How you can build a data-driven supply chain – from Zencargo’s VP of Data

Jun 17, 2022

What gets measured, gets managed. 

That’s particularly true within the supply chain, and adopting a data-driven approach can help you move the right goods to the right place, for lower prices and lower environmental impact.

But how can you get started? We sat down with Peter Tomlinson, Zencargo’s VP of Data, to learn everything you need to know about data-driven supply chains.

First things first: what is a data-driven supply chain?

A data-driven supply chain is one where the core decisions made are based upon measurable data, rather than relying solely on intuition. 

To get there, you need to have a single, fully integrated view of what’s happening across your supply chain. All the manufacturers, agents, carriers, hauliers, internal teams: they all need to be feeding into one system. 

With that foundation in place, you can then use the real-time, holistic information you have to inform your decisions and the steps you need to take.

Adopting a data-driven supply chain strategy might look like:

  • Benchmarking the performance of your suppliers according to measurable KPIs (response time, accuracy of estimated cargo ready date)
  • Setting a hypothesis for supply chain improvement, and measuring results before and after any intervention to judge its success
  • Monitoring KPIs in real-time, and nipping issues in the bud once your measurements cross a certain threshold, rather than discovering problems after they’ve happened

What are the benefits of a data-driven supply chain?

More internal alignment

One of the most important benefits is simply that a data-driven approach to supply chain makes communicating with other teams far simpler. 

Instead of the supply chain team, the finance team and the merchandising team all making decisions based on their own interpretation of what’s going on; everyone can use the same facts. This avoids a ‘families at war’ environment, or one where decisions are made based on whoever shouts loudest.

Supply chain visibility

Without capturing what’s happening and using that to make your decisions, you really are operating blind. How can you know what’s really happening, if you don’t have the evidence?’

Taking a data-driven approach to supply chain management is crucial for making the right moves, when you are not realistically going to be able to go on ‘gut feel’, especially if your company, product catalogues or supplier base grows.

Easier risk management

On top of that, when the market is as volatile as it is, supply chain leaders are often asked to make hard decisions. Here, being data driven is a non-negotiable part of your risk management. 

Why? Because being able to quantify the impact of each choice helps you (and your team) feel far more confident in the paths you choose to take. If you have core, comparable measurements across your supply chain, it’s easier to compare options when you are considering making a change. 

In fact, once you have a clear digital overview of your supply chain, you can use it to stress-test your current set-up. What would happen if Shanghai went back into full lockdown? How would that affect our manufacturers and logistics? What can we do to counter this risk?

This is of course possible to do in an analogue way, but access to the data makes your calculations far easier to do frequently, meaning you can stay on top of your risk better and intervene sooner.

Operational excellence

Finally, developing a data-driven supply chain approach can help you solve many of the day-to-day issues that many teams face.

For example, a Zencargo survey of 200 senior supply chain professionals revealed that:

  • 53% struggle with tracking supplier performance
  • 40% have no live updates on where their goods are
  • 51% struggle to explain context to internal stakeholders

Making your data accessible so you can analyse and investigate what’s happening across your supply chain means you can easily start to solve these problems.

What’s more, the number of businesses struggling with issues that could be solved with data presents a big opportunity. 

If you can truly succeed at accessing supply chain data and using the insights from it to make informed decisions, you can turn your supply chain from purely a cost centre into a competitive advantage for your business.

Survey of 200 senior supply chain professionals

How are other businesses handling their supply chain data?

Research: The Supply Chain Data Crisis

How can your freight forwarder help you become more data-driven?

Every single day, a vast quantity of important information passes through the hands of your freight forwarder. 

That’s information like:

  • How many of each item leaves (or is due to leave) each factory
  • When each shipment is due to arrive at the distribution centre
  • The average time it has taken for goods to move between any two points in the chain

This verified, high quality information represents a gold-plated dataset for you to draw from, helping you answer questions, investigate problems and find solutions.

While traditional freight forwarders have not made the most of the wealth of supply chain data they are sitting on, digital freight forwarders like Zencargo not only have access to that information, they have the tools to do something with it.

What are the common problems people face when trying to become more data driven?

Not even trying.

The most common problem here is simply not even looking for data to help you make your decisions, or assuming that the data isn’t there.

That can happen when the people who are looking at the data and the people who are making the decisions are not the same people. 

If leadership in a business are passive receivers of data, rather than being ‘in the data’ themselves, it can be very hard for them to really understand what’s there.

Using data to support your plans, not question them.

The other big problem is confirmation bias. People just look through the numbers to support their initial hypothesis, instead of being curious about what’s actually happening.

I spent several years working in digital marketing with a terrible data culture; we all knew our job was to make sure that the Chief Marketing Officer got the numbers they wanted to support the type of advertising that they wanted to do. It wasn’t about challenging their assumptions. 

When the outlook is to look for data, which supports the prejudices you are walking in with, then it’s worse than pointless. It can actually be quite damaging.

Lack of engagement from the top of the organisation.

Your company or your team’s data culture comes straight from the top: how data literate and data engaged are your senior leadership team?

If your data practitioners or anyone that’s involved with data is even at one removed from the decision making aspect of the business, then it’s a struggle to build a culture that rewards following the numbers. 

Plus, if data isn’t easily accessible, it’s very easy for busy people to find someone else to dig through it for them; it’s hard to justify the time otherwise. But if you can get that level of enablement at the senior leadership level, then it all flows from there.

So how can you start to build a data-driven supply chain? 

Pull your data together.

Most organisations are sitting on piles and piles of data that tend to be in little operational silos. You’ve got one team over here doing a load of stuff with Google Sheets. Another team might have their own little database; another team brought in a third-party solution five years ago. 

Once you’ve found out where that data is, decide whether you want to integrate it all, just some of it, or largely leave it where it is. For example, it might be that you just take the relevant bits from your different sources and merge them together for reporting, but otherwise keep things as they are. 

Anticipate that you might face some cultural challenges as you collect your data. Those different teams may not necessarily want to relinquish control of that data (as they perceive it). So it all has to be easily accessible to all teams, and the benefit for them to cooperate has to be clear.

Add in the extra information you need.

Next up, it’s time to look outside the business, at the wider data landscape. 

What do you know is out there, but you haven’t got? How can you acquire that data through partnerships or purchasing additional feeds? What information, if you could figure out a way to get it, would make everyone’s lives much easier? How might you go about getting hold of that?

Building up this holistic picture does take time, and you don’t need to have everything figured out straight away. But having a wish list makes it easier to be purposeful about what else you add into your systems, and it also makes the limits of your model clearer. 

For example, if you don’t have weather data, you know that whatever insights you gather need to be taken with the knowledge that typhoon season in Asia could affect overall schedule reliability beyond the numbers you have in front of you.

Speak the same language.

Once you have the information you need, make sure everyone understands what each term means, and where exactly that data you have comes from.

For example, ‘landed cost’ may be a straightforward enough term for a supply chain team, but one that is underused or labelled differently by the merchandising team. When the meanings of core terminology are fragmented like this, it’s easy for assumptions to go unnoticed, but still cause plenty of alignment issues.

One way to solve this problem might be to compile a data glossary that captures the exact definition of each term you use. So when you refer to ‘cargo ready date’ or ‘lead time’, people can refer to the exact nuance of what that means and how it is captured.

When people are more confident in their understanding of the data, they are far better equipped to grapple with what the numbers in front of them actually mean, and to turn that into meaningful improvement within the supply chain – and that’s what being data-driven is all about.