How to Implement Data Analytics in Your Distribution Center
Data analytics is an industry buzzword that seems to pop up everywhere. The distribution and logistics industry is only the latest in a long line of industries where data analytics are becoming mainstream and even vital. How is data analytics being used in distribution centers and how can you implement a new data management system in your warehouse?
Why You Need Data Analytics
First, why do you need even to consider adding data analytics to your warehouse?
It’s simple — we live in the digital age, and unless you’re a distribution center for retail giants like Amazon, you’re going to be scrambling to keep up with the changes in the logistics industry. Companies like Amazon have the funds and the workforce to streamline every step of their process, going as far as adding picking robots to their workforce and equipping their employees with RFID or GPS trackers to monitor productivity.
Most companies don’t have the workforce or the income to make those kinds of drastic changes — but thankfully, including data analytics in your company’s processes doesn’t mean you have to make massive or expensive changes. Streamlining your distribution system means that you can effectively manage your inventory with fewer errors, keep item prices in check, while preparing for upcoming peak seasons or unexpectedly high demand.
What Are Your Goals?
First, why do you need to implement a data analytics system in your distribution center? What are your overall goals?
Are you trying to improve inventory management to augment efficiency and prevent inventory loss or shrink?
Do you need a cloud-based data management plan to help you sort through all the information that your company generates daily?
Once you’ve figured out what your primary goals are, it’s time to move into the planning phase.
The Planning Phase
Before you start making any major changes, the first thing you need to do is spend 12-16 weeks planning out your data optimization system. Trying to implement any major moves without a comprehensive planning phase will inadvertently fail. Collect as much operational data as you can over that period to help your team or consultants design the most useful data analytics system possible for your specific distribution center.
Data analytics programs aren’t something that you can copy and paste from one company to the next. They are specifically designed for each company and take substantial planning to implement. Collect information on:
- Item information for each SKU in your facility, including item location.
- Order history for the past 12 months including at least one peak season
- Forecast demands for five years or as long as the company have been in operation if less than five years.
- Inbound receipt details and customer data.
Collecting 12 months or more of data helps you create a baseline for your data analytics system. Any deviations from this baseline will generate an alert — often before something goes wrong. The goal of these systems is to streamline and automate data collection, reducing errors and speeding up the process considerably.
Choosing a Data Analytics Platform
Once you’ve collected the data to create your baseline, your next step needs to be choosing your analytics platform. You have a couple of options on this front. Warehouse management systems or WMS are traditionally cloud-based and focus almost exclusively on the movement and storage of inventory. A WMS can keep track of your inventory in real time, updating your information as items move in and out of the warehouse.
Enterprise Resource Planning (ERP) software is designed to automate all of the activities in your facility, from inventory management to customer service and accounting. This is a one-stop shop when it comes to data analytics for distribution centers, but it requires significantly more effort and preparation to implement. That being said, 84% of midsized companies have already implemented some form of ERP software in their operations.
The platform you choose will depend on your distribution center’s needs. If you only need a program to keep track of your inventory, a warehouse management system may be sufficient but if you need something to streamline your entire operation, opt for an enterprise resource planning program.
Include Everyone in Your Plans
Adding a data analytics system, whether you’re opting for a WMS or ERP software program, is no small feat and it’s something that will require the cooperation and participation of everyone in your company, from the highest CEO to the lowest team member.
Ensure that everyone is informed of the upcoming changes well in advance. Provide any additional training you deem necessary to make sure that everyone is prepared for the eventual adoption of this new system. New training might take some time out of their workday, but it will ensure that there will be no hiccups once the latest data analytics system goes online, preventing efficiency problems while everyone gets used to the new policy.
The Results — How Did It Work Out?
Once you’ve collected your information, chosen your analytics platform, and adopted it, all you’ve got left to do is evaluate the result. How did a data analytics program in your distribution center change your standard operating procedures? Is there anything you could have done better, or any aspects that you could have left out entirely in favor of efficiency and productivity? Taking a close look at your results can help you tweak your data analytics program to improve it for the future. These programs are continually changing and adapting to your needs, so don’t hesitate to make some changes if you feel like your program isn’t as efficient as it could be.
Megan R. Nichols is a industrial writer and blogger. She regularly publishes in magazines like Manufacturing Global, EBN Online and Industry Week. She also updates her personal blog, Schooled By Science weekly with easy to understand manufacturing and technology articles. Keep up with Megan by subscribing to her blog or following her on Twitter.