NETTING IT OUT

In May 2007, we had the opportunity to join a meeting of nine empolis GmbH customers discussing their progress in automating the creation and use of knowledge assets. The participants were project managers currently involved in customer support knowledge projects at Fujitsu Siemens, Moeller Group, Nokia Siemens Networks, Siemens A&D, Siemens SIS, O2, and Versatel.

Each of the teams at the meeting described their projects, issues, and results, which we recap in this report. We also observed a developmental model, comprised of these steps:

• Establish Proof, Get Breathing Room
• Secure Organizational Commitment
• Make Development Predictable
• Measure Progress and Effectiveness
• Align Skills and Rewards
• Professionalize Knowledge Work
• Optimize Knowledge Systems

This report also recounts two cases in more detail: Moeller Group's knowledge project uses dialogs to lead customers to the solutions they need. A team of five people manage 45 trees and 350-400 solutions in both German and English. Each successful self-service query saves one half hour of call center agent time. In January through March of 2007, there were 3,045 online diagnoses. 

Siemens IT Solutions and Services, which provides call centers for its clients, has made the longest strides in professionalizing knowledge work. The knowledge team has established the roles and responsibilities involved in knowledge encoding, knowledge publishing, knowledge asset maintenance, and skills development. The system, called Knox, is in production in four countries, and in test mode in two more. Knox has common workflows, language concepts, repository, processes, and roles across the organizations involved. There are 2,000 agents using Knox, 50 experts creating knowledge assets, and 30 knowledge promoters to motivate and support the agents on site and to serve as broker between the operational lines and the headquarters.

The participants in this meeting have achieved indisputable success in automating customer service. This is a relatively young science, so there is much to be discovered about how to manage the people, processes, and technology that enable the growth of knowledge assets. We can hope that, at some point, the knowledge assets created by their exploration will be captured for the rest of us to use.

THE MEETING

Format

On May 21-22, nine customers of empolis GmbH from seven companies gathered inMunichfor a mutual exchange of current accomplishments and challenges in customer support knowledge and content management. All of the customers were players in the European telecommunications sector.

Each participating company had an hour to present an overview of the company, the customer support environment, and the knowledge development evolution to date. Each also provided a demonstration of the current knowledge-enabled support capabilities. Finally, each wrapped up with a discussion of plans and challenges.

Participants

The customers participating in the meeting were customer service executives and project managers currently involved in customer support knowledge projects at, Fujitsu Siemens, Moeller Group, Nokia Siemens Networks, Siemens A&D, Siemens SIS, O2, and Versatel.

Meeting Host

The meeting was organized by empolis GmbH of Germany. Empolis provides search, content, and knowledge management solutions. It has 500 customers, mostly inEurope. It was founded in 2000 as a merger of five media service companies and software manufacturers for content and knowledge management solutions. Empolis customers include Airbus, Bosch, the European Patent Office, Wolters Kluwer, Siemens,Avon, and Schlumberger. Empolis is a subsidiary of arvato AG, the international media and communications service supplier within the Bertelsmann group.

THE COMMON THEMES FROM PARTICIPANTS

Goals

All participants were engaged with empolis's knowledge management, search, and content management technology to transform support activity from an artistic endeavor to a scientific, predictable, repeatable, and scalable process by automating the capture and delivery of knowledge. In business terms, this translates to delivering answers of higher quality, more quickly and more consistently; being able to deliver answers directly to end customers via self-service search or dialogs; shorter call times; fewer escalations; shorter training periods for call agents; higher customer satisfaction; and shorter duration of faults (problems don't last as long). Because answers and resolutions can be delivered by search and by dialogs, the knowledge encoding projects support scalability in two key ways. First, customers can resolve their own problems. Second, new call center agents can be effective more quickly, guided by the encoded answers and dialogs.

Accomplishments

Each of the customers had encoded a significant set of knowledge within 6-8 weeks. Most had knowledge development processes defined, and half had feedback mechanisms in place for improving the knowledge assets. Half tracked statistics that provided some measure of the business value of the system.

Remaining Challenges

The models for knowledge asset development and management aren't mature, ingrained, or disseminated. There are a number of areas that the group needs to explore and experiment with. Most continue to seek better models for governance of their assets--in particular, more effective ways of ...