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3 Ways Predictive Analytics Can Harness Your Big Data

Businessman and businesswoman using digital tablet in the meeting. An inventory management system provides you with a plethora of data. You can gather information on everything, from real-time stock levels to customer behavior and trends. The problem is many companies have decided that this so-called “big data” is too much to handle. Or simply that they don’t need it. It was cool for a while because big data was the buzz word of the hour. But now? Not so much. Investing in barcode inventory management was the right move because your old manual process caused way too many errors that cost you big time.  Perhaps it’s not that you don’t need all this data, but that you aren’t applying it in the right way. Enter predictive analysis. Not a new concept in the business world, but it can be a huge benefit to any organization when married with big data. Predictive analysis is just what it sounds like: looking at your current data to predict future outcomes. It is essentially a road map to better business.


For example, the layout of the local grocery store was no accident. It was designed through analytics to maximize sales and politicians definitely use data in every way possible to predict how voters will turn out on election night. Your business can use it, too.

"Every industry can benefit from predictive analytics, it's just a question of whether they have the data on hand to make these predictions," said Rowan Curran, a researcher with Forrester Research. "There is no company that could not take their customer journey or developer roadmap and not take a look at a point where they could take information andpredict an outcome to better improve their business.”

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Predictive analysis takes your business’ data to the next level, and here’s how:

Get Your Business Processes Into Focus

When inefficiencies start costing your company customers and revenue, it’s likely that departments will start pointing their fingers at the other guys. Is it bad customer service? Disruptions in shipping and receiving? Or somewhere in between? Harnessing big data across operations can help pinpoint problem areas from end to end and optimize processes. These can then be backed up with customer feedback through reviews, social media, and more. This combination will ultimately eliminate wasteful practices and help you develop useful metrics, resulting in a better consumer experience.


“Usage of that data is cross-departmental” Florian Douetteau, CEO and co-founder of Dataiku, said in an article in Datamation. “Every group in a company can use data from their own group or from others. It is used in sales, marketing, operations, logistics, and R&D.” Gary Kincheloe, owner of Fairfax, VA based company Ace A/C and Heating was spending an exuberant amount of extra money on service calls because the company used a spreadsheet for inventory management. Ace was one of nearly half of small businesses that don’t accurately track inventory data. As a result, they had no visibility into what parts they had in stock at any given time. They always ran out of parts, causing service technicians to make extra trips to a regional supply depot where they had to wait in long lines to purchase parts they needed. It became the norm for workers to rack up extra travel expenses and time. Kincheloe knew he needed to do something to get inventory under control, so he invested in a mobile computer that easily updated inventory counts by scanning the barcodes on replacement parts as they were received. Once the inventory management system was implemented, service technicians could take parts from the warehouse for a job, and the inventory items would be checked out to them. Automated inventory management provides a constant flow of specific data, which when broken down, can renew focus. You can then make more educated predictions and change from how you’ve always done things to best practices.  The capability to make strategic changes will take you a step ahead in an ever-changing market and help you stand out from your competitors. Three managers analyzing financial statistics

Deepen Customer Relationships

You deal with a lot of people from the time your products leave the warehouse until they are delivered on your customers’ doorstep. You can build those important collaborations through a better understanding of big data. Think about how important your customers will feel when you truly understand their needs, due to predictive analysis of your customer data. Ace’s Gary Kincheloe used data from the company’s inventory management system to not only negotiate better prices for inventory items, but he says customer service has improved since technicians are able to immediately find the parts they need to complete a job more quickly.

Improve Supplier Networks

Without question, businesses of any size know that partnerships are the lifeblood for a healthy supply chain. “Businesses are increasingly relying on their suppliers to reduce costs, improve quality, and develop new processes and products faster than their rivals’ vendors can,” according to an article in Harvard Business Review. Once you learn how to use big data in a more productive way, your supply chain managers can form more in-depth relationships with suppliers through knowledge, rather than just focusing on completing transactions. The creation of larger, deeper networks should be the goal because that will lead to even more transactions in the future, along with more trust and client referrals. Predictive analytics are increasingly important to all facets of business, making processes more accurate, reliable, and less costly. How could you better identify issues and make wiser decisions for the future?