Lean and Mean: Using Lean Six Sigma to Improve Your Analytic Processes - Paper 193-2012

Sep 12, 2026

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Many businesses have increased their analytic sophistication, yet analytic maturity has outpaced the investments needed to manage analytic processes with strong quality and efficiency. Analytic teams often spend time operating production processes and lack a framework to prevent errors and reduce cycle time. A lean Six Sigma approach helps teams govern these processes, applying the DMAIC lifecycle to improve overall performance, while Transamerica’s Life & Protection division uses the framework to advance marketing campaign optimization.

LanguageEnglish

CategoryPresentations

FormatPDF

Pages8

Reading Time3 min

AccessFree to download

ABSTRACT

THE NEED FOR IMPROVEMENT

INTRO TO LEAN SIX SIGMA

DMAIC and Voice of the Customer (VOC)

THE LEAN SIX SIGMA TOOLKIT FOR ANALYTICS

DEFINE

SAS Global Forum 2012 Planning and Support Paper 193-2012 Lean and Mean: Using Lean Six Sigma to Improve Your Analytic Processes Robbie Reynolds, Life & Protection a division of Transamerica Rachel Alt-Simmons, SAS ABSTRACT Many businesses have increased their analytic sophistication, with analytics becoming more pervasive in business processes. With the increase of analytic maturity, investments in the people, methodologies, and technologies needed to effectively manage those processes have lagged. Many analytic teams are tied up in managing production analytic processes, and often lack a framework for ensuring process quality and efficiency. In this session, we help analytic teams better manage these processes, as well as reduce errors and cycle time through a lean Six Sigma framework. The Life & Protection division of Transamerica puts the framework to work in making significant improvements across its marketing campaign optimization process. THE NEED FOR IMPROVEMENT As competitive pressures increase the need for organizations to master analytics , internal analytic teams have increased their statistical sophistication, but are struggling to productionalize their insight. Many analytic groups find themselves managing operational processes with little help from their technology partners, while the demand for analytics, as well as the data volume and need for speed-to-insight, grows within the organization. Over time, the processes can grow so complex that it becomes difficult to identify the root causes when the process breaks down; and a breakdown in the process can set the team back days if not weeks as resources scurry to find and fix the problem. How do we find and identify problems from the start? How do we free up critical analytic capacity? Lean Six Sigma. INTRO TO LEAN SIX SIGMA Lean Six Sigma (LSS) is the marriage of two improvement methodologies: While the roots of statistical quality control have been around for decades, the current methodology is credited as being “invented” by Motorola and popularlized by its widespread implementation at General Electric. Six Sigma is a quality improvement methodology traditionally used in manufacturing organizations, with a goal of reducing the number of defects in a process to a six sigma level (99 .99966% defect free) . The methodology follows the “DMAIC”methodology to define, measure, analyze, improve and control to identify defects and improve processes. Another key tenet of Six Sigma is “voice of the customer”(VOC) . Customer needs and requirements are the primary driver for process improvement. While many organizations across many industries have had success for Six Sigma, companies have struggled to identify how the methodology can be applied to transactional processes. Enter Lean. While Six Sigma’s goal is to reduce defects, Lean’s goal is to eliminate waste and improve efficiency. As defined by Taiichi Ohno, “father” of the Toyota Production System, waste is made up of eight components: waiting, overproduction, rework, motion, transportation, processing, inventory and intellect. When the two methodologies are married up, you have a framework for improving quality and reducing process lead time. The LSS methodology provides a toolkit for improving analytic lifecycle management – effectively and efficiently managing the elements (people, processes, data and technology) necessary for operationalizing predictive models from conception to deployment. Why haven’t more organizations used LSS in the past? With any process improvement initiative, there are always going to be cultural and organizational challenges. The biggest barrier to effective process flow is the organization itself. Most organizations operate in a matrix structure. Each functional area may have its own set of performance goals and incentives; cross-organizational workstreams have been divided into narrowly defined roles and responsibilities embedded across these functional areas. You c

FAQs

What problem does the document address regarding analytics teams?

Analytics teams struggle to operationalize insights and often lack a framework for process quality and efficiency, leading to errors and longer cycle times.

How does Lean Six Sigma support analytic process management?

It applies a lean Six Sigma framework to reduce errors and process lead time, using DMAIC and customer-driven requirements to guide improvements.

How does Transamerica’s Life & Protection division apply the framework?

It uses the lean Six Sigma framework to make significant improvements across its marketing campaign optimization process.

Sep 12, 2026

Upload by Hazel