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The data mining and modeling approach Investigation Analytics Group ™ offers corporate counsel and insurers is a unique and powerful way to consolidate numerous seemingly different cases into far fewer silos that share common bases of key technical issues.
Defining the silos based on technical key issues means that most of the key issues are defined once and can be researched to develop more insight as to why failures, accidents, and issues occurred. New cases start much higher on the learning curve, cutting time, cost, and producing better outcomes. Insight from this approach can be used by professionals, designers, technicians, scientists, and healthcare professionals to reduce the occurrence of the failures, accidents, complications, and negative outcomes. Litigators who may not be technically versed can focus on, and become experts in the few key technical areas that underlie the numerous failures, accidents, or industry related issues. Fewer litigation firms may be needed and case management becomes more efficient, and easier. These benefits are also available to insurers since insurers tend to have more presence in defined market segments.
Gatekeepers are both capable of taking a broad view of a failure or accident while being sufficiently knowledgeable and skilled to apply the requisite domain knowledge. Gatekeepers also differ from typical experts in several other important ways. Gatekeepers have to be far more experienced with searching for and identifying relevant scientific and engineering studies, which is a skill in itself and one in which many experts lack sufficient depth.
The challenge is not so much finding sources of data, but rather to be able to recognize that data is relevant because most available data was not developed for establishing the cause and origin of failures and accidents, nor was this data developed for the situation under investigation. Nonetheless, industry publishes much technical data for marketing and regulatory purposes and academia publishes much applied research, and some of this data can often be used to estimate properties that define a box, usually a very small box, that establishes the range of possibilities for the cause and origin of a failure or accident. This data and its analysis also establish estimates of what results testing should produce and significantly limits unsupported creative interpretation of testing and the events surrounding the failure or accident.
In reality, this phase of the investigation, and the extent to which it should be conducted never occurs in too many cases.
Mediation and other early resolutions processes cannot be treated as deals to be made because U.S. Supreme Court rulings cite the reliability of expert investigations as a central tenec for admissibility of expert testimony, so this should also be a central tenec of early resolution processes. Since a large portion of costs and the time involved in litigation is in the discovery phase, achieving early resolution and substantially reducing costs requires short-circuiting the discovery phase. Settling a case requires establishing a reasonable basis for understanding the key technical issues involved, who is likely to prevail, and what it will take and cost to prevail, which is what the discovery phase does. Analytics provides a reliable basis to resolve a case without completing the discovery phase.
Analytics involves data mining and modeling. For example, accidents and product/structure failures do not happen in a lab under controlled conditions and the watchful eye of measurement instrumentation. Although there is often data, it is limited in its scope and amount, and limited in its applicability since it is often contaminated with uncertainty and unrelated factors. Unfortunately, experts are often not involved until well after an incident when the site, equipment , or evidence may no longer exist. Data mining uses specialized, sophisticated software to visualize and identify patterns in the data that is available, and advanced statistical and artificial intelligence techniques to identify relationships and differences in the data and to test their significance. Although data mining is powerful in the insight it can produce, it is common for significant gaps to exist in the data. Modeling addresses this issue by using scientific principles and the known properties of materials to estimate the data needed to fill the gaps. These estimates are tested by also estimating data that exists.
Absolutely. Analytics during litigation are not a matter of if, rather a matter of why and how.
As is demonstrated by Virginia Tech’s College of Science having made analytics an overarching theme of its graduate degree programs. A recent message from the Dean of Virginia Tech’s College of Science stated “At the Virginia Tech College of Science, we have reimagined scientific research. We are focused not on data itself, but amplifying the relevance of that data with analysis, modeling, and interpretation.” (Va. Tech Science, Fall 2019)
Combining empirical trends in the data uncovered by data mining in litigation-related technical investigations with estimates made from modeling based on fundamental scientific principles, using data generated by academia and industry, not only fills gaps in the limited data available from the accident, of failure but is also uniquely able to provide insight as to what scientific principles were violated and why they were violated, resulting in the accident, or product failure. Testing the hypotheses made in an investigation is inherent in this approach, which is extremely valuable. Testing hypotheses is an essential aspect of the scientific method that guides the normal conduct of scientific investigations; and it is also fundamental in litigation-related technical investigation to meeting the rules of evidence.
Patents may not be reduced to practice, which poses a challenge in intellectual property (IP) disputes. Investigation Analytics Group ™ provides a reliable way to estimate how a device, or process as claimed in a patent, whether or not reduced to practice, would work by combining relevant available data with fundamental scientific principles.
Yes. There is an 800 USD annual membership fee to be a Select Consultant of Investigation Analytics Group. In addition, as a Select Consultant you agree to pay ExpertAnalytics Group 5% of all billable hours.
Pre-qualified experts in the scientific, forensic, medical, engineering, financial, and technical disciplines qualify to be prospective Select Experts of Investigation Analytics Group ™ ?
Yes. There is a pre-qualification process to become a Select Expert of Investigation Analytics Group ™ ? You may apply at the bottom of the FAQ page.
Training will be available for all Select Experts; and for potential experts who are on the threshold of meeting the criteria to become a Select Expert of Investigation Analytics Group ™ .
We will only be selecting 3 experts per specialization in the disciplines relevant to Investigation Analytics Group ™ .
Should you not be chosen as a select expert it does not mean that we do not deem you to be a qualified and credible expert. Multiple factors are taken into consideration when choosing Select Experts for Investigation Analytics Group, not just experience. Investigation Analytics Group focuses on the practice of analytics and evidence throughout litigation. We appreciate the interest of all of our applicants and we look forward to working with you as a member of our Experts Court Infinity app.
We will be posting very shortly an application on our website to become a Select Consultant of Investigation Analytics ™ . Once your application has been reviewed you will be contacted by one of our Investigation Analytics ™ support team to discuss your application and the opportunity further.
Once you are selected as a Select Expert there will be an onboarding call to discuss processes, communication, compensation, and literature will be provided to you.
Presently, USA, Canada, and the UK can participate in our Investigation Analytics ™ program and become Select Consultants.
Case opportunities are very specific and on-demand. Expert opportunities that meet the Investigation Analytics ™ criteria and relevant disciplines are in high demand. While we cannot predict that you will be retained for 30 cases per month, we can say that there will be no shortage of high quality cases.
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