WHAT IS LEAN SIX SIGMA?

Six Sigma focuses on reducing process variation and enhancing process control, whereas lean drives out waste (non-value added processes and procedures) and promotes work standardization and flow. The distinction between Six Sigma and lean has blurred, with the term "lean Six Sigma" being used more and more often because process improvement requires aspects of both approaches to attain positive results.

Lean Six Sigma is a fact-based, data-driven philosophy of improvement that values defect prevention over defect detection. It drives customer satisfaction and bottom-line results by reducing variation, waste, and cycle time, while promoting the use of work standardization and flow, thereby creating a competitive advantage. It applies anywhere variation and waste exist, and every employee should be involved.

Implementing Lean Six Sigma:

For any organization, the first step in a Lean Six Sigma deployment is deciding to use the methodology. Once the leadership of an organization believes they can benefit from using Lean Six Sigma, they can follow eight steps – from creating a burning platform for adopting the approach to recognizing team member contributions – to complete the rollout.

What is robotic process automation?

RPA is an application of technology, governed by business logic and structured inputs, aimed at automating business processes. Using RPA tools, a company can configure software, or a “robot,” to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. RPA scenarios range from something as simple as generating an automatic response to an email to deploying thousands of bots, each programmed to automate jobs in an ERP system.

Robotic Process Automation Examples:

Automation is the demand from most of the individuals if they are thrown a question at them “Whether or not would you be fine with those boring tasks off of your hands”. RPA enables organizations to make use of these software robots to finish all these repetitive, time-consuming work for improved customer satisfaction. In addition to that, employees can now look into many pressing matters than the same old boring tasks which could be automated. This also helps them ensure that they can develop their skills and experience for the betterment of the Organization.

Robotic Process Automation is well suited for processes that are clearly defined and well documented, repeatable without many changes and also if they are rules-based. RPA should be implemented after a lean six sigma study. Based on criteria mentioned, it helps organizations across numerous industries automate the completion of a wide variety of tasks.

What are Analytics?

Analytics is the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns towards effective decision making. In other words, analytics can be understood as the connection between data and effective decision making within an organization. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.

Organizations may apply analytics to business data to describe, predict, and improve business performance. Since analytics can require extensive computation, the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics. Analytics should be implemented after RPA’s has streamlined and clean the data.

Examples of Analytics:

Business Analytics

Analytics can be applied to any area of a business including strategy, operations and sales. For example, operations analytics might look at product cost, quality control and the throughput of resources such as production lines.

Customer Analytics

Analytics are often used to model customer behavior. For example, modeling the events that lead to a customer becoming brand loyal.

Marketing Analytics

Analytics to look at the results of product, pricing, promotion, advertising and distribution strategies. For example, analytics might show that female customers in their 20s are 70% more likely to purchase a particular item at price A as compared to price B.