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Analytics Get You the Most for Your Logistics Dollars

When asked about their supply chain challenges, electronics companies list globalization, commoditization, rapid product obsolescence, and supply and demand volatility as ever-present factors. However, they also say pricing and logistics optimization are major impediments to supply chain optimization.

This sense of excessive logistics spending is corroborated in a 2016 survey by Deloitte and Material Handling, Inc. (MHI), a supply chain industry association. In the survey, supply chain respondents said they still needed to achieve lower pricing and more flexibility in shipping goods in modes that mixed a variety of packaging and shipping options; and  they still did not have the kind of supply chain visibility that they wanted for themselves, their shippers, their logistics providers and their customers.

Unfortunately, concerns like these are not easy to solve in today’s fast-moving supply chain environments.

For instance, when it comes to forecasting transportation spend, you could look at a variety of factors: spending in the past year; spending trends tracked over several years; product shipping forecasts for the coming year; and so forth. Unfortunately, technology limits in present systems might not give you the visibility around which transportation lanes in each area are most effective and why. They won’t let you dig into new management approaches to these lanes, such as mixing modes or altering shipment from premium to standard delivery service, in ways that might produce cost savings and transportation efficiencies. As a result, you are unable to optimize your transportation mode, shipment, and route choices and you overspend. 

Nevertheless, there are companies that persist by making a gallant effort to get to the bottom of this murky spend and logistics picture. They commit employees to reconciling invoices and other logistics documents—which can come in many different forms, terms, currencies, and languages from suppliers around the world. The manual reconciliation process is time-consuming. It includes correcting errors in logistics documentation, manually revising and confirming true costs, and then finally pulling everything together so you can compare one vendor to another to see how you are really spending your logistics dollars and what the impact is on your profitability.

All are all daunting tasks, and many companies eventually give up on them.

But what has changed is that there are now cloud-based tools available that can assist you with your logistics optimization and spend management. They come in the form of predictive analytics that enable you to model future supply chain logistics and cost scenarios with the help of what-if predictive modeling of your supply chain.

Here’s how the process works. The first step is to normalize all incoming data from your logistics suppliers so you can compare apples to apples in your what-if scenario modeling, which the software does for you.

Don Baptiste, CEO of Trax Technologies, a predictive analytics solutions provider for the supply chain, explains how this data normalization works:

You might have an originating shipping point or a destination for a shipment that is labeled ‘PHX,’ but is it the Phoenix airport, or a distribution point somewhere in the Phoenix metro area? The software looks up the zip codes to ensure that sites are correctly identified. Or, you could see ‘Munchen’ and ‘Munich’ on logistics documentation. The software can normalize both expressions into a single occurrence of “Munich,” which helps enable a logistics analyst to compare apples to apples.

The second step is to describe the various what-if supply chain logistics spend modeling scenarios that you want predictive analytics to analyze for you.

To do this, you develop what-if queries against your supply chain data like:

  • Can I move some of my shipping volume from premium service priority next day shipping to standard overnight or second day shipping to save money and still meet delivery timetables?
  • Or, am I using the least cost carriers on my most active shipping lanes?
  • Or, how will my supply chain logistics perform if product demand exceeds expectations next year? 

The third step is to put the analytics to work by taking the insights you have received from your what-if scenarios to fine-tune logistics operations and optimize spend. Trax says that its customers are reporting 2-10% cost reductions by shifting their logistics service levels; 5 to 15% cost reductions by consolidating freight; and 1 to 7% cost reductions by eliminating or reducing discretionary charges by using what-if modeling 

Will what-if supply chain modeling solve all logistics spend issues?

Probably not. There are always issues that it is difficult to model and even when you use what-if supply chain logistics spend analyses, they are only as good as the models that you develop for the software to analyze.

However, executives like Baptiste point out that when you use supply chain predictive analytics, you are also gaining the benefit of statistical science, mathematical algorithms, data modeling, machine learning and artificial intelligence gleaned from supply chain experts and data scientists. These can be added to the talents of your own staff.

You might not get to the bottom of every supply chain issue, but you will move closer to 360-degree supply chain visibility and the ability to proactively intercede with your logistics providers to improve both spend and performance.

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