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In the world of inventory, a trend has emerged causing executives and supply chain operations to redesign process and operations. This trend is the use of big data to feed into AI and machine learning.
First things first, what is big data? 

To put it simply, big data is a term that describes a large volume of structured, semi structured, and unstructured data that is collected by companies and organizations and are mined for information. This information proves to be extremely crucial to these companies because they help enhance machine learning, predictive modeling, and other advanced analytics. Big data is usually characterized by its volume, its variety, and the velocity at which it is collected and eventually processed.  
Now that we know what big data’s all about, let’s highlight its importance in the industries of inventory and warehouse management. You see, big data has opened a lot of doors in industries such as these, and the opportunity for business growth is colossal in magnitude. Big data is the perfect example that as technology progresses, it propels establishments in even greater strides, and opens new opportunities that lay down the foundations for continual business development and expansion. Big data basically provides companies nowadays with a rich and vibrant pool of real-time data and comprehensive analysis that they can utilize and use to their advantage in making well-informed decisions pertinent to their businesses’ strategies and methods in inventory management. 

WithoutWire’s Travis Smith 

In his most recent blog, Travis Smith, the founder, and CSO of WithoutWire, shared his insights on how big data largely influences the way companies nowadays manage to grow their businesses and increase sales through more efficient inventory management. What prompted this realization in him was his short encounter with a magazine article that he chanced upon during his recent trip titled “Meet a Start-up with a Big Data Approach to Hiring”. The write-up basically talks about how big data is being used by various organizations all over the world to help with their respective Human Resource divisions, allowing them to predict the outcome of new hires.  
Travis Smith further elaborated that in the many years he spent reviewing and analyzing all sorts of inventories in businesses, what piqued his interest and amazed him was how solution needs for companies differ vastly from one another. He further explained that even for a single company, recommending the best method for a particular process can be very perplexing and challenging.  
Eventually though, through the utilization of volumes of data grouped into inventory related categories called “signals”, companies can match up which methods would provide the best results. He relates this experience with how his inventory management company, WithoutWire, wants to redefine the inventory management space by building inventory platforms that engage workers and drive efficiency in the supply chain, the warehouse, and beyond. He highlights how today’s inventory control systems now hold the key to powering business insights that can help them make data-driven decisions for increased productivity and profitability. 

An Empirical Perspective 

Another example to take note is how the company White Truffle does the job right by providing a data service using a proprietary model which analyzes 50 categories of “signals” in a job candidate’s profile. This company banks on the common belief that the more data they get, the smarter the model becomes. To better understand how this principle works, you should try to see it from a more empirical perspective; try to imagine it like you’re gathering information about a person in order for you to come up with the best way of approaching that person. As you can see, the more you know how they think and act, the better you can communicate with them. Now, apply this to a corporate perspective and you’ll begin to understand that the more information you have about people, the more likely you end up hiring the best employees. 
And while he says he’s not really an expert in the “Big Data” trend, Travis Smith is able to perfectly summarize its purpose: “more data to analyze means better results”. Indeed, big data analysis can be a valuable tool to selecting the best performers for your company. Furthermore, it can also be used for selecting the best performing method of picking, receiving, and bin strategies. It can even be used to leverage business operations and improve them to be able to make smarter and more profitable decisions. 

Big Factors for Big Data 

Here’s some of the factors that prove that big data is truly improving the world of inventory management: 

  • Big data improves operational efficiency 
    • Big data can be used to continually optimize the time given in picking, receiving, and bin strategies.  
  • Big data helps boost sales 
    • Companies that use big data can better decide on strategies for promotion and price based on demand, which translate to more maximized sales. 
  • Big data increases customer satisfaction across the board 
    • The data gathered will open opportunities to provide a better customer experience, such as in the example of identifying a poor-performing shipping provider so that there is a guarantee in customer satisfaction.  

​Seeing how Big Data helps companies thrive in today’s very competitive business climate is a wonderful thing. We can say that it truly is a revolutionary tool and could possibly be one of the key factors in shaping the future of the business sector. especially for executives like Travis who are involved with inventory management. One thing’s for sure though, big data helps distributors and manufacturers come up with the best methods in accomplishing their tasks and have a clearer grasp of the situation. At the end of the day, that’s all you really need.