Big Data or Six Sigma?

Six Sigma or Big Data

In this fast pacing world of increasing uncertainty, fiercer competition and fast changing businesses, what makes the difference is the “speed”.

The winners have short time to market, so they need to have:

1. Exceptionally fast development to new offers

2. Lightning fast reaction to unpredictable changes

3. Quick reaction to solve customer complaints and meet their requirements

Six Sigma or Big Data?

The point which needs attention is that both affect the bottom line but in different ways.  Six Sigma aims to eliminate errors in the business process which may result in defects in any product or service and offer a seamless workflow optimization.    

Big data corresponds to the large amounts of data produced by any company or organization in its day to day activities and then predicting the trends. Data collection is a traditional activity. The difference is that today digitization has made the things go easier. Now the data can be collected, monitored and maintained in real time as well.   

Read Also: Diagnostic Imaging Improvements with Lean Six Sigma   

Six Sigma’s intelligent strategy and statistical tools help in improving the process performance and quality. Big Data and Six Sigma complement each other if blended properly. Six Sigma gets sub-optimized without Big Data and Big Data turns ineffective without Six Sigma.   

Working on Big Data

After gaining relevant Six Sigma experience and knowledge, there lies an opportunity for the organization’s data analyst to get a good hands-on experience with Big Data, indeed with some learning curve.

Lean Six Sigma focuses on reducing process variation. Lean Six Sigma green belt certification helps the trainees to attain perfection in identifying and eliminating the defects. This results in better quality output and reduced defects, ultimately resulting in better customer loyalty and ROI.

The Lean Six Sigma’s trained belters are fully equipped with statistical tools that are coupled with change management and project management skill set.

In this digital world, the future of every company is IT-reliant. Statistician or Data Analyst mine and analyze the data that is acquired from internal or external resources. Analysts with strong analytical and data mining skills will churn out the results from the input data to valuable insights. These insights actually help the organizations in understanding consumer usage behavior, market trends and aid in designing future strategies. 

Getting the best from one another

The Six Sigma equips the Six Sigma belters with adequate tools that help in efficient problem-solving. Talking about the Big Data world, data here is heavily crunched in order to find the correlations. Correlations is basically a skillset that is already being acquired during the Measure and Improve Phase of the DMAIC strategy.

The thing which is missing from the equation is the knowledge on how to mine the data and perform predictive analysis on it. All this requires a bit of learning curve.  

Lean Six Sigma Green Belt professionals are those invaluable gems that can help in your Big Data projects and on the other hand, data analysts can prove to be an excellent resource for the Six Sigma methodology implementation. 

Why Big Data Needs Process Improvement Experts?

For the organizations having thousands of employees, the analysis of large data set could turn out to be complicated. The statistics, numbers and figures could be overwhelming for an untrained person.  This is the main reason for which process improvement experts are inclined towards studying the analysis of Big Data. The IT managers are redefining their approach towards the data by strategically planning all the dimensions of Information Management.    

Read Also: Creating a Six Sigma Culture in Your Workplace  

Lean six sigma workflow optimization focuses on making decisions by skillfully acquiring data about any problem. On the other hand, Big Data gathers information/ data to answer the most challenging questions for which no one knows the correct answer in the business world.

Six Sigma uses small (sample sized) data to unlock any problem domain. On the contrary, Big Data uses huge (population sized) data and works on statistical trends to unlock the knowledge.  Big Data requires huge computer software and lightning fast power to operate quickly and accurately but there is no such requirement for Six Sigma.

When the organizations aim for business improvements, the business leaders should try to strike a balance between both Six Sigma and Big data. By studying the quality management trends 2018, it is evident that these two concepts cohesively work together by passing wisdom and insights back and forth just like old friends.

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