization of services and deliveries to corporate clientele. Companies must make the choice to implement an AI-based system to drive their decisions.  Not an easy task when it often requires a significant operational and cultural shift in how they conduct business.  Companies making this decision are likely to benefit but must be wary of the myriad pitfalls.  What ramifications this will have on the competitiveness of companies and markets, as well as within the broader business information environment still remains to be seen.

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