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Consortium for Service Innovation

The Four Phases

In the KCS v6 Adoption Guide, we identify four phases that support the successful management of a KCS adoption program. For each phase, we describe the relevant benefits and measures and how our measures must change as we evolve. We specifically note the exit criteria for each phase, which helps leaders know when they are ready to enter the next phase and make the appropriate and necessary changes in the measurement model.

Understanding of the phases is critical because the benefits and corresponding measures evolve through the phases. Sensitivity to these phases optimizes and sustains the benefits of KCS, appropriately expanding the scope of our measures at each phase.

A challenge for KCS leaders is managing expectations of the organization's executives with respect to the KCS benefits. The near term benefit seen at the end of Phase 2 (increase in capacity or productivity) is usually more than enough to justify the adoption program cost. The longer-term benefits realized in Phases 3 and 4 (self-service success, business improvements, and automation opportunities) create huge value for both the customer and the organization. However, these long-term benefits take time, and are realized as a result of the KCS practices becoming part of the organization's DNA. Ironically, a rushed adoption will actually take longer to realize the benefits!

To lay the groundwork for these dynamics, Phase 1 - Planning and Design describes baseline measurements against which we can assess early progress. Phase 2 - Adopting is about the knowledge workers learning the KCS Practices and techniques and maturing the knowledge base. The Phase 2 measures are familiar. Phase 3 - Leveraging expands the use of the knowledge base to other audiences, including customers. Phase 3 requires some new, value-based measures which are much broader and are more complicated than the traditional transaction-based measures.

Using a phase-based framework for the focus, measures, and benefits allow KCS leaders to describe the evolving competencies, efficiencies, and contributions in a way that is relevant to the organization. And, most importantly, it describes the dynamics and additional measures that are necessary to assess the health and value of a knowledge-centered organization.

A note on our approach: We occasionally offer specific numbers for the key measures. These are meant to be examples, not goals or industry best practice. This precision provokes discussion and helps make the dynamics at play more obvious. Please recognize that the results will vary based on the nature of the knowledge work involved and the nature of the customers being supported.

We describe KCS adoption as a journey, and a key part of that journey is a continuous process of learning and improvement. As KCS is adopted, an organization will realize an evolution of its people and their skills, its processes and the supporting technology, as well as its relationship with its customers and other internal organizations. The maturing knowledge base enables improvements in self-service success, the identification of a broad range of organization improvements, and is the foundation to leverage emerging automation and predictive capabilities (text analytics, cognitive computing, machine learning, bots and artificial intelligence).

Four distinct phases mark progress and must be measured with metrics relevant to the phase:



Sample Organizational Measurements

1: Planning and Design

  • Executive understanding of the benefits and the journey
  • Gather baseline measurements (both existing, and new, to the extent possible)
  • Set realistic internal and external expectations
  • Definition of the foundation elements that are good enough to start wave I 
  • Executive sponsor buy-in
  • First draft of adoption program deliverables and milestones (for details see the KCS v6 Adoption Guide)

2: Adopting

  • Learn KCS behaviors
  • Create articles in the knowledge base
  • Create internal understanding and excitement through realization of initial benefits
  • Establish internal referenceability
  • Ratio of known to new incidents
  • Process Adherence Review (PAR)
  • Content Standard Checklist
  • Knowledge worker competency profile (licensing model)
  • Improvement in cost per incident, capacity, and first contact resolution
  • Improved time to proficiency for new employees and new products/services 

3: Leveraging

  • Mature the knowledge base
  • Increase process efficiency
  • Promote self-service
  • Conduct Knowledge Domain Analysis
  • Improve collaboration and knowledge worker satisfaction


  • Time to publish
  • % of articles in a visibility state of "external" (available through self-service mechanisms)
  • Self-service use and success (cost savings: issues resolved without an incident logged)

4: Maximizing

  • Optimize the support network
  • Increase customer success and productivity
  • Improve employee job satisfaction
  • Implement organizational improvements: products, services, processes, and policies
  • Ratio of support cost to revenue
  • Customer effort
  • Customer loyalty (renewal rate, new product/upgrade adoption rate)
  • Customer satisfaction (speed to resolution, first contact resolution)
  • Employee effort
  • Employee loyalty 
  • Employee turnover rate
  • Ratio of known to new incidents being handled by the support organization
  • Organizational improvements: policy, process, feature, functionality (number of Requests for Enhancements (RFEs) accepted by organization owners)
  • Cultural health: trust and willingness to collaborate, share, and improve


Adoption Timeline.png

Measurements Matter

We use phase-appropriate measurements to assess when we are ready to move to the next phase. The right measurements for each phase will provide honest feedback and promote the correct behaviors. Getting measurements wrong could mean a premature advance to the next phase, the result of which will compromise the benefits or even mean failure for the KCS adoption. Another cause of failure we have seen all too often is when organizations use time-based goals for moving from one phase to the next instead of measurement-based criteria.

Having the right criteria to move from Phase 2 to Phase 3 is particularly important. While KCS techniques improve the efficiency and quality of assisted support, enabling a shift from the assisted model to a self-service model has even bigger benefits. By capturing knowledge and making it available to all the responders, KCS helps responders shorten resolution times and improve capacity in Phase 2. As we mentioned, the measures in Phase 2 are familiar: average work time to resolve, cost per incident, and productivity (the number of incidents handled per knowledge worker per month). Positive trends in these measures accurately reflect improvement. The picture changes dramatically as we move to Phase 3. As customers use self-service, they have access to information earlier in their resolution process. Self-service enables customers to get answers to their issues quickly, with less effort, on-demand, without support center assistance. And, when customers can find resolutions to their issues faster than opening an incident, they will use it a lot!

Before we enter Phase 3 and start promoting self-service, we have to be sure the knowledge base has critical mass. This ensures the requestors will have a good probability of finding resolutions to known issues and create a positive experience for them. If we move to Phase 3 before the knowledge base has critical mass, the customer experience is compromised and that will inhibit their use of self-service in the future.

When assisted support is necessary, ideally, it is because the issue is not known or the requestor does not have the authority (rights and privileges) to implement the resolution. The resolution of these new and complex issues are often the ones that require significant time and multiple resources to resolve. A successful self-service model changes the nature of the work in the assisted model:

  • The easy and known issues are now being resolved through self-service.
  • The new and complex issues are the ones entering the assisted support process.

As we progress through Phase 3 on the KCS journey, the transaction-based metrics (average work time to resolve, cost per incident, and productivity) start to look like they are moving in the wrong direction. What has gone wrong? ...........Nothing!

The customer experience is vastly improved, incident volumes (when normalized to the install base or number of customers being supported) decline, and total support costs as a percent of revenues decline. In Phase 3 we need new measures that reflect the value of the knowledge base: self-service success, organizational improvements based on the patterns of reuse of knowledge articles, and the impact on customer and employee loyalty. This expansion of the measurement model is key to a successful implementation of KCS.

Positive Trends, Not Absolutes

The KCS phases follow the same sequence for each adoption, but each group in the organization might have a different experience. The length of each phase depends on the culture of the group, the enabling technology, and the complexity and nature of the issues being resolved.

At any single point in time, different groups within an organization may be at different phases. This variation is normal, but challenging for leaders who need to capture and communicate each group’s progress and contribution. Meaningful, phase-specific measures support an informed assessment and provide a way to communicate progress and value.

As we look at using measures, we must keep in mind that absolute numbers are not critical: positive changes in the trends are. As with the timeline for each phase, the actual results and benchmarks vary by industry and the complexity of the issues being raised. We must establish measurements relevant to each organization and then use them to confirm that trends are moving in the right direction. Depending on the organization, even a modest change in a particular measurement can represent significant progress.

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