Data is a key driver for business growth across the globe. And industries across the globe have welcomed Big Data with open arms where it is bringing a new revolution to Lean Six Sigma standards. Lean Green Belt Training is all about data-driven decisions taken to improve processes. Terabytes and petabytes of data collected need to be turned into actionable insights for enterprises to thrive in this ever-so-competitive market.
Six Sigma is one such step-by-step statistics-oriented process improvement methodology used to lower the process variation rates. This Six Sigma philosophy was first pioneered by Motorola, GE, Ford, and Allied Signal in the mid-80s and 90s to have better ROI and increase their bottom line. Let us explore how Six Sigma has evolved over the years and its potential for analyzing massive amounts of data and its new beginning of statistically-driven problem solving and process optimization techniques.
Objective Changes from Defect Reduction to Process Optimization:
According to “The real-world use of big data, IBV Report”, it says that more than 60% of enterprises have witnessed an increased and more incisive data usage as a powerful competitive advantage. Enterprises across the globe will never let go of Six Sigma and the related statistical stools. It is a known fact that for any complex problem, there is a no better approach than the DMAIC (Define, Measure, Analyze, Improve, and Control) process.
In today’s times, with a huge chunk of data available, it makes it all the easier for operations personnel to understand the key value of such a problem-solving approach. In fact, the Six Sigma tools have evolved over the years where they have moved away from defect reduction to process optimization. Enterprises believe in rather than finding something wrong and fixing it, they are focusing more on something that is ‘just okay’ and improving it. When you have your processes under control the next obvious step is to optimize them.
Without the help of data, Six Sigma in the past was resource-intensive and time-consuming. It literally took 6 months or a year to complete a project and in the end, the results were difficult to maintain and there was no clarity on financial benefits which would help the senior management to believe in Six Sigma.
Today, enterprises are implementing only a few tools and not the whole Six Sigma project. For instance, the customer knows that one of the processes is not performing up to the mark and they need to improve it. Because the customer and their team already have process knowledge, they will be directly performing a DOE – Design of Experiments which is a multi-variant testing methodology to encourage optimum process settings. All this was possible because the team had access to customers’ data which helped to make an informed decision on how to go about optimizing the process.
When enterprises start to address more complex issues, the Six Sigma process pulls together a team to accelerate project execution. They start by defining the problem, setting up measurement systems, and then start collecting data. After a couple of months, the data collected will be analyzed by the team to create an action plan and then go ahead with the implementation of process improvement techniques.
Analyze Massive Flow of Data in Real Time to Create Actionable Insights:
Today, data is collected at every stage of our lives, and anything and everything is data such as your DNA sequence, video streaming logs, social media activity, etc are a few examples of what raw data looks like. But enterprises are already using this raw data for research and to gain market insights to ensure their business services stay relevant in the future. For instance, Boeing, says that a single transatlantic flight of a four-engine jumbo jet generates 640 terabytes of data. That is a huge amount of data and if carefully looked into can give actionable insights from where you can streamline many processes.
Enterprises use Lean Six Sigma Standards to increase the speed of business services while maintaining quality. If enterprises can access and analyze the massive inflow of data in real-time this could help their Lean Six Sigma journey to save a huge amount of operational resources.
Even before the explosion of Big Data, enterprises recorded or stored the data on a small scale. But it was so laborious that the practical application of Six Sigma based on data was avoided completely. Today, Data is available in every facet and is helping process improvement methodologies such as Lean Six Sigma to transform processes which is devoid of wastage and that provide a better quality of services.
In past, implementation of the Six Sigma concept in an organization required a person who had the knowledge of Six Sigma statistical tools and experience working on hundreds of projects. But today, data has helped in an immense way where enterprises can rely on their own employees to get trained and start implementing areas that provide easy wins with high impact. This high impact gets people excited in your organization and gathers better support along the way. For instance, you can go ahead and start with your marketing and sales domain as it offers high data along with high customer impact.
