Guest Commentary: How Do You Tackle Big Data?

There are a lot of hot topics swirling around the supply chain industry right now, but one that seems to be permeating almost every discussion is “big data.” And big data is big: Put simply, it’s the collection and integration of massive amounts of information that can’t be processed using traditional data processing applications. This could include everything from inventory details to customer emails to fulfillment statistics. Just the thought of working with and integrating massive amounts of data is daunting, let alone accomplishing it. But if we take a step back for a moment and appreciate what the exercise can do for our organization, we can approach tackling big data the same way the old saying goes about eating an elephant: one bite at a time.

In other words, don’t worry about integrating massive amounts of information across your entire company. Instead, look at what is possible and then determine what is practical. Start by choosing one or two targeted processes to focus on and gather the data accordingly. Here are some key steps to consider when starting an operations plan involving big data:

  1. Start small. Yes, this sounds contradictory in a big data exercise, but taking on too many processes or departments will only create confusion and frustration. Instead, work closely with business counterparts across the organization to discover what types of information would improve business outcomes and where that information might come from. Identify the source(s) and frequency of the data to integrate. This includes key reports, vendor profiles, customer ordering habits, DC locations, inventory levels and more.

  2. Determine who needs to know what. Have a clear understanding of which key pieces of information would benefit which individuals, and when they need to know it in order to make timely decisions.

  3. Determine whether technical solutions for the selected business ideas exist. If so, decide on the appropriate solution based on the complexity of the data.

  4. Execute with the right team and a realistic timeline.

With the exponential growth of data and the increasing complexity of decisions in the extended supply chain, companies can no longer rely on manual analysis in decision making. One of the significant barriers to succeeding with big data will be the ability to ask the right questions and use the right technologies to get the answers. Unfortunately, there is not one technique or technological solution, but an approach that relies on a wide variety of tools, methods and often new skill sets to support decision making across the supply chain. You must have a very clear understanding of what you are trying to accomplish or what problem you are trying to solve.

It is too easy to get lost trying to find your way through a large jungle of data. Make sure you develop a solid plan, get buy-in from the right people and have a definition around the value you can generate from the data. Big data doesn’t have to be daunting, but it often has to be addressed in small steps to help increase the chances of buy-in, follow through and ultimately reaching your objectives.

Chuck Fuerst is the director of product strategy at HighJump Software. He has more than 15 years of experience in the technology market, working for supply chain and ERP software companies to deliver innovative solutions. Chuck is responsible for monitoring supply chain industry and technology trends and identifying ways to enhance the value of products for HighJump’s customers. He holds a bachelor’s degree in marketing management and innovation from Concordia University.

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