The 7 Biggest Pain Points of Adopting Supply Chain Analytics (and How to Solve Them)

If you’re using the traditional methods of supply chain execution, you’ve likely been feeling increased pressure over the past several years—a kind of tightening noose, as your competitors adopt more nuanced, tech-driven strategies, and your customers begin to expect more from you as a company. That’s not even including the increasing global nature of the supply chain, volatile fuel costs, and the looming threats of outsourcing and automation.

Supply chain analytics systems, when integrated properly, provide much of the answers. If you’re crunching the numbers quickly and effectively, you’ll be able to diagnose issues faster, identify weak points and improve them, calculate your profitability and returns, and even provide more transparency to your partners and customers.

The problem is, integrating a new supply chain analytics system can be complicated; not only is it challenging to initiate, but there are also dozens of things that could potentially go wrong. But if you’re serious about optimizing your supply chain, you’ll need to learn to recognize those pain points—and learn how to overcome them.

The Pain Points of Supply Chain Analytics

These are some of the biggest challenges supply chain managers face when attempting to integrate an analytics system:

1. Overcoming complacency. The first problem is a notoriously human one: complacency. If your upper managers are used to relying on traditional spreadsheets to track orders and manage your data, they may feel perfectly complacent, and unwilling to make the investment or the transition to a new, more technologically nuanced system. Your best method of persuasion will be based in long-term optimization; you need to convince these people that you need to build the business around what will work in five years, not what worked five years ago.
2. Pulling data from multiple sources. One of the biggest challenges as reported by supply chain managers is trying to integrate data from multiple sources. The average link in the supply chain has multiple partners and sources to deal with, and probably already relies on multiple data-related systems. Trying to stitch those together without errors can be tough, but with an open-ended or customizable platform, you should be able to make integration much easier.
3. Dealing with data quality. You’ll also have to deal with data quality—a common issue in any analytics system, but if you’re new to data analytics, it can be overwhelming. The first step is committing to a cohesive, consistent process, and enforcing that process no matter who is using the system. Then, an occasional cleanup to get rid of duplicate records, outdated records, and other faulty points of data is warranted.
4. Finding the budget. Modern analytics for supply chains are big, complex systems, capable of more processes and greater volume than ever before—but that also comes with a cost. If you’re not used to paying a monthly subscription for a data analytics platform, this can interfere with your budget somewhat significantly. Overall, analytics platforms tend to save you more money than they cost, but you have to bear that in mind when making your decision (and many managers don’t).
5. Facilitating training. Once you’ve bought and integrated a system, you have to make sure your employees are using it—and using it correctly. In an ideal world, that means launching a small training program, ensuring each employee knows how to use the system. But even in that ideal world, that takes time.
6. Using the system consistently. Over time, employees tend to get lazy or branch out with their own preferences for things like data entry or analysis. That’s why it’s vital to have some central documentation—like a standard operating procedure (SOP)—that explains all the right formatting choices, entry methods, and analytics approaches for all your employees.
7. Not knowing the right questions to ask. Having a supply chain analytics system in place will provide you with limitless data about your business’s performance—but there is such a thing as too much data. Your analytics will provide virtually any answer you want, but that puts the pressure on you to ask the right questions.

Starting From Scratch

If you don’t have a business intelligence or analytics strategy in place, this is all going to seem overwhelming to you. But the good news is, you don’t need to install and start using a new supply chain analytics system overnight; you need to start with a high-level analytics strategy, then hire the right talent to help you smooth the transition to a more integrated approach. The hard part will be comparing solutions providers, since there are so many to choose from, but once you have an intuitive system in place, everything else will come together.