Using Predictive Modeling For A Better Way to Inspect

Let’s be honest here: site visit inspections are a hassle. They come with an array of logistical challenges that make them unwieldy and drive up overhead costs. Now, of course, they are an essential tool in ensuring compliance with the Statute as a whole and to the specific stipulations and/or restrictions imposed on individual licensees. Inspections help uncover unlicensed activities, unfair practices, and, in more serious cases, fraud. Because of how important these inspections are, they can’t be avoided. Thankfully, the challenges they come with can be alleviated by leveraging technology to identify trends, correlations, and risks and predict risk of non-compliance.

The challenges with traditional inspections

Oversight visits come with a plethora of pains, such as arranging travel, accommodations, coordinating with the licensee, and possibly having to reschedule due to longer or shorter inspections, weather conditions, and/or other unforeseen circumstances. This uncertainty creates an administrative overhead and drives up costs.

Traditionally, these were considered unavoidable logistical challenges; a necessary annoyance. Most agencies employ a common set of strategies, such as hiring inspectors from different parts of the state to reduce travel time and hotel expenses or grouping travel. While these solutions may help ease some aggravation, they have many limitations. Factors such as attrition, skill levels, and need for supervision regularly undermine these strategies. Larger states like Texas, California, and Montana have the additional problem of being encumbered by geographical expanse.

The real risk posed by these challenges is the possibility that licensees at high risk may not get the attention they need, leaving the licensees out of compliance and the citizenry vulnerable.

Risk prediction using technology

With recent advancements in technology, a previously-cumbersome approach has become practical. The solution for streamlining inspections that has gained wide acceptance in the private sector and is quickly moving through many industries is predictive modeling. What began as an algorithmic formula for predicting price trends and profitability is now being used to predict a wide range of possible outcomes in many different areas of operations.

You are probably familiar with similar algorithms from Netflix, which suggest the movies that you may like based on your viewing patterns, and Amazon, which suggest products to you based on your current and past purchases.

The private sector has embraced predictive modeling as the best way to make smarter business decisions.

Smart Inspections

Inspections don’t have to be a hassle anymore. Regulatory Agencies can and should harness the power of similar predictive algorithms to identify the risk associated with every license and use that information to plan their inspections more efficiently. Agencies sit on a massive amount of data that can help them make better decisions if it is properly utilized. Predictive modeling algorithms are the perfect tool for analyzing this data to find trends that can help better weigh risk, discover non-intuitive trends that are holding your organization back, allow you to effectively allocate time, and even recruit more appropriately.

Well-developed Predictive Models use artificial intelligence that continuously and automatically refines its own algorithms to improve its accuracy with experiential data. It can also correlate the experience, availability, and geographical constraints of every inspector to help agencies best utilize their resources and cut down on travel costs.

Gov2Biz is a Licensing platform that uses a proprietary Risk Modeling mechanism to help agencies determine which licensees pose the greatest risk of non-compliance so they can allocate time and resources where they are likely to be needed for more effective inspections. It doesn’t have to be such a headache just to check on your licensees.