You are a key member of the Operations and Business Intelligence (OBI) team in Company ABC Customer Success (CS). This team provides the operational platform to enable and support a two sided marketplace for our customers to connect with product and domain experts.
The mission of the OBI team is to: envision and manage the Operations and Business Intelligence platforms, that make delivering delightful services at scale easy.
There are 4 pillars that form the OBI team:
The Group Manager, Operational Capacity Planning – Data and Analytics will play a critical leadership role to drive the charter of the Intelligent Planning pillar. The forecasting team part of this pillar is responsible for:
The volume forecasted and headcount required is fed into a workforce management solution (Aspect) where agent schedules are reviewed and the headcount is scheduled. Accounting for agent schedules ensures the appropriate staffing is available. Schedules are reviewed 2 weeks out, as well as a day prior (and course correction made where needed).
Messaging was launched six months ago and there is a gradual shift in volume to messaging from Phone. The collaborative process with Product owners is not defined, inconsistent across product lines, and adhoc.
Key stakeholders do not have visibility and cannot influence the forecasting process. As a result the team has deployed a planning tool, Anaplan, where all forecasting related input data is loaded, forecasted volume is calculated, adjustments are made and volume is sent to partners who then figure out how to staff the volume based on various assumptions. Anaplan replaces Excel spreadsheets so all data that is an input to the forecasting process is stored in one central repository. This tool can be customized to get input from internal staff as well as external staff (BPO partners)
Q1. The current forecasting process is broken and needs to be changed.
Q2. What important analytical methods/ data science would you layer in at different points of the process to improve forecast accuracy?
Q3. What would be the forecast accuracy metric (or set of metrics) you would use? How would you define the metric(s) and confirm that it is indeed the right metric?
Q4. The forecast for Product A and Product B customers was 3x the original expectations of the team. How would you go about doing the diagnosis on what was the root cause for why this happened?
In January 2020, the California Consumer Protection Act (CCPA) will allow customers to download, delete, and access their data. The Chief Customer Officer has asked you give him an update on what impact this will have on the forecast.
Q5. How would you adjust your contact volume and Average Handle Times (AHT) in your forecast to account for this?
Q6. How would you plan for contingencies in case the contacts are >5x your forecast?
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