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You need a robust enterprise infrastructure to build a successful company these days. Technological advancements enable companies to provide consumers with customized products and create tailored marketing campaigns. Many of the most exciting advancements in technology are a result of big data, and businesses across the United States are using it to take their enterprises to new heights.
Of all the big data tools out there, predictive analytics might be the most exciting. It has far-reaching capabilities and has use cases and potential in every sector of business. Statistical models produced by predictive analytics tools give companies valuable insights into future events and market potentials. To learn more about the ways predictive analytics can bolster your small business, read on.
See market trends and changes in demand before they come.
Can you imagine how many companies could have prevented their downfalls if only they could have seen the future events that precipitated their downfalls in advance? As you know, commerce is based on the principle of supply and demand, and changes in either of those elements can have dramatic effects on your company’s business processes and sales.
Predictive analytics gives businesses the ability to see changes in demand ahead of time so they can plan accordingly. Using historical data and machine learning algorithms, companies can create predictive models that can forecast changes in the market, such as a coming lull or spike in sales.
Many of the finance and mortgage companies you can read about on the InfluentialTimes website use analytics to gain predictive insights into the markets. If predictive analytics can help financiers see what’s coming their way, imagine what they can do for your small business.
Use predictive maintenance to cut downtime due to malfunctions.
The manufacturing relies on expensive heavy-duty equipment for their business processes, and even the best machines eventually break down. Operations can be delayed or halted for days when significant malfunctions occur in factories, and manufacturers often end up having to pay their employees for not working during maintenance downtimes.
Many manufacturing companies employ predictive analytics to predict when their machines will need maintenance. Knowing when a machine will need maintenance before it breaks down saves companies time and money and helps them to continue to meet and exceed customer demands.
Predictive analytics is a great cybersecurity tool.
Being that we live in a world that’s growing ever more dependent upon cyber technology, cybersecurity is a greater concern than ever. A data breach can be crippling to a company’s finances, security, and even more importantly, its image.
Predictive analytics gives companies actionable insights into when and how hackers are most likely to strike, enabling them to bolster cybersecurity and tailor it to meet their needs and fortify vulnerabilities. By analyzing large data sets of previous attacks, you can learn the most popular methods and timelines of cyberattacks and build a defense for your system that would make a professional football coach envious.
You can use predictive analytics to determine credit risk.
As you well know, providers of financial services use credit scores to determine creditworthiness. In recent years, the use of predictive analytics to determine creditworthiness has grown exponentially, and it’s a trend that should continue.
If your company finances purchases for your customers, using predictive analytics to determine credit risk could keep your company from gambling on the wrong applicants. There’s only so much you can learn from a credit score, and what you can’t learn from it, you can learn from different predictive models.
Now that companies in every sector of business are leaning on predictive analytics to gain insights into their industry, customers, equipment, and cybersecurity, you can expect the trend to continue to grow. Information is more valuable than gold in the world of commerce, and predictive analytics is a fountain of knowledge.