Automation has a substantial influence on improving Operational Excellence and Decision Making. Executives' strategic decision-making abilities are being enhanced by Machine Learning (ML) in an increasing number of firms nowadays.

Global research done by MIT Sloan Management Review in collaboration with Google, involving 4,700 CEOs and a number of Key Informant Interviews, indicates that ML is increasingly transforming how firms generate and analyze value. This is largely due to the capacity of Machine Learning to make Key Performance Indicators (KPIs) more rigorous and analytical. When KPIs are more demanding, executives can improve corporate operations by applying strategic indicators to guide machine learning (ML) algorithms.

Companies who invest in and employ ML to improve customer service are fundamentally distinct from those that do not. They have a comprehensive picture of their clientele and examine KPI data and reports frequently. It enables firms to liberate people from menial tasks so they may concentrate on essential goals.

Companies with a focus on Machine Learning regard data as one of their most valuable assets and adopt ML and other technology tools of the current period to develop a Competitive Advantage.  Significant findings of the MIT SMR study indicate that:

  • Approximately 75% of research participants stated that investing in Machine Learning and Automation enables them to meet their functional KPIs more effectively.
  • Organizations with the most innovative and remarkable ML projects demonstrated a strong commitment to managing data as a valuable asset.
  • Data-driven enterprises have a significant competitive advantage over those that adopt data or machine learning capabilities slowly.

Typically, the Marketing department is the first in a business to implement Machine Learning. Advertising, customer intelligence, and segmentation are the most common applications of machine learning.

Technology executives employ 3 crucial Machine Learning best practices to support Strategic Decision making:

  1. Employ KPIs to Enable an Integrated, Single View of Customers.
  2. Analyze and Interpret Factors Driving KPIs.
  3. Evaluate KPI Reports Carefully and Regularly.


Let's delve deeper into the complexities of the best practices.

Employ KPIs to Enable an Integrated, Single View of Customers

A comprehensive, data-driven view of the client is essential for company executives today. Companies that incentivize their staff to implement Machine Learning with relevant, quantifiable KPIs have a comprehensive, broad perspective of their customers.

The development of a single customer view is facilitated by rewarding the use of machine learning and establishing meaningful, practical, and attainable KPIs to measure its efficacy. This enables businesses to generate precise consumer segmentation and plan effective client interactions.

Analyze and Interpret Factors Driving KPIs

The subsequent best practice for enabling Strategic Decision Making using Machine Learning is to interpret the underlying factors that impact their performance indicators. Companies that are compensated for utilizing machine learning are more likely to agree that they can assess the factors and data that comprise their key performance indicators. The capacity to evaluate and analyze the elements of business KPIs contributes to the improvement of Operational Excellence.

This ability promotes a better understanding of company data and consumer demands, thereby influencing decision-making based on data. Leading companies utilize data, analytics, and ML to run software and apps essential for predicting client desires, manage systems required to comprehend business requirements, and make these systems smarter.

Interested in learning more about the Machine Learning best practices to enable Strategic Decision Making ? You can download an editable PowerPoint on Strategic Decision Making with Machine Learning here on the Flevy documents marketplace.

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