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Machine Learning Is Redefining The Enterprise In 2016

machine learning imageBottom line: Machine learning is providing the needed algorithms, applications, and frameworks to bring greater predictive accuracy and value to enterprises’ data, leading to diverse company-wide strategies succeeding faster and more profitably than before.

Industries Where Machine Learning Is Making An Impact  

The good news for businesses is that all the data they have been saving for years can now be turned into a competitive advantage and lead to strategic goals being accomplished. Revenue teams are using machine learning to optimize promotions, compensation and rebates drive the desired behavior across selling channels. Predicting propensity to buy across all channels, making personalized recommendations to customers, forecasting long-term customer loyalty and anticipating potential credit risks of suppliers and buyers are Figure 1 provides an overview of machine learning applications by industry.

Source: Tata Consultancy Services, Using Big Data for Machine Learning Analytics in Manufacturing – TCS

Machine Learning Is Revolutionizing Sales and Marketing  

Unlike advanced analytics techniques that seek out causality first, machine learning techniques are designed to seek out opportunities to optimize decisions based on the predictive value of large-scale data sets. And increasingly data sets are comprised of structured and unstructured data, with the global proliferation of social networks fueling the growth of the latter type of data.  Machine learning is proving to be efficient at handling predictive tasks including defining which behaviors have the highest propensity to drive desired sales and marketing outcomes. Businesses eager to compete and win more customers are applying machine learning to sales and marketing challenges first.  In the MIT Sloan Management Review article, Sales Gets a Machine-Learning Makeover the Accenture Institute for High Performance shared the results of a recent survey of enterprises with at least $500M in sales that are targeting higher sales growth with machine learning. Key takeaways from their study results include the following:

Why Machine Learning Adoption Is Accelerating

Machine learning’s ability to scale across the broad spectrum of contract management, customer service, finance, legal, sales, quote-to-cash, quality, pricing and production challenges enterprises face is attributable to its ability to continually learn and improve. Machine learning algorithms are iterative in nature, continually learning and seeking to optimize outcomes.  Every time a miscalculation is made, machine learning algorithms correct the error and begin another iteration of the data analysis. These calculations happen in milliseconds which makes machine learning exceptionally efficient at optimizing decisions and predicting outcomes.
The economics of cloud computing, cloud storage, the proliferation of sensors driving Internet of Things (IoT) connected devices growth, pervasive use of mobile devices that consume gigabytes of data in minutes are a few of the several factors accelerating machine learning adoption. Add to these the many challenges of creating context in search engines and the complicated problems companies face in optimizing operations while predicting most likely outcomes, and the perfect conditions exist for machine learning to proliferate.
The following are the key factors enabling machine learning growth today:

Further reading

Companies Are Reimagining Business Processes with Algorithms. Harvard Business Review. February 8, 2016.  H. James Wilson, Allan Alter, Prashant Shukla. Source: https://hbr.org/2016/02/companies-are-reimagining-business-processes-with-algorithms

Domingos, P. (2012). A Few Useful Things to Know About Machine Learning. Communications Of The ACM, 55(10), 78-87.

Pyle, D., & San José, C. (2015). An executive’s guide to machine learning. Mckinsey Quarterly, (3), 44-53. Link: http://www.mckinsey.com/industries/high-tech/our-insights/an-executives-guide-to-machine-learning

Sales Gets A Machine-Learning Makeover.  MIT Sloan Management Review, May 17, 2016. H. James Wilson, Narendra Mulani, Allan Alter. Source: http://sloanreview.mit.edu/article/sales-gets-a-machine-learning-makeover/Sebag, M. (2014).

The Next Wave Of Enterprise Software Powered By Machine Learning.  TechCrunch, July 27, 2015. http://techcrunch.com/2015/07/27/the-next-wave-of-enterprise-software-powered-by-machine-learning/

What Every Manager Should Know About Machine Learning, Harvard Business Review,  July 7, 2015.  Link: https://hbr.org/2015/07/what-every-manager-should-know-about-machine-learning

What Is Machine Learning? Making The Complex Simple.  Mike Ferguson.  IBM Big Data & Analytics Hub. Link: http://www.ibmbigdatahub.com/blog/what-machine-learning

World Economic Forum White Paper Digital Transformation of Industries: In collaboration with Accenture Digital Enterprise, January 2016. Link: http://reports.weforum.org/digital-transformation-of-industries/wp-content/blogs.dir/94/mp/files/pages/files/digital-enterprise-narrative-final-january-2016.pdf

Yan, J., Zhang, C., Zha, H., Gong, M., Sun, C., Huang, J., & Yang, X. (2015, February). On machine learning towards predictive sales pipeline analytics. In Twenty-Ninth AAAI Conference on Artificial Intelligence.  Link: http://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/viewFile/9444/9488

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