How Predictive Analytics and Machine Learning Can Improve Your Planning and Decision Support Process

Are you up to date with how predictive analytics and machine learning could help your business?

There are an increasing number of use cases coming to light from small, forward-thinking and innovative businesses right through to large corporations. Wherever you sit on the scale, we’re certain there are ways your business can benefit from predictive analysis and machine learning.

In this article, we’ll show you some use cases to highlight how these growing technologies are helping in the planning and decision support processes for many businesses already.

At River Logic, we’re striving to provide these benefits to our clients and our partners’ clients as we continue to invest heavily in developing bespoke, value added solutions. With a foundation in prescriptive analytics, machine learning has even more power than simply having a foundation in descriptive and diagnostic analytics.

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5 Use Cases to Consider by Sample Industry

Both standard and custom predictive models and machine learning methods can be developed and implemented across a range of optimization use cases. Here are 5 use cases to consider:

1. Pricing Analysis – Financial Sector

There’s big money to be made in pricing predictions. Stock markets can be volatile, and there are many people who would like to better predict which stocks will rise and which ones will fall. Leading trading firms use systems and software to predict the market and make high speed, high volume trades. The main benefit is clear. Firms who have the best predictive analysis in place can make massive profits. There’s simply no way that any human could compete with analyzing such vast amount of data at these high speeds and efficiency.

2. Recommendation Analysis – E-Commerce / Online Services

We’re all familiar with this type of service, whether you realize it or not. From streaming services that recommend a song playlist based on your taste of music, to product recommendations based on your latest online searches; machine learning algorithms are getting smarter. Our online activity is constantly being monitored, analyzed and compared in order to recommend, promote and upsell products and services. This type of activity can provide sizeable revenue growth for businesses who embrace it.

3. Risk analysis – Banking, Logistics & Transportation

Risk is everywhere on a daily basis and it can be extremely costly if not handled correctly. Consider for a moment the risk that banks face trying to protect their customers’ personal details and account security. Think about the risks faced by logistics companies tasked with delivering $1.5 million worth of products on time, in perfect condition. It’s not hard to see why predicting risk for such companies is not only valuable, but essential. Predictive analytics can highlight potential risk areas from a large volume of data, and evaluate it to allow businesses to prepare accordingly and work towards mitigating the risk to protect their bottom line.

4. Equipment Monitoring – Automotive, Manufacturing

Many companies in the manufacturing sector have massive capital invested in high tech machinery and equipment. As such, protecting these expensive assets is almost as valuable as adding revenue to the bottom line. Predictive analytics is used to measure and evaluate lifecycle maintenance of the equipment through metrics and data from past experience. This means that companies can plan scheduled maintenance tasks more efficiently, minimizing costly downtime, and also budget for expected capital expenditure for wear and tear.

5. Capacity Planning – Airlines, Pharmaceuticals

Predictive analytics and machine learning are valuable tools for capacity planning. A range of industries are using these methods to help plan for demand. Take the Airline industry for example; they use historical data from previous years and metrics that are based on specific marketing efforts. This data allows them to plan better promotions at historically quieter times, and prepare for extremely busy periods in the form of more scheduled flights, or increased staff numbers. This results in more accurate forecasting and a much leaner business model overall, leading to greater profits.

It’s very clear to see from these examples that there are many benefits available to companies who are willing to embrace the technology and use it to turn their data into profit.

What About Your Business?

Now that you’ve read how other businesses are profiting from predictive analytics and machine learning – what’s your plan?

Planning and decision support processes are critical to the success of any business, and intelligent business software is helping businesses like yours grow. The software on offer is getting smarter all the time, and it could help your business to become more proactive instead of reactive, allowing you to plan better and identify new products or services to offer your customers.

Editor’s Note: This post was originally published August 8th, 2017 and revised September 30th, 2018.

prescriptive analytics

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