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 in Munich for 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 in Europe. 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 managing knowledge processes; measuring effectiveness, value, and progress; gaining commitment across organization; acquiring skills; motivating staff to capture and enhance knowledge assets; and managing distributed development of knowledge models and solution trees, the forms in which knowledge is encoded for use by customer service applications.

DEVELOPMENTAL MODEL EMERGES

As we listened to each team present its projects, demonstrations, goals, and challenges, patterns emerged that resolve into a developmental model.

People and companies accumulated experiences, skills, tools, and corporate attitudes in their journey to success. These four elements are intertwined, and all four elements are necessary. The accumulation can be sped by wise acquisitions, but the fourth element, corporate attitude, can’t be purchased. And, as the state of the knowledge science stands today, you can’t purchase the knowledge processes and policies the way you can purchase mature systems such as Production Planning or Inventory Management. So a journey of discovery is unavoidable. Fortunately, there are plenty of pioneers to help each other on the way.

Each of the teams at the meeting described similar steps on their journeys. The steps we saw people taking were these:

• 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

The participants all had the same, successful first step: encoding a significant body of knowledge and using it effectively. Their paths through the next several steps varied, for entirely pragmatic reasons; their next step was chosen based on the obstacles and opportunities in front of them. If the organizational culture was supportive, then resources of all types could be enlisted across the company and larger and longer term projects engaged. If the organizational culture was not supportive, the team had to focus on small victories, careful justification of every investment, and projects that did not require contributions beyond the core team. If, for example, the team lacked sufficient skills or resources, it must outsource development and quickly find ways to manage distributed development of knowledge models and solution trees.

Although the sequence of the steps varied among the companies, it was clear that each of these stages must be entered to create the knowledge assets that support the participants’goal of reliable, scalable, and predictable customer support delivery.

Establish Proof, Get Breathing Room

Getting the initial project up and running is step one for everyone. Each of the companies established a significant knowledge asset quite quickly. This accomplishes some invaluable effects:

• Begins to pay back the investment by allowing users to get their own answers, or by making agents much more productive
• By reducing calls, frees people’s time to extend the benefits to additional areas
• Proves that the system works, which gives the organization confidence
• Provides some insight into the impact on call volumes and call times: what is the potential payback?

Most of the companies tracked some measure of system impact. Common metrics for participants include call time, number of searches, number of troubleshooting dialogs, first call fix rate, time to clear faults, customer satisfaction, and number (or percentage) of escalations. Tracking the changes in these statistics provides insight into the value the system is delivering.

Secure Organizational Commitment

Knowledge management is not a short project. It is, at least, a long-term project, and, more accurately, it is a program. To endure, it requires the commitment of the company. One never hears the argument that “we just don’t need accounting and all that expensive accounting software.” But one certainly hears knowledge investments brought into question. They aren’t understood; they aren’t taken for granted; they are somewhat new and, perhaps, vulnerable to attack. Without the company’s commitment, knowledge teams will have trouble recruiting and retaining talent, attaining stable funding for long-term projects and plans, developing strategies, and gaining acceptance of knowledge goals and key performance indicators (KPI). 

This report continues...