For decades the company was an “information provider” serving the pharmaceuticals industry. It rebranded as a “big data” company. The stock rose threefold. But despite numerous technology advances, its operations required manual data wrangling activities. These eroded operational efficiency, impeded process improvement and degraded the customer experience.
Under pressure from activist investors, the COO launched a core transformation that promised cost cutting, productivity improvement and continuous improvement in customer service. While visiting frontline employees, he marveled at the rework required to complete research and the redundant processes hampering the company’s knowledge worker productivity. These produced the 7 wastes targeted by lean process improvement: waiting, defects, inappropriate processing, excess motion and more.
Non-technology, self-funding operational
– No new technology
– Enterprise-wide improvement
– 6-month implementation
The Lab began with documentation previously developed by the internal lean consulting team and quickly identified hundreds of ways to improve productivity. A lean kaizen blitz identified process standardization improvements for raw data collection that cut intake errors in half. Quickly implementing lean standard work methods eliminated 40 percent of one-off data cleansing tasks. Within months, the COO’s core transformation delivered a knowledge work factory using lean production methods to achieve a 30 percent cost reduction and a 50 percent increase in customer satisfaction.
A Top 5 global provider of financial market information, the company employs 45,000 people. This initiative focused first on operations in the Americas division.
The initiative began with a 6-week Phase I analysis and process review. This launched a 6-month, guaranteed, self-funding, lean, non-technology improvement implementation.
– Cost cutting
– Increased productivity
– Customer experience improvement
– Data procurement
– Data enrichment & integration
– Analytical & reporting services
– Product sales & delivery
– Post-delivery product support
The Lab implemented more than 250 non-technology process improvements and best practices. Examples:
Pre-empted “Non-Standard” Inquiries — The Lab traced thousands of seemingly unique, customer inquiries to a dozen root causes in the order fulfillment process. To preempt these inquiries, confusing instruction forms and orientation scripts were fine-tuned with the field sales teams. These inquiries fell by 70 percent, reducing the order-to-cash cycle.
Upgraded Lean Data Inventory Management — Market information was inventoried in three databases. However, identifiers for the same company could differ by database, causing manual reconciliation. The Lab centralized accountability for data inventory quality. Process reengineering and lean management metrics for data inventory management eliminated half of these reconciliations.
Capacity Model & Productivity Metrics — Although information products and work activities were similar and repetitive, no capacity planning model or productivity metrics were implemented. Overstaffing averaged 30 percent. The Lab’s activity cube delivered capacity planning based on lean standard work units. Within 8 weeks overstaffing was reduced by half.