Company: TELUS Communications Inc., Calgary, Alberta, Canada
Category: Workforce Management Solution - New Version
TELUS Inc (TSX: T, NYSE: TU) is Canada’s fastest-growing national telecommunications company, with $12.8 billion of annual revenue and 12.7 million subscriber connections, including 8.6 million wireless subscribers, 1.7 million high-speed Internet subscribers, 1.4 million residential network access lines and more than 1.0 million TELUS TV customers. TELUS provides a wide range of communications products and services, including wireless, data, Internet protocol (IP), voice, television, entertainment and video, and is Canada's largest healthcare IT provider.
To provide and maintain products and services for our residential customer base in Western Canada, a workforce of over 2300 technicians isrequired, with an annual operating cost of $350M.
Our challenge is to forecast where demand will materialize across 708 unique marketing locations by Product (TV, Internet), Technology (Fibre, Copper, Satellite), and Job-Type (Installation, Repair, Move or Change) and ensure the required technician skill-hours are available to meet the demand.
Through 2017 our challenge was compounded by a number of factors including the rapid expansion of the TELUS PureFibre network, which drove new product offerings and peak demand across many distinctive geographical pockets, and a workforce differentiation program which established an entry-level position with a unique cost-base and skill-set, and hiring requirements.
The ability to accurately project demand and make the right technician supply available, significantly improves labour utilization and responsiveness to customer requests while decreasing overall operating costs.
Our previous forecasting process centered around a Microsoft Excel Workbook which modeled a summary demand forecast for 70 marketing locations. The volume of data and calculations, spanning millions of data points, started to exceed the application’s limits, causing crashes and data loss.
It took 3 full-time resources 3 weeks each month to produce our forecast, leaving negligible time to analyze the information, formulate recommendations, and disseminate the package before the next forecast-cycle commenced.
This process was not sustainable due to technical limitations, but also the rapid pace of change which required the ability to provide more granular insights and integrate new streams of activity on the fly.
Oracle Hyperion Planning, an integrated planning, analysis and reporting platform, was selected to provide a scalable framework in which forecasting could be modeled, and tens of millions of data-points processed. The application has “what-if” and drill-down analysis capabilities, and provides users with the ability to run ad-hoc or canned reports.
We immediately realized a number of benefits since the beginning of 2017.
There has been a significant reduction in the effort required to produce the monthly forecast, with the net reduction being shifted to analytical and communicative activities, producing more salient recommendations while ensuring our stakeholder groups understand, and are aligned to, the information.
We have been able to align our data-sources and categorization of data with upstream and downstream business units and have established Service Level Agreements with those teams to meet key monthly deliverables on time.
A number of groups we collaborate with have used our forecast to drive improvements of their own. Finance has been able to generate a more accurate monthly budget triage outlook, while Marketing has been able to direct efforts to areas where we have excess labour.
We yielded savings of $2.4M in 2017, while implementing the change on time and under budget by $200K.
We now have a single source for our operating plan and forecasts with all processes, data, and business rules residing within Hyperion.
We have delivered standardization, reduced time to completion, and a level of governance not previously achievable.
We have transformed how business units collaborate and decisions are made with continuous improvements already being applied to the model with broader changes already anticipated in the future.
Enhanced insights, substantiated forecast predictability, and strong cross-organization alignment have driven increased confidence in our data and our recommendations.
Monthly forecast time to completion reduced by 85%, with net cycle-time being allocated to more analytical tasks.
Enhanced updateability of the application has facilitated integration of new streams of business and enactment of strategies and tactics to support those new streams.
Ability to meet lead-time requirements for hiring of 6 months, facilitating increased likelihood of hiring and classsize maximization, and critically providing the advance notice required to secure fleet, and technical tools and equipment.
Significant reduction in overtime, with increased labour utilization and customer service levels globally – driving both a significant reduction in cost and mitigating loss of revenue.
Initial projection of 181% ROI over 5 years on a budget of $950K, actually yielded savings of $2.4M in 2017, while the implementation occurred on time and under budget by $200K.