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1 October 2020

Leading in the next normal with cross-channel knowledge sharing

Victor Snyder spoke with Sagi Eliyahu, the CEO of KMS Lighthouse - knowledge management solution for enterprises - about the importance of knowledge sharing amid lockdown. Founded in 2012, KMS Lighthouse works with multinational brands such as DHL, GE Healthcare, Orange and AIG.

Since the beginning of the COVID-19 situation, companies across verticals have been reorganizing the way they handle knowledge management, as well as the various ways in which this knowledge can be accessed. Most teams are interacting less often with customers in person, and entire organizations are working from home, so self-service access to updated information has become pivotal.

I recently spoke with Eliyahu about his company’s growth amid these shifts.

The pandemic has changed many of the dynamics surrounding self-service customer support and information sharing across newly remote teams, so it makes sense that you’ve been seeing significant business growth in recent months. What do most people misunderstand when it comes to leveraging organizational knowledge to optimize these two very different use cases?

Absolutely – the two areas of customer self-service and the need to support remote teams have been significant drivers that push companies to undertake digital transformation.

Many of our customers have been able to deploy projects in a few months for areas which had been discussed or stalled for many years. The main catalyst has been the need to enable employees to keep working as they used to work, but in the new environment, and to support customers in the best way possible.

The organizations that are succeeding today are those that have come to understand that their digital transformation will only be as good as their knowledge base. This awareness has encouraged companies to deploy omnichannel knowledge systems to support their customers and teams at the same time, using authorization controls.

Many theorists believe that the best leaders don’t lead by example and don’t assert their vision on anyone else – they simply give their teams the tools and information assets they need to succeed on their own and get out of the way. In this sense, to what extent do you see knowledge assets in the enterprise as an expression of leadership, and to what extent does knowledge management speak to your own company leadership style?

I’m a big believer in that leadership principle, mostly because the old ways of onboarding and re-training employees are dead.

In an ideal world, organizations would invest large amounts of time and money on training and education to inform their team for the best approaches to handle different situations. This would include product information, support, sales and customer care. In reality, especially in organizations driven by agents whose employment churn rates can easily reach 30% in a given year, this requires a different approach.

Today’s business environments are so dynamic, that you can’t spend 22 weeks training someone in a given process, only for that process to be revamped altogether a year later, or for that employee to move on. It just isn’t sustainable. You’re better off investing in setting people up to quickly and easily find the information they need.

The “next normal” places even more emphasis on this need, since today’s veteran employees and new recruits alike are working remotely, so they can’t just lean over into the next cubicle to ask a colleague or a superior what to do in any given scenario – they need to be able to respond on their own and get it right, on the fly. As a result, dependable, on-demand knowledge resources have changed from being nice-to-have into must-have, as company leaders depend on individuals’ ability to manage themselves.

You seem to be “all in” on the value that AI has to offer businesses today. What is it about knowledge management specifically that makes it so hard for humans to properly find information on their own?

Traditionally, the main challenge associated with finding information with legacy knowledge management solutions has been the dependence on tagging content and teaching users how to search, using specific keywords for specific topics. The success of next-generation knowledge management started with the ability to enable users to find the content they need, when it’s needed, without anyone needing to manually tag entries.

AI and machine learning technology are critical to assist the system to understand user intent and to learn from user behaviour. This is why the adoption of a knowledge base with AI and machine learning components dramatically increases the ability to get it right.

What use case for chatbots – sales, support or internal knowledge sharing – has seen the biggest growth at KMS Lighthouse in recent months?

I’d say that customer-facing support chatbots are seeing the biggest demand growth on our end. We’ve been receiving a high volume of requests to integrate our knowledge management solution with various chatbot engines, but also to other third-party technologies. Most of our clients come to us having already realized that there’s a lot to be gained by holistically tackling all three of the use cases you listed, as one. 

The situation with the pandemic has changed everything. Prospective customers who might have once spent 18 months considering their options for digital transformation platform partners are now doing so in four to six weeks. We’re also seeing more senior leaders from enterprise companies, like CEOs and board members, reaching out to us directly for more details on knowledge management-integrated chatbots, which shows what a strategic priority this has become to business continuity.

They need chatbots to provide the same definitive answers, regardless of if the chatbot is being used by customers or the company’s own agents. The content may be packaged a bit differently, but the answers need to be consistent.