In the age of data science, we can measure the world in ways we never could before.
Customer Lifetime Value.
Causal Factor Mining.
Who are the key resources likely to leave the organization? And When?
What are the greatest staffing needs today? In three years?
What is the correlation between performance and pay?
What is the relationship between the interview test score and performance?
Are we targeting and acquiring the right customer?
Are we identifying and ensuring retention of profitable customers?
Do we have a strategy to switch customers from our competitors?
Are we resolving inconsistent agent performance and churn?
Are we doing marketing optimally to gain the maximum return on investment?
How well do we detect fraudulent transactions?
Is our pricing aligned to historical data?
Do we forecast call/ transaction volumes and identify the capacity requirement for optimal utilization?
Do we differentiate between a genuine customer vs a nongenuine one(one who is only a deal seeker)?
Do we know in real time if any of our sellers are being targeted by fraudsters?
Do we need a virtual assistant place to drive business?
Do we have a cockpit view of lead indicators?
How do we reduce the high operations’ cost?
Is customer satisfaction related to business growth?
Do we struggle with siloed information?
Most customers decide based on price. Are we pricing correctly?