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Ten Best Practices for Succeeding with Speech Analytics

Ten Best Practices for Succeeding with Speech Analytics 11/26/2013
By Donna Fluss


Speech analytics continues to be an exciting application because it does something that has never been done before in contact centers or enterprises – it uncovers insights by analyzing large numbers of conversations and converts the findings into files of metadata for analysis.

Doing this right is complicated. Speech analytics is a highly sophisticated task that requires the right technology, resources, expertise, experience, and time to analyze the data and obtain the required results. And that’s the easy part. It also requires senior executive sponsorship and the ongoing support and cooperation of all customer-facing departments in an enterprise.

Using Speech Analytics as a Change Agent

Speech analytics findings and trends need to serve as a catalyst for change. For this to happen, there must be a process in place for applying the findings in the contact center, to departments across the enterprise, and sometimes with business partners. This means that the organization needs a structured approach to share both positive and negative findings so that identified issues can be corrected.

Here are best practices to position your company to use speech analytics to drive positive change.

  1. Find a senior sponsor for the speech analytics initiative – ideally, choose an influential leader who does not work in the contact center.
  2. Emphasize the enterprise-wide benefits of speech analytics, and put together a cross-functional team of influencers to participate in a speech analytics steering committee. (This may require significant up-front “politicking” to convince non-contact-center leaders to participate.)
  3. Communicate the uses of speech analytics to all internal departments that can benefit from its findings, to get their buy-in and support for the new solution.
  4. Assemble a dedicated team that is not part of the contact center to manage the speech analytics process. (This will help to make it an enterprise application.)
  5. Staff the speech analytics team with resources who understand the business, not just quality assurance people or contact center supervisors.
  6. Set up a formal speech analytics reporting process and organization that enables findings to be shared with senior management and other departments throughout the enterprise on a timely basis.
  7. Determine the key performance indicators (KPIs) to be measured and included in the speech analytics reporting package.
  8. Create a mechanism for tracking and reporting the progress of each issue, KPI and department on a monthly basis. (The reporting should be set up so that it is shared with all relevant departments and senior managers.)
  9. Empower the speech analytics team to hold department managers responsible for justifying or addressing the issues identified by the speech analytics application; department managers must be required to communicate how and when they are going to fix each of the highlighted issues.
  10. Create a closed-loop process that measures improvements on an ongoing basis; managers should be recognized and rewarded for tackling and correcting the issues identified by speech analytics.

These ten best practices, combined with a bit of political savvy and support from senior management, will help to drive the success of a speech analytics implementation, as will having a technology partner who can provide guidance and support throughout the process.