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How Predictive Analytics Makes Businesses Disruption-Proof and Profitable

Predictive Analytics

2020 brought to the fore the irreplaceable role of technology in business resilience—among a gazillion other things. Software technologies, in particular, saw a meteoric rise in popularity across industries. Many analytics called it the pandemic-spurred digital transformation wave. You might like to call it something else. But the point is, these cutting-edge enterprise tech solutions have now taken over the commercial arena—more than ever. Predictive analytics-based artificial intelligence solutions rank top among those technologies.

With help from predictive analytic models, businesses can efficiently handle and maintain their assets. Whether you operate a manufacturing plant or manage a utility company, predictive analytics helps you everywhere. In this blog post, we will discuss how artificial intelligence solutions leverage predictive analytics to make businesses more insights-driven. But before that, let’s get our basics right.

What is Predictive Analytics?

Predictive analytics relies on AI and advanced analytics capabilities to make predictions about future events. It uses historical data combined with statistical modeling, machine learning, and data mining techniques. Companies in industries like manufacturing and utilities deploy predictive analytic to detect patterns in data and identify risks.

With its unique capabilities, the popularity of predictive analytics is growing rapidly. Analysts estimate a global market of nearly $10.95 by 2022, according to Zion Market research. Using the most advanced breed of artificial intelligence solutions and analytics, businesses can avert significant risks. Tech companies often combine predictive analytics with other techniques like big data and machine learning for more accurate prediction-making. Data scientists also implement deep learning and ML algorithms to spot patterns in more complex data. With help from machine learning development services, businesses of all kinds can rely on such techniques.

Business Benefits of Predictive Analytics

From improving service quality and regulatory compliance to reducing maintenance costs and business risks, predictive analytics benefits businesses in many crucial ways. Here’s how.

Better Service Quality

With an analytics-driven business model, you could dramatically improve the quality of service. For instance, if you manage a utility company, outages are common roadblocks to customer service. Sudden outages could also be damagingly costly. But predictive analytics solutions allow utility companies to avoid outages and disruptions. It helps them improve customer service significantly.

Low Maintenance Costs

You must have heard—or ignored—the term “predictive maintenance.” It relies on predictive analytics to notify you about a potential maintenance requirement before it happens. The automotive industry is a pioneer in embracing predictive maintenance. Car owners can save substantial maintenance costs by repairing a part before it breaks down. Likewise, manufacturing plants and other facilities could use this technology to avoid production disruptions and save on maintenance costs.

Flawless Safety and Compliance

When you get notified about a potential outage or maintenance need, the safety of your operations increases significantly. Whether it’s a factory, an automobile, or an electricity grid, predictive maintenance makes everything safer. Besides, with analytics-based process management, you’re better equipped to ensure failure-proof regulatory compliance. Whether it’s industrial safety guidelines or government rules, analytics-based artificial intelligence solutions make everything smoother.

Challenges to Predictive Analytics Implementation

Having mentioned all the benefits of predictive analytics, we must also know that its implementation is easier said than done. If you’re a small or mid-sized enterprise owner, the challenges could appear formidable. And that’s why we’re highlighting so you don’t have to deal with surprises.

Data Management

Predictive analytics rely heavily on historical data. That means the more data you have, the better analytics you could create. But collecting and managing such massive sets of data is an uphill task for most businesses. But with a strategic approach, you could make this less challenging. You could also choose data analytics solutions from a suitable tech vendor. In addition to these, legacy data could be another critical roadblock. You need professional data management experts to handle such streams of data.

Deployment Costs

If you’re looking for a custom predictive maintenance system, you need to be strategic and careful about the costs. You need to collaborate with the right digital transformation solutions provider. Once you deploy the predictive analytics system, its long-term benefits will outweigh the development and deployment costs.

Choosing the Right Tech Platforms

And here comes one of the trickiest areas of development and deploying of predictive analytics. Even some of the tech providers struggle to pick the most suitable platforms. Only expertise can help you choose the platform that yields the best results. Consult tech experts who can guide you through the role of AI, ML, and analytics in this process.

Wrapping Up

Predictive analytic enables you to make more accurate and reliable business forecasts. Based on such insights, you could create comprehensive and future-proof business strategies. However, you need to consider the potential roadblocks and choose the most suitable technology. And that’s where the crucial role of tech vendors like OrangeMantra comes into play.

We help you strategize the entire roadmap for predictive analytics deployment and pick the most suitable technologies. Over the years, we have built personalized AI and ML-powered tech solutions for manufacturing plants and educational institutions alike. Reach out to us to discuss your tech strategy.

FAQs

Q. How should an organization begin with predictive analytics?

Businesses can start implementing predictive analytic with a pilot project. Ideally, starting with a critical business area is an excellent way. It enables you to measure and control the initial costs of deployment. Once your predictive model is full-blown, you could deploy it to other areas of your business.

Q. What is meant by big data analytics?

Big data analytics is the use of advanced analytic techniques against large, diverse data sets that include structured, semi-structured, and unstructured data, from different sources.

Q. How much does it cost to develop predictive analytics solutions?

The costs of predictive analytic vary depending on your requirements. If you need solutions with basic features, costs are comparatively lower. OrangeMantra offers AI and predictive analytics development services at a competitive price.

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