Telecommunications Industry – Predictive Analytic and Team Scaffolding

Designed and conducted four Learning & Development impact and optimization projects for a Fortune 20 telecommunications organization while scaffolding the team to conduct predictive analytics projects.

Capabilities Enabled:

• Enhanced capability to employ a scalable predictive analytics measurement framework to demonstrate program impact and optimize program outcomes.
• Credible, valid, quantitative insights into four strategic programs affording informed decision making.

Impact Created:

• Through program isolation analyses, the client realized:
  • A 138% ROI and a significant positive impact to customer cancel rates from a services training program and insights to program continuation/modification.
  • A statistically significant improvement in service delivery, outage resolution, and customer satisfaction due to a comprehensive change management program and insights to program continuation/modification.
  • A 24 minute time savings in service resolution from a services pilot program and insights to program continuation/modification.
  • An increase in funnel pipeline and monthly booking value from a sales pilot program and insights to program continuation/modification.
• Enhanced Learning & Development team capability to conduct predictive analytics measurement projects by providing processes, tools and templates.
• A common metric language across the organization.
• A model for embedding predictive analytics measurement into program design and instructional design activities.

Summary:

The client uses the survey-based Kirkpatrick Learning & Development measurement model and the Phillips ROI estimation approach to assess program effectiveness. There was a desire to enhance the current measurement model and enhance team capability with predictive analytics. Four programs were selected to be evaluated:

• An existing services program with 6,000 trained.
• An existing change management program with 1,400 trained.
• A pilot services program with 48 trained.
• A pilot sales program with 106 trained.

The internal teams shadowed SPP partners and were coached on better practices throughout the duration of the projects. For each of the four projects, multiple regression models were established and analyzed to assess the impact of training on targeted business metrics (e.g., customer satisfaction, funnel pipeline, margin to targets, first ticket resolution, and customer churn).  After the influence of training was isolated from business metrics (past insights), optimization analysis was conducted to identify where the greatest impact was realized (future predictions) yielding prescriptive recommendations. Based on the past insights and future predictions, the programs were modified accordingly to maximize the benefit to the learners and the organization.

About the Client :

The client is an American broadband and Telecommunications Company and the largest U.S. wireless communications service provider.

The Challenge:

The client wanted to transform the Learning & Development organization and measurement strategy from a primarily survey-based measurement approach to incorporating predictive analytics to better meet executive needs and for internal continuous improvement.

The Solution:

To design each of the four projects and to secure buy-in, cross-functional stakeholder meetings were conducted to build a measurement map that would serve as the strategy, analysis, and communication vehicle. Next, relevant demographic, training, and business outcome metric data were collected. Predictive multiple regression models were developed for each project and data were analyzed to isolate the effect of the program on key business outcomes and to identify where future outcomes could be maximized yielding prescriptive recommendations. Findings and recommendations were delivered to each project stakeholder group and program decisions were made to either continue as-is, modify, or eliminate.

The Outcome:

• Provided tools and templates to their Learning & Development team to conduct predictive analytic projects independently.
• The scalable predictive analytics framework was adopted by one Learning & Development division and is under consideration by another.
• The insights and recommendations from each of the four projects empowered the leadership team to make strategic programming/funding decisions.