Modeling the Unexpected
Expecting the unexpected is something that we typically don’t do in the business world. We look at current trends and expect them to continue, until they don’t, and the fastest businesses to adjust are typically the ones to succeed and make it out of an unexpected situation. Recently we were all thrown into an unexpected situation, the coronavirus pandemic. There were very few businesses prepared to handle this situation from a financial, staff, workload, and any other relevant standpoint. Following models on current trends is a great idea. Businesses can take advantage of current trends to be more successful, and if businesses start to model odd concepts or events that they might not have considered a possibility, they may be more prepared and successful during a time like the one we are living in now.
How to model the unexpected?
Predictive analytics uses statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future. This is so important because we can potentially map out situations that we never thought possible and quickly find out ways to adjust to them. Predictive analytics can be done by AI as well, which won’t significantly raise costs for a business and most big businesses already have something built into their budget for predictive analytics. Increasing that budget slightly to predict more outcomes on different events should be on their minds considering how poorly some businesses handled the pandemic. Predictive analytics would be able to help people across the world if it is used properly.
How to work a model
Working a model shouldn’t be difficult in today’s tech driven world. The whole idea of modeling is to provide opportunities to plan for different possible futures, such as understanding the impacts of future government intervention on supply and demand or how different scenarios might affect business operations, staffing requirements or customer concerns. That way, should one of the scenarios become reality, business leaders know in advance what they should be doing. Businesses will be able to survive in these scenarios or even thrive. Unexpected scenarios aren’t always bad. Something could go right in the world for your business to grow exponentially in a short amount of time, and you could have missed out because you missed on a model or didn’t factor in the new trend or scenario. If this becomes a more common practice, we can live in a more secure world. Job security can increase, knowledge about what to do in unprecedented situations will be available, and businesses will be more financially secure.
What do we need to do?
For this to become a reality, there needs to be more funding and research done on how to put out more models in shorter amounts of time. This task falls to data scientists who develop software on modeling and predictive analytics tools. Businesses are aware of what needs to be done for the most part and the current pandemic is opening their eyes to see why. More businesses may have survived. This technology will eventually be something that all businesses are relying on in some capacity and the sooner that it is here the better off businesses will be.
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