The path to lean analytics


In my role at SAS I have the great fortune to meet with business intelligence and analytic (BI&A) teams all across the United States to share and discuss best practices and pain points, particularly around the ability to execute and operationalize insight internally and externally throughout the organization.

In these discussions, I have identified a key theme: As these BI&A teams grow in analytic maturity, they don’t often evolve the skillset of the team, or build the necessary relationships with their IT partners, to accommodate the increased need for discipline and repeatability in operational BI&A processes (which can cover a diverse range of processes from data management to report development and delivery to model development and model lifecycle management). As a result, many teams struggle to keep up with the ongoing “work at hand” while the demands for their analytic talent increase. These BI&A teams are often the victim of their own success.

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 fact, these types of conversations with BI&A teams became so pervasive, that I saw an opportunity to help organizations through leveraging process improvement techniques. Two primary improvement methodologies, Lean and Six Sigma, have been heavily used to improve quality and reduce cycle time in manufacturing, but have struggled to make their way into transactional environments, where the concept of “products” and “customers” may be less concrete.

Lean improvement methodologies can be used by BI&A teams to streamline their processes and free up capacity. The LSS methodology provides a toolkit for improving BI&A lifecycle management – effectively and efficiently managing the elements (people, processes, data and technology) necessary for operationalizing insight from conception to deployment. However, one of the biggest barriers in improving these processes is the organization itself. Most organizations operate in a vertical matrix structure (the infamous silo!). 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 can improve a tiny piece of a process in this structure, but because teams only know their piece, they can’t influence major improvements. The workflow is so granular and divided that handoffs, redundancies and errors are almost impossible to address.

As you can imagine, the first step down the path to lean is getting these cross-functional/organizational teams together and creating shared accountability. A critical success factor for lean is horizontal-process ownership, not vertical-functional ownership. The next step is to map out the current state of the process (also known as value stream mapping). Critical for consideration are the five principles of lean as defined by James Womack and Daniel Jones, in their 1996 classic book Lean Thinking.

  • Value: Value is always defined by the customer. By understanding the value to the customer, the team can more readily identify activities within the process that are required.
  • Value Stream: The value stream represents all activities, value-add and non-value add, that make up a process. The value stream map is used to visually represent the process flow. It is estimated that 85 percent of steps within a given process are non-value add, meaning that they don’t add value to the final product or service.
  • Flow: The goal of your process improvement initiative is to generate flow, where information moves across a series of process steps without stopping (okay, BI&A teams, how many times do you stop your process because of data quality issues, or you’re waiting for additional information or resources?).
  • Pull: Pull represents a “just in time” approach to information delivery that reduces process lead time. In short, this allows the upstream supplier to only take on work when the downstream customer indicates that they need information (sound familiar, BI teams?).
  • Strive for Perfection: Process improvement initiatives aren’t once and done. The team must continually strive to maintain and sustain improvements.

One BI&A team that I worked with last year began to use lean improvement techniques in an operational analytic process that gave them back five days per month. That’s five days that the team could use to focus on new and possibly game-changing initiatives for their organization. Are you thinking lean?


About Author

Rachel Alt-Simmons

Business Transformation Lead - Customer Intelligence Practice

Rachel Alt-Simmons is a business transformation practitioner whose expertise extends to operationalizing analytic capabilities vertically and horizontally through organizations. As the Business Transformation Lead for customer analytics at SAS Institute, she is responsible for redesign and optimization of operational analytic workflow, business process redesign, training/knowledge transfer, and change management strategies for customers. Prior to SAS, Rachel served as Assistant Vice President, Center of Excellence, Enterprise Business Intelligence & Analytics at Travelers, and as Director, BI & Analytics, Global Wealth Management at The Hartford. Rachel Alt-Simmons is a certified Project Management Professional, certified Agile Practitioner, Six Sigma Black Belt, certified Lean Master, and holds a post as adjunct professor of computer science at Boston University’s Metropolitan College. She received her master’s degree in Computer Information Systems from Boston University.

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