{"id":4370,"date":"2022-03-16T01:15:39","date_gmt":"2022-03-15T19:45:39","guid":{"rendered":"https:\/\/tdw.co.in\/crux\/?p=4370"},"modified":"2022-03-17T21:57:24","modified_gmt":"2022-03-17T16:27:24","slug":"using-predictive-analytics-to-stay-ahead-of-changes","status":"publish","type":"post","link":"https:\/\/tdw.co.in\/crux\/using-predictive-analytics-to-stay-ahead-of-changes\/","title":{"rendered":"Using Predictive Analytics to Stay Ahead of Changes"},"content":{"rendered":"\n

Modern businesses have access to datasets that are staggering in the sheer volume of data they contain. Most of the information pulled from this data relates to events that already took place. The total expenses spent on material last year, the number of new customers acquired, the average sales value per salesperson, and so on. <\/p>\n\n\n\n

This historical information can be useful, but wouldn\u2019t it be better if you could have insights into what may<\/em> happen in the future? This is the promise of predictive analytics<\/strong>. Businesses can build models using historical data to predict the potential for future outcomes. You can then provide insights into what may happen in the future. <\/p>\n\n\n\n

What are some of the ways a business can use predictive analytics <\/strong>to stay ahead of what is coming? <\/p>\n\n\n\n

Predicting Demand for a Product<\/strong><\/h2>\n\n\n\n

View Post<\/a><\/p>\n\n\n\n

One example of useful predictive analytics<\/strong> is the forecasting of demand for a product. Maybe you run a retail business, and you want to make sure you always have enough of a product to meet consumer demand, but you don\u2019t want to risk overstocking because storage and shelf space are valuable, or it might be products that have a limited shelf life. <\/p>\n\n\n\n

Predictive analytics<\/strong> can take data from a variety of sources to help a retail business manage its inventory. Historical sales data would be one obvious source of useful data for this application, but it could also look at the time of year, weather, and consumer sentiment among a range of other signals that might be relevant.<\/p>\n\n\n\n

Managing Material Needs<\/strong><\/h2>\n\n\n\n

A manufacturing business might need a variety of materials to keep production moving. With that said, the future of demand can be murky. You don\u2019t want a manufacturing facility to run out of key materials, but you also do not want to warehouse vast quantities of materials that might not be needed until a few months into the future. Beyond that, there is also the question of acquiring materials at the best price. <\/p>\n\n\n\n

The managers of manufacturing businesses can gain valuable insights into these concerns when they use predictive analytics<\/strong>. On the one end, you can predict the demand for the products the facility makes, but you need an output that can also consider things like supply chain disruptions, weather issues, and changes to the prices for different materials. <\/p>\n\n\n\n

Seeing the Future of Real Estate<\/strong><\/h2>\n\n\n\n

Predictive analytics<\/strong> has a lot of potential to inform the decisions of real estate businesses. At the agent level, predictive analytics<\/strong> can help them identify market segments that may have an increase in the number of prospective buyers in the near future. On the level of the investor, you could predict the future value of a property or create heat maps that indicate areas ripe for development or other types of investment.<\/p>\n\n\n\n

Predictive analytics<\/strong> in real estate could draw on a number of data sources to provide forecasting in several different ways. Of course, the current and historical value of properties would be valuable. These systems could also draw on data from lenders, occupancy rates, foreclosures, infrastructure development, and more. <\/p>\n\n\n\n

A Window to the Energy Markets<\/strong><\/h2>\n\n\n\n

The future of energy markets could be of interest to several different types of organizations. Financial institutions could use these predictions to make investments, and energy-intensive businesses could predict future costs or make purchases based on predicted rates. Utility companies could use predictive analytics<\/strong> to forecast rates for customers and to handle load management.<\/p>\n\n\n\n

Those interested in energy markets would have several data sources that could help with building predictive models. Histories of supply, demand, and pricing would be valuable. This is especially true when you consider the way pricing can affect demand. Beyond that, it could account for things like regulations, equipment failure, weather events, and geopolitics.<\/p>\n\n\n\n

Different organizations will need to deploy these tools in different ways. With AI-driven solutions like Crux Intelligence<\/a>, predictive analytics<\/strong> are more accessible than ever before. Contact our team to set up a demo<\/a> and learn more about augmented analytics and what it can do for your business.<\/p>\n","protected":false},"excerpt":{"rendered":"

Modern businesses have access to datasets that are staggering in the sheer volume of data they contain. Most of the information pulled from this data relates to events that already took place. The total expenses spent on material last year, the number of new customers acquired, the average sales value per salesperson, and so on.  […]<\/p>\n

Read More…<\/a><\/p>\n","protected":false},"author":14,"featured_media":4375,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[49],"tags":[55],"acf":[],"yoast_head":"\nUsing Predictive Analytics to Stay Ahead of Changes | Crux Intelligence<\/title>\n<meta name=\"description\" content=\"Read about ways a business can use predictive analytics to stay ahead via an AI solution like Crux Intelligence.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/tdw.co.in\/crux\/using-predictive-analytics-to-stay-ahead-of-changes\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Using Predictive Analytics to Stay Ahead of Changes | Crux Intelligence\" \/>\n<meta property=\"og:description\" content=\"Read about ways a 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