The Power of Data in Supply Chain

Feb 28, 2021 | Supply Chain

“In God we trust, all others bring data”, W. Edwards Deming, statistician, professor, author, lecturer, and consultant.

“The goal is to turn data into information, and information into insight”, Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co.

“If we have data, let’s look at data. If all we have are opinions, let’s go with mine”, Jim Barksdale, former Netscape CEO.

All these quotes show the importance and power of data. As a leader, you are probably thinking how to use this “data power” for greater profitability, cost reduction, revenue increase.

Data in Supply Chain

Think of supply chain with a holistic approach that is comprised of procurement, operations, and logistics – transportation and warehousing. This means different activities – as the SCOR model indicates:

  • Plan
  • Source
  • Make
  • Delivery
  • Return

If powered with the right data, six key links in your supply can deliver a higher EBITDA for your business or organization:

  • Improve customer service
  • Decrease inventory
  • Optimize production
  • Be agile
  • Reduce costs
  • Manage materials

To accomplish this in your P&L, you need to start identifying what data to use and the right data sources throughout end-to-end supply chain. Today there is data everywhere, as the cost of data storage is low. This data abundance could be an issue.

The key is to focus on what data you need and then identify from where you will obtain it. A real-life example was with a company that was using a query built in the system some time ago. Such a query was pulling information from outdated sources.

Data can give you an edge if managed well. So, where do you start?


Lean Six Sigma – DMAIC Approach

You probably have heard about lean six sigma. The DMAIC approach within lean six sigma, is a structured approach with specific steps:

  • Define
  • Measure
  • Analyze
  • Improve
  • Control



Everything starts with defining your problem in statistical terms. If your problem is late deliveries; it is not enough to say that you need to reduce late deliveries. If you just have one more on time delivery you would be accomplishing your goal.

But, is that your true goal? The meaning would be different if you state your problem as: reduce late deliveries from 20% to 10% while maintaining the same shipping cost.

Now you have a challenge! Your problem is specific, of a defined scope. It has a point A from where you start to reach point B. You also have a constraint. Any actions you take or any decisions you make cannot increase your shipping cost.

I wish I could have no restrictions on my budget, as you probably would too.

That is the Define phase.



Moving into the Measure phase, you need to establish your measurement system. Such a measurement system needs to have reproducibility and replicability.

Reproducibility means that no matter who measures late deliveries, everyone will get the same number or percentage. There is no room for subjectivity.

Replicability means that if tomorrow you will measure the late deliveries of past months, you will still get the same results as those in the past.

For example, let’s take January 2nd. On this day, you measured late deliveries and they represented 10% over the total. Two months later, you measured the late deliveries on January 2nd. If your measurement system has reproducibility, you will get 10% again.

Before starting a project, you need to define and measure your baseline with a system that has reproducibility and replicability. This is 20% in the example.



In this phase, you dive deep into the data. Initially thinking about all the factors that can have an effect on late deliveries. A factor could be the weather that has an effect on shipping; another factor could be limited capacity at your plant; another factor could be that production is aware of the customer order late in the process; and the list can continue.

Spend your time in understanding what data tells you, in looking at potential relationships among the factors. There are different tools to help you in this analysis. Regardless of the toolkit you use, you will need to identify what data you need and the source.

From the many factors you have begun with, at the end of this phase you will have the key 3, 4, or 5 factors that have the highest impact on the problem that you are solving. In this case, the top factors or elements with the highest impact on late deliveries.

Now you can see why this reduction in the number of factors is called funneling effect.



This is the fun part. Once you have identified the top factors to explain your problem, you will focus your efforts on those factors only. To know if your solutions have generated the expected outcomes, there is no other way than to measure.

You have your baseline. Now, it is time to measure again by applying the same measurement system that meets the reproducibility and replicability requirements.



After all your hard work, you want the improvements to be sustained over time. This is not a flavor of the month. This is how the continuous improvement is built. You don’t need to start from zero every time.

In this phase you ensure that after three months, six months, a year, you name it, when you measure you still see the improvements implemented.



Of course, technology can help you! But it needs to be built on solid data and process to make its magic. In the Data and Tech in Supply Chain video series of my podcast, Adventures in Supply Chain, you can hear from amazing guests how data and technology can help your business scale your operations.



There are countless metrics that you can track. Too many metrics to track can have an undesirable effect because at the end, you may not be able to track nor manage them. Having focus is fundamental.

Below you will find some critical metrics.

  • Perfect Order – this means on time, in full, no errors at all. It is a very highly demanding metric. However, it gives you a good indication about the performance of your supply chain and the opportunities for improvement.
  •  Cash to Cash Time – this measures the days from the time when your company pays your suppliers until your company receives payment from its customers. It has a component on inventory, on the days on payables, and on the days on receivables. Pay close attention to this metric, as research indicates that it is directly linked to your profitability.
  •  Supply Chain Cycle Time – this measures how long it would take to complete a customer’s order if you do not have inventory. This metric is the longest possible lead time for each phase of your supply chain.
  •  Fill rate – also known as customer satisfaction or service level. This metric measures the amount of the customer demand that you can meet with your inventory on hand, without backorders or lost sales. If there are lost sales, there are opportunities, so it is critical to track this metric.
  •  Inventory Turnover – this metric measures the number of times that your inventory is sold in a specific timeframe, usually in a year. It is indicative of the efficiency of your supply chain.

 To define the baseline of each of these metrics, you need to be clear on the definition, calculation, and sources of data.

A data-powered end-to-end supply chain is the most powerful strategy to boost your profitability through revenue increase and cost savings. We’d love to be part of your company’s growth. Please feel free to reach out.



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