Understanding The ‘Unknown- Unknown’ Information Drivers Addresses ‘Sea of Data’ Issues and Creates Opportunities
I posted comments on Fast Company article discussing ‘Sea of Data’ issues Fast Company Article “Avoiding Short-Term Thinking In A World of Big Data” http://tinyurl.com/7gaepbl
I shared my vision that predictive analytics is ‘raising the bar’ in how we manage the ‘sea of data’, and offered comments on new directions I see in manufacturing and health care. Here is a copy of my comments posted on the Fast Company site:
The article makes the point that “…in a sea of data, how can we make sure that we’re not just reacting to the information in front of our face, but rather analyzing every possible input.”
One solution to the problem, not mentioned in the article, is the need to develop new analytics to identify key drivers which create the data ‘outcomes’. Predictive analytics enable us to identify these ‘unknown-unknown’ drivers that can only be found by analyzing data, looking for relationships and new rules that emerge developed by analyzing the data. Contrast this to today’s ‘deductive’ approach using expert opinion and well-defined rules.
This ‘data-driven’ analysis to create new rules is an inductive (rather than deductive ‘expert opinion’ based approach) and from my perspective holds great promise to radically change current business processes, improve productivity and improve our quality of life.
This may sound bold, but as the former CEO of an early stage predictive analytics company and also looking at new opportunities in analytics, I see exciting potential here.
Look at manufacturing. If a “supplier’s supplier” has a problem, supply chain management ensures quick notification, before it impacts the assembly line. Predictive analytics engines ‘raise the bar’ here by analyzing historical performance and risk data, often real time, defining future risk and performance drivers, and enabling management to optimize performance and mitigate risk.
Going beyond traditional data mining, these new predictive analytics tools analyze industry reports, government filings, trade press, and other sources to assess supplier “health,” pending regulations, and other “unstructured” data sources. Seamlessly integrating with other data, we can use these to more accurately gauge supplier and production line risk and improve performance.Driving new rules, providing real time early warning signs that impact future supplier and business performance are the new management tools to harness ‘the sea of data’.
Look at health care, my primary focus, where PA techniques hold great promise to help our current health care system. Consider the benefits of these new capabilities which are only a small sample of what lies ahead here:
• Tracking Medical Diagnoses, Treatments, Medications, Outcomes, Costs,Reimbursements, and Relationships
ICD or International Classification of Disease Codes , classifies diseases on health records.CPT or Current Procedural Terminology codes developed by the AMA describe services provided by medical practitioners. Medicare employs a similar system, using ‘HCPCS’. Tracking and examining relationships among these metrics, looking at patient data, identifying processes, and key cost and patient health drivers, you can develop ‘best practices’ to improve the health
• Identifying Adverse Drug Analyses – assessing underlying drivers to more effectively identify “at risk” patients
• Optimizing clinical trials (candidate selection and monitoring) – predicting higher risk clinical trial candidates and assessing the key risk drivers
• Developing directional indicators to predict the underlying drivers for treatment of chronic disease to understand how medication protocols impact treatment plans and patient outcomes
The new predictive analytic-based tools now emerging in all sectors are helping companies cope with the sea of data problem, and “raising the bar” in how leading firms optimize business performance in today’s dynamic global markets.
Paul B. Silverman
Author: Worm on a Chopstick : Understanding Today’s Entrepreneurial Age: Directions, Strategies, Management Perspectives http://paulbsilverman.com/books/
Linked in: Paul Silverman