Predictive Analytics and 7M Methodology
İlknur Rodoplu
Transformation Leader | Risk and Crisis Management Consultant | Founder of CMONE and PRM Sigorta | Independent Board Member
These two ideas would initially seem to deal with different facets of corporate governance. But behind the surface, predictive analytics and the 7M technique share a powerful energy that, when applied successfully, may enable businesses to make informed decisions with unmatched accuracy and promptness. Let's look at how predictive analytics and the 7M methodology can transform decision-making, problem-solving, and the pursuit of operational excellence in this post.
Understanding Concepts
Predictive analytics is a more advanced type of analytics that uses historical data, statistics, and technologies such as machine learning to predict the future outcomes of organizational actions. On the other hand, the 7M technique is a structured strategy that is commonly used in manufacturing and process optimization. "Man, Machine, Material, Method, Measurement, Milieu, and Management" is what it stands for. Each of these seven categories reflects a factor that may have an impact on the process or outcome.
Shared Contribution to Process Improvement
Predictive analytics helps organizations identify which factors, i.e. which M as I mentioned above, are most critical in determining outcomes. By analyzing historical data, predictive models can reveal which variables have the most significant impact on a process or outcome. This information can also guide the focus of the 7M analysis.
The 7M methodology can be enhanced with predictive analytics to perform data-driven root cause analysis. When an issue or problem arises, predictive models can help identify possible causes by analyzing real-time data. This accelerates the identification of problem sources and enables organizations to take action more quickly.
Predictive analytics and the 7M technique both aid in continual improvement efforts. Predictive models can be used to monitor and predict prospective deviations or problems in real time. When paired with 7M analysis, this data can enable proactive process adjustments and enhancements to avoid problems from developing.
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Furthermore, predictive analytics can assist firms in more efficiently providing resources by forecasting future demands, equipment maintenance needs, or quality difficulties. Organizations can make better informed decisions regarding resource allocation in various aspects of their operations by integrating predictive insights with the 7M elements I described before in this post.
To Summarize…
Predictive analytics and 7M methodology may seem like disparate approaches, but they are inherently linked when it comes to data-driven decision making and process improvement. By combining the power of predictive analytics to forecast future outcomes with the structured analysis of the 7M methodology to identify potential causes, organizations can gain a holistic view of their operations and make proactive, informed decisions to manage risk. This synergy increases efficiency, reduces risks and paves the way for continuous improvement across a variety of industries, ultimately contributing to the success and competitiveness of businesses and organizations.
This shows that the combined power of predictive data and the 7M methodology should not be underestimated...
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