Mohan Giridharadas, Founder and CEOLeanTaaS was formed in 2010 based on a simple premise— to embed lean principles with predictive analytics and optimization algorithms into a software-as-a-service suite of products. The company would deliver “Lean Transformation as a Service” (hence, the name LeanTaaS) to customers across several industry verticals.
Prior to starting LeanTaaS, Mohan Giridharadas was a senior partner at McKinsey & Company and led the lean manufacturing and lean service operations practices both in North America as well as the Asia-Pacific region. He had worked with clients in airlines, banking, manufacturing, retail and healthcare and fundamentally believed that the lean process improvement methodologies could be significantly enhanced through predictive analytics and a new delivery model. He envisioned a delivery model that relied on software products with real-time data feeds and scalable algorithms instead of depending on people “walking the halls” and solving operational problems based on historical snapshots of data contained in spreadsheets.
After several years of building out the core analytics platform and the delivery model by deploying custom apps across a variety of industries, LeanTaaS pivoted toward healthcare in 2015. The need for unlocking the capacity of scarce assets through operational excellence had never been higher in healthcare. An aging population combined with an ever-increasing incidence of chronic illnesses meant that millions of new patient visits needed to be accommodated within the existing asset base of health systems. At the same time, lower reimbursements levels were forcing all healthcare providers to “do more with less.”
LeanTaaS adapted some of its core optimization algorithms to match the demand signal for infusion treatments with the available supply of chairs and staff at Stanford Health Care. The approach worked—within a few months, the results were clear: a 31 percent decrease in wait times, 17 percent reduction in total cost per unit of service, and 25 percent increase in nurse satisfaction. The iQueue product suite was born. Today, iQueue for Infusion Centers manages over 3,000 infusion chairs across 126 infusion centers belonging to 54 leading cancer centers in the U.S. Six of the top 10 and 21 of the top 40 cancer hospitals in the country (as ranked by U.S. News and World Report) rely on iQueue to deliver a superior experience to their infusion patients.
LeanTaaS uses lean methodologies with advanced data science and optimization algorithms to radically improve the operational performance of healthcare providers
The very next year, in partnership with UCHealth in Colorado, LeanTaaS developed iQueue for Operating Rooms, a cutting-edge product that improves the allocation and utilization of operating rooms—the financial backbone of most health systems. The product analyzes the patterns of usage of the operating rooms by surgeons and service lines and utilizes proprietary, machine learning algorithms to facilitate an internal “marketplace” for OR time. It also identifies opportunities to repurpose blocks of OR time that are not being used effectively. The product has been (or is being) deployed for 450 operating rooms across 14 leading health systems across the country and delivers a significant return on investment.
There are several expansions of the iQueue suite being developed with active customer involvement. These include ambulatory clinics, diagnostic imaging, inpatient beds, radiation oncology, and emergency departments.
The company has an innovative approach to transforming core operational processes resulting in improved patient access, reduced wait times and higher staff satisfaction. “The quality of the trust-based relationships with our customers and the passion and dedication of our team is the driver behind the traction that the company is seeing in the market. We will transform the operational delivery of healthcare one asset at a time through sophisticated optimization algorithms combined with predictive analytics and a scalable, software-centric delivery model,” concludes Giridharadas.