Here’s How to Integrate Analytics Into Your Distribution Center

Distribution centers play a vital role in our supply chains — and supply chains bring essential products to customers all over the globe. It’s probably not an exaggeration to say that without well-run, adaptive and technologically advanced supply chains, there’s little point in designing world-class products to begin with, since they won’t be able to get where they’re going when they’re needed most.

Equipping our distribution centers to service a global economy means leveraging high-quality data and putting it to work in analytics systems. But how do you actually integrate these tools — and what’s the competitive advantage?

Combine ERP and CRM

ERP and CRM are two major technologies that form the backbone for analytics in distribution centers. Without these tools, modern warehouses and other facilities leave useful data untapped:

  • Enterprise Resource Planning (ERP) systems make back-end tasks and data-gathering far simpler than they would be otherwise. An ERP software suite helps supply chain managers surface and react to a wealth of data — including customer purchases, billing and other historical data, shipping processes and company financial information.
  • Customer Relationship Management (CRM) systems are front-end systems that gather, organize and make real-time data more actionable. Customer interactions, data from marketing campaigns and tracking information are generally major components of CRM systems.

Whereas ERP provides analytical and planning tools based on what’s already occurred, CRM systems focus more on reacting in the moment. But the best way to utilize these systems is to combine them.

Investing in two separate software packages creates potentially conflicting databases of information. It also creates unnecessary labor in the form of tedious data entry and reconciliation between the two systems. Combining ERP and CRM can also reduce the number of steps between drawing up a proposal for a partner and turning that proposal into an order.

Look for Real-Time Analytics Functionality

Let’s take a closer look at some of the real-time analytical functionality offered by modern CRM and ERP systems. The ultimate goals for managers in harnessing analytics capabilities in distribution centers revolve around becoming leaner, more agile and more responsive to ever-changing conditions “on the ground.” Here’s what that could look like in practice:

  • Connected infrastructure and vehicles provide end-to-end visibility on the speed and efficiency of every operation while they’re in motion. Smart technology like this, powered by the Internet of Things, means fewer surprises and faster responsiveness to disruptions.
  • Automatic notifications can “tip off” decision-makers about business events as well as disruptions and opportunities.
  • When data is gathered in real-time, it also becomes more useful to partners and clients, who can engage in self-service through digital portals, including accessing historical and current records.
  • Real-time analytics makes it easy to pick out ongoing trends in demand, pricing, the geographical distribution of your customers and much more. All of this contributes to more accurate forecasting.
  • The surfacing of real-time data makes collaboration between business divisions and departments — such as customer relations and fulfillment — far easier and more streamlined and cuts down on miscommunication between parties.

In a world where Amazon fulfillment centers are the envy, practically by default, of supply chain and distribution center managers everywhere, it’s worth remembering that the retail giant’s endgame involves “predictive shipping.”

Once a far-future concept, predictive shipping involves readying customer orders even before those customers commit to clicking the “buy” button. For distribution centers that deal with repeat orders and long-term customers, a system like this is a no-brainer — but it’s not possible without access to real-time operational and analytical data. The more data gathered by operators in a supply chain, the easier it becomes to predict not just when customers will place an order, but also what those orders will contain.

Examples of Analytics in Action

The world’s supply chains bring together small businesses and major distributors, as well as small-batch and industrial-scale manufacturers. This remarkably complicated web can transport almost anything, which means analytics tools have to cater to a wide variety of product and business types.

Telecom companies don’t “ship” physical products — but what are fiber optic cables, if not a distribution mechanism? Even in telecommunications, analytics systems focused on customer trends, real-time interactions and visits to web properties can help shed light on customer churn and helps decision-makers single out opportunities to introduce new types of products and services or make changes to existing ones.

Small and large e-commerce companies alike benefit from gathering data on their web properties, such as bounce rates for new and existing customers, the average duration of visits and which products customers purchase after viewing others.

Think about businesses that focus on building local client relationships, too. Cars are major expenses that customers don’t take lightly. And neither do dealers, who must carefully plan their marketing budgets to reflect how — and when — customers seek out major new purchases. Automotive companies and local dealers have a lot to gain by peering into data such as how their customers interact with their website, how many reported major life changes since their last purchases, how many frequent local automotive shows or clubs, what kind of marketing materials get the most traction and much more.

What’s the Strategic Advantage in Leveraging Analytics?

If you need more convincing of the merits of bringing analytics into the mix at your distribution center, consider recent research which found that data-centric organizations are:

  • At least 23 times more likely to grow their customer base
  • At least 19 times more likely to improve their profitability over time
  • At least six times more likely to retain new customers for longer

If these aren’t compelling reasons to step up your analytics game, we’re not sure what is! We live in a world that’s reeling from the consequences of looking before we leap, producing more product than we need, squandering physical resources on products without proven demand and spending money on marketing and other communication efforts before we know what kind of return we’ll actually get. Big data isn’t the “new oil” for no good reason — it’s because a business without business intelligence is flying blind.

A photo of MeganMegan 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.

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