Industry Insights

Why Six Sigma Learnings are relevant for Big Data?

Big Data Picture

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Here’s a pop quiz. Answer true or false:

a)     Big data will be key to driving business growth

b)      You don’t know how to leverage big data in your organization

If your answers were “true” and “true,”  you are not alone. More than 60% of organizations see increased and more incisive data usage as a powerful competitive advantage.[1]On the other hand less than a quarter of the organizations view themselves as strong user of data.[2]

Successful Six Sigma programs[click here]  provide valuable cues on developing and implementing a strategy that addresses big data. Why Six sigma in particular? Because there are several vital similarities between Six Sigma and big data initiatives [Table 1]

 

Criterion

Six Sigma

Big Data&Analytics

What is the objective? Eliminate defect and improve processes Gain deeper insights into processes
What is/are the tool(s) used? Statistical Tools Data Mining and Analytics tools
Who Implements? Statistical Experts Data Scientists

Table 1: Similarities between Six Sigma and Data Initiatives

Here are the key learning from Six Sigma for a successful Big Data implementation.

a)      Big Data is the business. Companies like Motorola and IBM took the Six Sigma methodology and designed their businesses around it. Processes, organization structures and metrics were all designed to support the “zero defects” philosophy of Six Sigma.  Make no mistake – big data is becoming fundamental to business of the future . Organizations who fail to build viable business models around data will lose a key competitive advantage.

b)      “Show me the money”. A vital sign that Six Sigma is working is that the initiative “pays itself”. A good way to get started is to look for areas of easy wins with high impact. This gets people excited and gathers more converts along the way.  It also enables an”earn as you learn” approach. For high impact, the marketing and sales domain is a great starting pont – offering high data availability + high customer impact. Customer analytics products like CoreMetrics, Google Analytics are affordable, robust and can be implemented in short time with minimal disruptions to current processes.  Best practices, tutorials and expert advice are readily available to support your efforts.

c)       Centrality of purpose. Six Sigma requires not just the buy-in but active participation of the top management. Jack Welch in his book, “Straight from the Gut” outlines the relentless drive and personal initiative he took to implement  Six Sigma in GE. You need a similar evangelical zeal of senior management for big data. If your top management isn’t the biggest cheerleader of analytics it’s going to be a rough up-hill climb.

d)      Build your own army. There is a huge shortage of data scientists today. Not having resources, however, to act now is not good enough! When faced with a similar resource crunch Six Sigma implementers innovated. They created their own army of statistical experts who drove the program from the trenches[click here]. It also helped democratize the concepts in the organization much faster and helped get greater buy in.  You need to start evaluating a similar program for Big Data. Educating and mentoring data scientists much easier today than it used to be even a couple of years back.[3]

As I am writing this I just received a list of the 10 most innovative big data companies. There were only 2 large organizations in the list – GE and IBM. Both having extremely strong and successful six sigma culture in the organization. Is that a coincidence? I think not.

Data is central to how companies will operate in the future. It is too important to be left to the data scientists alone. Six Sigma programs contain several important learning which can be used in implementing a successful big data strategy.


[1] Analytics: The real-world use of big data, IBV Report, 2012

[2] Analytics: The widening divide.How companies are achieving competitive advantage through analytics, IBM and MIT Sloan study, 2012

[3] http://insights-on-business.com/electronics/become-a-data-scientist-in-30-days/

Global Industry SME - Electronics CoC at IBM

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