Importance of Data Accuracy and Quality in Transportation Spend Management

Data analytics plays a significant role in supply chain management, and its importance was brought to the forefront during the COVID-19 pandemic. Remote working conditions, global shutdowns, monetary limitations, and stuck shipments meant that supply chain management had to evolve years in a matter of months. At the heart of that evolution was data analytics.

With accurate and complete data, you possess greater visibility into a supply chain's financial and operational aspects. It’s only with this end-to-end insight of your Transportation Spend Management can you optimize processes and costs to become an industry leader.

Hazards of Inaccurate or Incomplete Data 

Adopting data analytics for your supply chain does come with risks if you have inaccurate or incomplete data. Some of these hazards are:

• More incorrect/incomplete data—Relying on inaccurate or incomplete data for decision-making is a slippery slope, as those decisions can create more incorrect or incomplete data sets. This can lead to a vicious cycle in which bad data breeds more bad data and creates limits to tasks like projects, reports, analyses, initiatives, and so on.
• Poor decision-making—Inadequate data can lead to dire mistakes. For example, miscalculating accruals or accessorials based on wrong data could lead to significant financial losses. Low-quality data increases your risks and errors, and leads to reduced trust and confidence in business decisions.
• Increased costs—Trying to course correct after making a decision based on incorrect data is costly. Sometimes a mistake isn’t found until it’s too late, which costs you even more money to try to rectify. Or, you waste valuable resources that spend their time and productivity chasing root causes—when the root cause is actually bad data.
• Missed opportunities—You can’t take advantage of an opportunity if you can't see it. Inadequate data delivers poor visibility into real-time opportunities. Even if you do see an opportunity, bad data can mistakenly lead you to believe the company isn’t in a position, financially or otherwise, to go after that opportunity.
• Inaccurate forecasting—When you have incorrect or incomplete data, you lose the necessary visibility to data that can help with forecasting precision. Bad forecasts cause improper resourcing, over- or underspending, poor use of resources, and more.
• Poor customer experience and damaged brand—Errors based on inaccurate data, such as estimating shipping costs, delivery times, or damage rates, can hurt your brand and lead to lost clients, trouble attracting new clients, and a dwindling market share.

Supply Chain Data Accuracy 

Incomplete data can be accurate, but it’s vital to remember that accurate data doesn't guarantee that you’re seeing the whole picture. For example, you may have all the data for proper shipment weights, origin and destination locations, accessorial charges, and so on, but if the data is inaccurate, it’s essentially useless. Along a similar note, you could have accurate weight and accessorial charges, but that doesn’t mean you have the entire picture—you may be missing vital location or other information.

Enhancing data analytics is one of the top 10 priorities of chief supply chain offers. Companies that want to elevate their data quality rely on specialist partners, such as Trax, to do so. Trax completes, centralizes, filters, and enhances your data sets to give you more visibility into your supply chain. We work with carriers on improving data accuracy and quality through the optimization of Transportation Spend Management practices, such as freight audit, Carrier Management, rate management, claims management, and more.

Trax’s Transportation Spend Management Maturity Model guides you through optimizing your supply chain's financial and operational processes via data-driven analytics. Our tools provide you with digestible data—and promote strategic use of KPIs and variance metrics—in an easy-to-use platform so you can make data-informed decisions. Companies that mature through the model have a steady influx of clean, relevant, accurate, and high-quality data to boost business intelligence and make data-driven decisions.

Data Completeness 

In order to optimize your data management, you also need complete data, which enables the automation of processes and business rules, as well as drives healthy analytics and business decisions. When you have a gap in your data, it can hinder your progress and decision-making, so it’s imperative that your data is complete. For example, you may have correct shipment weights and accessorial charges information, but without having the full, complete data, it carries little meaning. The pandemic pushed every industry to its limits and accelerated the adoption of data analytics, as 91% of supply chain professionals plan to invest in data analytics.

By channel

Data completeness involves combining source information or mapping other information to create derived values. Here’s an example. In retail, having complete visibility into the channels of deliveries (distribution chain to store to customer) and the return cycle is imperative for controlling costs and measuring performance against KPIs. The channel of delivery data isn’t in the carrier's billing or source information, such as a Warehouse Management System. This data needs to be augmented, or sourced, to create a complete picture so you can make impactful decisions regarding channel of delivery. This augmentation lets you see KPIs by channel rather than just a lump sum. You know how much you spend via each channel and can determine derivations, including returns, through channel data alignment.

Looking by channel or lane is the real, hidden value that Trax can produce from the data we mine in our offerings, such as Freight Audit Services. It’s within that goldmine that cost reductions are found—savings that most of your competition doesn’t know exists because they have incomplete data.

By SKU

All industries struggle with inbound and outbound SKU-level data. Having SKU-level data lets you break down the total cost of transportation by product, giving you greater visibility and control over your transportation spend. When you know the exact cost per unit and the sales forecast on the SKU level, you can better forecast the total cost, including transportation. Optimizing your data management process makes it possible to produce comprehensive, accurate budgeting.

For example, in the healthcare and life science industries, complete data sets are vital for cold chain shipments. Knowing what was shipped, origin and destination, temperature requirements, if the shipment was delivered on time, and more, are crucial to successful transportation. Damages, losses, delays, and expires are excruciatingly harmful when it comes to time- or temperature-sensitive shipments. Complete and accurate carrier data, which can be gathered through optimized carrier management, scorecards, and other tools, helps to mitigate risks, improves billing-to-payment cycle times, and fosters trust between you, your carriers, and your third-party audit partner.

By carbon emissions

The environment's well-being is a growing concern for companies, especially the tech and retail industries. Calculating carbon emissions is a fool's errand without complete data sets. Complete data helps you to better plan, forecast, and consolidate shipments, which benefits both the environment and your bottom line by cutting fuel surcharges, improving your brand’s sustainability, and more.

By zone skipping and accessorials 

Zone skipping and accessorial mitigation, some of the most challenging aspects of supply chain management, can't be mastered without comprehensive data. Having that data allows you to make better decisions, forecast more thoroughly, and budget more accurately.

The ultimate route to mastering data management is optimizing Transportation Spend Management, which Trax helps you do. We optimize your supply chain's operational and financial processes built upon high-quality data management. By journeying through our maturity model, your data management process evolves so you can make strategic decisions that set you apart from the competition to be a leader in the market.

Data Analytics at the Core of Robust Supply Chains 

Analytics play a major role in every industry worldwide, and even more so since the pandemic. Data management within supply chains may be complex due to all the variables and processes, but partners like Trax help to streamline your data to be high quality, accurate, and complete. Optimizing your Transportation Spend Management makes it possible to deliver data-based decisions that grow your business. To know more about optimizing your data management, contact Trax today.