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The Application of Predictive Analytics in Logistics

The idea of using business intelligence (BI) tools to optimize a small parcel shipping operation isn’t new. And you are probably aware there are many clear and immediate benefits of BI for companies that ship almost anything.

But the reality is most logistics operations fall short of seeing the results they were hoping for once they get started. Most often, the problem is that companies try to do too much themselves. Knowing there is value in your parcel data is an excellent first step. Building the process to use it, however, is another thing.

Here’s our advice on the most common problems to avoid if you choose to build your own in-house BI solution.

1) Not building the right model

Building a parcel data model that is effective and works cleanly is as much an art as it is a science. A poorly built data model will not provide the ability to effectively drill down, slice and dice, and roll up data in ways that are accurate, complete, and responsive. Not having the right model will doom any BI project before it even gets started.

2) Failing to automate data collection

Obviously, data is the lifeblood of BI. The good news is parcel shipping is a very data-rich operation, but the flip side is there is A LOT of it. So, making sure you automate the steps to pull that data into your BI platform is vital. If it’s not straightforward and automatic, the process will not be sustainable.

3) Not accounting for multiple data sources

Speaking of data, it can come in many different forms. API and EDI can work well once they’re set up, but there will be times that data is only available from emails, spreadsheets, PDFs, or some other format. Building in flexibility for how your data enters your systems needs to be a primary consideration. (For a good example, see point 6.)

4) Underestimating the effort required for maintenance

Data sources change, and systems and software need updates. Implementing a BI solution is not a matter of set it and forget it. It takes ongoing attention to make sure the platforms and outputs are functioning as intended, and to account for changes that the carriers make on an almost monthly basis, which is a lot more work than most companies realize.

5) Ignoring user experience (UX)

Over time, full user adoption only happens with systems that provide a positive UX. Data by its nature is NOT a user-friendly thing for most people. So, it’s vital that any company building a BI tool consider UX as a priority, because without user buy-in the system will not gain traction and provide the desired results.

6) Missing multi-carrier support

Most companies are working with more than one carrier, with many using a dozen or more. At the same time, each carrier has its own ways of making data available to customers. This makes the process of pulling data different for each. If you build a model based on one carrier, you may find yourself painted in a corner if you add or switch carriers. Excluding some carriers because their data cannot be accessed has obvious detriments to what a shipper is trying to accomplish with BI.

7) Lack of defined roles and security

The way users use BI can also be wildly different. Finance, sales, customer service, and your logistics operations will each have their own interest in what BI can offer. There may also be reasons not every user should see everything available in the data platform. So, it’s important to build in the ability to define and restrict who sees what.

8) Overlooking the journey ahead: What comes next?

Your business is evolving, and what it needs from its data in the future will no doubt look very different at some point. Building a static platform that works for today probably will NOT work for what the business needs down the road. Failing to think about where your business is going and having the flexibility to adapt your BI solution to keep up can be a costly mistake.

TransImpact’ s Parcel Spend Intelligence solution is designed for small parcel shippers and built on a proper data foundation, made by a company that is an expert in creating data models. We believe BI is a journey. Let us help you started. You can read more here.

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