Article

Asena Atilla Saunders
Asena Atilla Saunders 2 February 2017

The Importance Of Predictive Analytics

Big data can be a huge benefit to any organization when used with predictive analytics which enables business leaders to make really quick strategic decisions. It is basically a road map to better business.

Today we have more data than ever. Customers are generating different kinds of data every second from various interactions they make.  Having big data was a cool asset for the organizations for a while however knowledge hidden behind this information and using this data for the future decisions has become the major issues. If you have a crystal ball, great! But otherwise how can you identify issues and make wiser decisions for the future?

Luckily there is a solution for it: Predictive Big Data Analytics!

Predictive Analytics is a data driven technology and statistical techniques which examine large data sets to discover patterns, uncover new information and predict failure points and outcome for future.  Big data can be a huge benefit to any organization when used with predictive analytics which enables business leaders to make really quick strategic decisions. It is basically a road map to better business.

Every industry can benefit from predictive analytics. First thing to do is to know what your strategic goals are as well as the key metrics you want to use to measure the success of those goals. It’s also important to align the metrics with strategies you have set. You can then achieve efficiency in your business. For example, with predictive data analytics auto makers can forecast how many certain spare parts are needed at just the right times and improve their inventory turnover.

When you combine big data with predictive analytics, your business can connect the dots and uncover trends in your sales and customer behaviour.  Predictive analytics enables you to;

Provide in-depth customer insight and improve customer relationship

It is now possible to predict the spending habits of each customer by analyzing all the data regarding customer behaviour – transactions, web browsing, social media activity, interests, demographics and transform into meaningful trends.

Predictive analytics can improve your customer relationship not only by analyzing your customer behavior, also by analyzing your inventory management.  A more effective inventory management will enable your staff to immediately find the parts they need to complete a job faster. And effects on responding to your customers` individual needs more quickly.

Identify issues in business processes

In order to avoid inefficiencies costing your company customers and revenue, you can use predictive analysis to get your business process into focus.  These analyses can help you determine the problem areas from start to end in your work cycle and optimize the processes. You can also back this up with customer feedback through reviews and social media. This combination will ultimately eliminate inefficient practices and help you develop valuable insights.

Improve supplier networks

Predictive analytics are getting more important to Supply Chain Management as it makes the process more accurate, reliable, and at reduce cost. As supply chain management is a cohesive and continuous process, a delay or failure at any point will ripple through the system and cause inefficient execution. That is why predictive analysis should be applied to each step like looking at historical demand data and try to calculate future demands, converting that to forecast production requirements and backwards into procurement and logistics requirements.

To be a step ahead, you should also analyze: Demand Analytics, Inventory Optimization, Network Planning and Optimization, Transportation Analytics and Procurement Analytics together to see the big picture and make strategic changes.

Predictive analytics are playing a key role, supporting industries in making processes more accurate, reliable, and less costly.  When done effectively it will be a huge competitive advantage to your competitors.

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