Taking Machine Learning from Myths to Business Reality

Julie Colas and Mark Ellis | 30 November, 2018

Topics: Lean Six Sigma, Six Sigma, Continuous Improvement, Machine Learning, Predictive Analytics, Data Analysis, Quality Improvement

You now often see “Machine Learning” appearing along with “Big Data”, “AI” or “Internet of Things” in the discussion of the digital transformation of business.

Yet these terms or buzzwords are often misunderstood. This is creating a series of myths, which can misinform businesses’ decisions when pursuing a data-driven strategy.

To give clarity to data-driven professionals, here is a breakdown of key points you need to know about digital transformation and where Machine Learning fits in business reality.

Exclusive webinar: Learn the business reality behind the 6 biggest myths about Machine Learning in this webinar. Watch it now: From Unicorns to Racehorses - Taking Predictive Analytics with Machine Learning from Myths to Business Reality

The Digital Transformation Race

 2018-11-Unicorns to Racehorses - The Digital Transformation Race

Today, all organizations are in the digital transformation race; it is imperative for all, from the small to the large enterprise. This race is also unique for every company and business sector – but what really is this digital transformation?

This race is two things. Firstly, the integration of digital technology into all areas of business, fundamentally changing how an organization operates and deliver s value to their customers.

Secondly, it's also a cultural change that requires organizations to continually challenge their structure  and status quo, to experiment - and to get comfortable with failure too. 

In other words, this is an exploratory and exciting adventure. Yet today’s myths imply that you will only unlock the benefits with certain technologies or skills such as Machine Learning or Data Science.

Is this true?

Is Machine Learning the key start to Digital Transformation?

Data is central to companies being able to make good decisions about products, services, employees, strategy and more. 

At Minitab, we see every day that there is much to be done by organizations to realize the power of the data on hand and the data that they are collecting.

One technique of analysis is Machine Learning. It is just one of many predictive analytic techniques. A simple way to think of Machine Learning is as follows :

Machine Learning = an algorithm to convert data into information

Which doesn’t sound quite so radical now, does it?

In Machine Learning, algorithms exhaustively search the data available, to identify the key predictors of specific business events or outcomes – e.g. defects or downtime.

But to deliver actual business value, this technique cannot exist by itself. It has to be part of a whole process that is driving actionable decisions.

2018-11-Unicorns to Racehorses - Where Machine Learning Fits

'Unicorn' myths are shutting out experienced professionals

Today’s trending topics suggest that Machine Learning, Big Data and Data Science are important in the digital transformation of industry.

The power of these tools and techniques has been promoted in some cases to seem like a magical wand  to easily convert data into actionable decisions, and provide direct solutions to problems.

This hype has led to Data Scientists sometimes to be referred to as “unicorns” – scarce creatures with magical powers to transform a business. This scarcity is leading to a bidding war from CEOs and boards who see a Data Scientist as their answer for digital transformation, but aren’t really sure why or how to use them.

This is a danger.

These technical abilities are not the only part of the solution. Knowledge of the organization’s processes matters most, so you know where this technology can be applied to solve problems and unlock improvements.

A danger is that domain expertise is getting overlooked in favor of ‘unicorns’ who possess seemingly mythical powers. The sense that digital transformation is something new is shutting out an organization’s existing data-driven problem solvers.

For example, Lean Six Sigma Black Belts are not yet commonly associated with digital transformation.

However, according to this interview with Hitachi’s leader of smart manufacturing, it should be Black Belts driving digital transformation. For real-world data-driven innovations and problem-solving, these are the most experienced professionals you can approach.

Expose these myths to advance your progress

Organizations need a clearer understanding of the roles, the uses and the impacts of the opportunities above in a digital transformation.

This will help to define the expectations of senior management and how to successfully apply these opportunities  to your business reality.

To understand the truth behind Machine Learning & Predictive Analytics Myths, take the next step and watch this free webinar:

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WEBINAR - From Unicorns to Racehorses:
Taking Predictive Analytics with Machine Learning from Myths to Business Reality

You receive expert insights as Gillian Groom, Technical Training Specialist at Minitab, converts the 6 biggest myths into business reality.