The Organization use of Machine Learning



The Organization use of Machine Learning

Your competitors are using machine learning (ML) to support sales forecasting, what do you do? Organizations today are applying machine learning capabilities to a wide variety of uses especially in improving decision making. Improving decision making translates directly to improved organization performance. The increased use of analytic techniques, data bases and algorithmic techniques means that managers need understanding of the value and effort relating to ML.

A 2011 Mckinsey report indicated that by 2018 1.5 million managers and analysts will be making decisions using analytical skills. How many managers and professionals today are capable of recognizing, understanding and using ML techniques for best value? Identifying, organizing, integrating and delivering ML capabilities to useful points in the organization is a key issue today. The good news is that organizations are already using some of the techniques without knowing they are part of ML. Machine learning is still a developing discipline. With over 50 different ML algorithms how do you know which one to use? Which one provides insight that you can use now? Which should you be looking at for the future? There are however, many machine learning algorithms that are reliable, easy to use and have great value to the typical organization. Statistical algorithms like affinity analysis, correlation matrices and semantic keyword analysis are used daily to assess market opportunities and customer and citizen behavior. ML promises faster, more effective decision making. This enables the ability to respond to rapidly changing market conditions, waves of culture shock and shifting markets.

Managers and professionals should prepare for the coming changes in analytics. What happens when ML becomes part of automated decision making? What will ML do for us in the future? How much of this will be done by robotic processes? Answers for these and other questions are part of the value of this course. This course is key for managers, strategic planners, marketing analysts, data analysts and architects, planning managers, process analysts, business analysts, business, enterprise and IT architects.

Expected learning outcomes

Expected learning outcome:

  • Explain the different features and purposes of machine language techniques today
  • Understand the statistical techniques used for the different types of ML capability
  • Define a roadmap to reach effective use of ML
  • Explain methods and tools available for ML
  • Interpret how ML helps the organization improve performance
  • Select appropriate ML techniques for their organization
  • Understand the advantages, limits and practical use of ML
  • Apply ML to social media data to understand market potential
  • Suggest operational opportunities for ML for performance insight

Who should attend

Who should attend

This course is key for managers, strategic planners, marketing analysts, data analysts and architects, planning managers, process analysts, business analysts, business, enterprise and IT architects.

Your trainer

Meet your expert course trainer: Frank Kowalkowski

Frank KowalkowskiFrank Kowalkowski is President of Knowledge Consultants, Inc., a firm focusing on business performance, business analytics, data science, business architecture, big data, business intelligence, predictive analytics and statistical techniques. He has over 30 years of line management and consulting experience in a wide variety of industries. He has been involved with many projects both as a user and purveyor of business analytics. He has worked projects in state and federal government dealing with back office operations, legislative compliance and regulatory compliance. He has worked on the federal level with the national defense department, Coast Guard for drug interdiction and other projects. His background includes a number of industries including manufacturing, distribution, supply chain, banking, insurance, financial institutions, health care, pharmaceuticals, oil and gas and chemicals.

More recently Frank has been involved in conducting workshops, professional training sessions and assessments of architecture, data science, governance, compliance, risk and process management efforts. He also develops algorithms for analytics tools particularly semantic algorithms as well as data analysis techniques.

He is often a keynote speaker, panel moderator and member at international conferences as well as a conference chair, he has written numerous papers and spoken at conferences on a variety of business subjects. He conducts frequent seminars nationally and internationally on a variety of business management, analytics and information technology topics. He is the author of a 1996 book on Enterprise Analysis. His most recent publications are a featured chapter in the business book “Digital Transformation: Using BPM You Already Own.” for publication in 2017. His chapter is titled “Improve, Automate, Digitize”, he also has a chapter in the business architecture book titled ‘Business and Dynamic Change’ June, 2015 and a chapter on semantic process analytics in the book Passports to Success in BPM published in 2014 all are available on Amazon.

About KCI

Knowledge Consultants. Inc. (KCI)


Knowledge Consultants, Inc. is a professional services firm founded in 1984. KCI provides consulting and professional education services. With over 50 courses taught worldwide, KCI provides the opportunity to develop core strengths in the following certification areas:

  • Process Management
  • IT Management
  • Business Performance Management
  • Business Analysis
  • Analytical Techniques for Business
  • Business and IT Architecture

KCI has expanded its training and consulting efforts internationally into Europe, Southeast Asia and the Middle East. KCI has an outstanding list of current and past clients including many of the Fortune’s 100 companies.

Consulting focuses on the key areas of Business Performance Management, Process Management, Business and IT Architecture, Business Analysis, Using Analytic Techniques for Performance Improvement and IT Management.

Download Brochure and Articles

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