by Greg Oxton
Date Published - Last Updated February 25, 2016

What is the future of knowledge management? The quick answer is multi: multimedia, multichannel, and multilingual. As we look ahead two to three years, I believe these three attributes will have a powerful effect on several key trends in service and support, all of which have implications for the future of knowledge management:

  1. A shift in focus from our internal productivity to our customers’ productivity 
  2. Customer self-service and intelligent swarming 
  3. Global, mobile, and social aspects of society and business

These emerging trends and attributes will impact both knowledge content and the processes we use to capture, maintain, and access knowledge, and they’ll play an increasingly important role in the organization’s value proposition.

A Shift in Focus: Value Erosion and Value Adds

Over the past few years, the members of the Consortium for Service Innovation have been developing principles and practices for a leadership model for service excellence. In one of the earliest discussions, Cisco’s Ana Pinzcuk asked, “What do we mean by service excellence?” There was a pause in the conversation—sometimes the simplest questions are the hardest to answer! After some discussion we came up with the following definition: Service excellence is about maximizing the customer’s realized value from our products and services.

If we accept this definition for service excellence, we’re expanding our scope: in addition to concern for our own productivity (e.g., number of cases closed, time to resolve), we also must focus on our customer’s experience, productivity, and success.

But what do we mean by realized value? BMC’s Christophe Bodin, who was then a VP at Oracle, proposed that realized value is inversely related to value erosion. The neutral point for customer-realized value is based on the customer’s expectations: can they accomplish their goal or intent with the expected amount of effort? If we can exceed those expectations, then we have added value. If we fall short of those expectations, we have value erosion.

The value erosion model exposes the fact that, from the customer’s point of view, by the time an incident/case is opened, the value erosion is extreme. If we’re really focused on customer-realized value, the opportunities to minimize value erosion occur well before the customer opens an incident/case. Yet, service and support organizations focus the vast majority of their efforts on improving the efficiency and effectiveness of their incident resolution processes. While that focus is well intentioned, in terms of the customer’s experience of realized value, it’s far too late to recover.

There are several things we can do to minimize value erosion before we pass the point of no return: 

  • Chat, for quickly answering questions about simple issues 
  • Self-service and forums, for providing information about known issues and questions in a way that is findable and usable by the customer 
  • Context-sensitive help, for making suggestions based on the functions being used or the customer’s clickstream patterns 
  • Automation, for detecting and correcting issues 
  • Elimination, for conducting root cause analysis and taking corrective action

In considering the things we can do to resolve issues earlier in the customer experience, it becomes apparent these things are all knowledge-enabled. Knowledge plays a critical role in our ability to minimize value erosion.

Upside and value-add opportunities are the second part of the realized-value model. Can we develop ways to exceed customer expectations with respect to their capability and/or reduce the effort it takes to get things done? Or, put another way, can we do things that would improve the customer’s productivity and success?

Assume, for example, that I’m a vendor that provides accounting software. I know the optimal steps and functions to use when processing an invoice in our system; my customer, an accounts payable manager, uses our software to process invoices, but he’s not following those steps or using those functions. How can I share my knowledge with him when he doesn’t know to ask or look for it?

In exploring this opportunity, two key dependencies emerge. First is knowledge in the context of use. In the example above, this is knowledge of accounting and processing invoices. Second, relevant knowledge is about the user, their role, and their goals or intent. We refer to this second dependency as the “know-me factor.” To better serve our customers, we have to know some things about them. Typically, our knowledge content is about how the product works—features, functionalities, etc.—and how the product breaks. Knowledge about the context of use is less common, but it’s gaining traction.

For years, Intuit has staffed its support centers with people who understand accounting first and are then trained on Intuit products. For Intuit, hiring for an understanding of the context of use is more important than hiring for product knowledge. Many organizations today work to balance context of use with product knowledge.

The requirements of the “know-me factor” introduce a new knowledge asset: people profiles. In addition to knowledge articles about the features, functionality, and context of use, we need to have a knowledge object that contains a rich collection of information about people. You’ll need to develop these people profiles for your customers, partners, and support analysts.

Value erosion, while a different way to think about support, is familiar terrain for support organizations; value-add opportunities are a new frontier.

Self-Service and Intelligent Swarming

As support organizations get better at capturing and delivering knowledge about known issues through self-service mechanisms and online communities, the nature of the work coming into the support center will change.

Historically, most support organizations handled known issues, or issues and questions that had captured and findable resolutions. Before the emergence of self-service mechanisms, the typical ratio of known to new incidents was 70/30. However, as organizations began to implement self-service mechanisms, knowledge capture rates increased and customer success with self-service mechanisms improved. The known-to-new ratio slowly shifted to more new issues than known, a powerful indicator of a successful self-service model.

As more and more known issues are handled through self-service, the total incident volume coming into the support center drops (normalized to install base activity) and the percentage of new issues increases. When a higher percentage of incoming incidents are new, escalation-based models become less effective.

Tiered models are very effective at resolving known issues at the lowest cost, but they are a very ineffective way to solve new issues. Instead, the most effective way to solve new issues is through collaboration. One of the first things support analysts do when they get an issue they aren’t familiar with is ask their peers. They collaborate. The traditional tiered support model does not facilitate collaboration; in fact, it inhibits it.

Intelligent swarming entails restructuring the support organization by doing away with support tiers and replacing escalations and inefficient hand-offs with collaboration. The goal is to get the person who’s most likely to be able to solve an issue working on it at the first touch, whether that person’s a specialist or a generalist. A generalist may even collaborate with a specialist to resolve an issue.

Early adopters of the intelligent swarming model have seen dramatic improvements in skills development, employee morale, and operational efficiency. Most importantly, their customers love it! These organizations have also found that not all incidents require collaboration between multiple support professionals; only 20–35 percent of the incidents closed in these environments require collaboration.

The intelligent part of swarming is enabled by the “know-me factor.” Here again we see the need for a new knowledge asset in the form of people profiles for both support analysts and customers. These profiles need to reflect each individual’s identity, reputation, skills, interests, and preferences.

With very few exceptions, self-service is an opportunity to leverage knowledge for all support organizations. If done properly, it’s a more efficient way to handle known issues for both the customer and the support organization. If customers can find resolutions to their issues and questions faster and with less effort than it takes to open an incident, they’ll use self-service. And they’ll use it to resolve a lot more issues than they would ever have reported as incidents.

Swarming, however, is not for everyone. Every organization is different, and before you decide to implement swarming, you should consider the complexity of the issues your organization handles, the ratio between new and known issues, and the availability of a knowledge base.

Global, Mobile, and Social

The trend toward global, mobile, and social has been well documented, and it has numerous implications with respect to knowledge management.


For many companies, their growth markets are in other countries. The fact that customers and employees, and potential customers and potential employees, are spread around the world is driving businesses to consider localization and translation strategies for their content. This is also driving the move to multimedia. Pictures, graphics, and video, especially those without text or audio, can be a way to communicate information to global users without having to invest in translation. Philips, HP, and Dell all use pictures (without text) to describe how to set up and use their respective products.


The generation that has entered the workforce over the past three to five years is the first generation where their personal technology is better—more sophisticated and more capable—than the technology they use in their jobs. These new employees are not willing to check their devices at the door. This phenomenon—BYOD—makes the environments we support less predictable and raises interesting challenges for support organizations. This includes the idea that knowledge should be able to be created, improved, and accessed anywhere, anytime, and the presentation of that knowledge has to align with the size and capability of mobile devices.


Texting, Twitter, LinkedIn, Facebook, communities, wikis, and blogs—mobile devices facilitate and inspire transparency and participation, which has led to explosive growth in the creation of content. Everyone has an opinion and wants to share it. Enlightened support organizations are developing strategies to leverage the many channels of social media, which provide new opportunities for creating, validating, and delivering knowledge. Social media is not without its challenges, however; the noise level and credibility of people and content in the social channels must be carefully managed in order to maximize the benefits.

Global, mobile, and social phenomena are having a significant impact on how we think about and manage knowledge. We’re seeing interest in the convergence of “our knowledge” and “their knowledge.” Imagine a universal knowledge process that integrates support knowledge, professional services, and customer- and partner-created knowledge. It’s time to start considering integrating vendor-sourced knowledge, across all business disciplines, with crowd-sourced knowledge.

Increasing Value

Knowledge will play an ever-increasing role as an asset in value creation and business success. The three drivers of change we’ve explored in this article all point to the fact that knowledge management in the future will have the following attributes:

  • Multimedia: Knowledge bases are moving from the current form of mostly text to a blend of text, graphics, audio, and video. 
  • Multichannel: The rapid emergence of online communities and social media is expanding our scope of interest well beyond the boundaries of the traditional support organization. We’re moving from a one-to-many model, where a few people create knowledge for everyone else to use, to a many-to-many model where everyone can contribute and everyone can use. 
  • Multilingual: With customers and employees around the world, localization and translation of knowledge is becoming a critical competency.

The support organization of the future will look more like a network than a hierarchy. That network will have much greater reach in that it will include employees, partners, and customers. The network will be knowledge-enabled, and it will seek to connect people to knowledge for known issues and people to people for new issues. Every interaction will be an opportunity to improve the relevance of the next interaction, so long as we capture what we learn from those interactions.


Greg Oxton is the executive director of the Consortium for Service Innovation, a nonprofit alliance of customer support organizations. The goal of the Consortium is to develop innovative ways to address the challenges of customer service and support, as evidenced by its continued investment in the development and evolution of Knowledge-Centered Support (KCS) and its practices.

Tag(s): future of support, knowledge management, KM, value-add


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