The impact of data integration on shipment forecasting and business intelligence

Mar 7, 2022

We live in an increasingly interconnected world. With the advent of smartphones, humanity has the power to access nearly anything they could imagine, merely with a few taps of its collective finger. However, manufacturing, transportation, and logistics have long since lagged in this technological renaissance; until very recently, that is.

Today’s smart-businesses leverage more than just the newest technology, though that certainly plays a role. What truly defines a smart business is how it collects and uses data. Data integration and business intelligence have become hot topics over the past few years, and their overall impact has been incredible. Companies employing data-fueled tactics are becoming leaner, smarter, and more efficient.


Why is data integration important?

In a big-picture sense, it’s relatively easy to understand how a business operates. Goods are made, sold, and distributed for a profit. However, within those steps is a macrocosm of information and opportunities. Every single action, from material procurement to the last mile delivery, has the potential to be automated, streamlined, and completely optimized. And so, taken from a granular view, business operations can be analyzed within specific processes, and inefficiencies become highlighted and solvable.

The amount of information generated by the supply chain is vast to the point of becoming incomprehensible. The data integration process separates the desired data relevant to the organization from the useless “noise” and then tracks and monitors the desired data. The data is summarized into digestible visuals such as charts and graphs and can help uncover patterns and generate insights within their operations.


How can data be used?

While the answer to this question can vary depending on the data collected, a few constants apply to nearly all data sets. The short answer is, analyzing data can help a business make smarter, quicker, and more efficient decisions. More specifically, it can help in the following ways.

  • Reduce operating costs and improve margins: Controlling costs is always a priority for any business. Given the current state of the global supply chain and freight costs, every step towards improvement could pay dividends. Real-time data collection creates a higher level of visibility and actionable insights into the supply chain.
  • Identify and mitigate risks: Risk assessment is a vital process for success. The longer the supply chain, the more moving parts and the greater the risks for disruptions, delays, rate hikes, and more. By incorporating data, these risks can be identified and even predicted in the future by analyzing trends and patterns within the supply chain.
  • Improve shipment forecasting and planning: Analysis of customer data can help an organization to better predict future levels of demand. This insight helps a business understand what their customer will need after the initial order has been placed. Additionally, trends can be monitored to improve stock levels of various items.
  • Running a lean operation: Lean logistics, when carefully managed, reduces cost, risk, and overall waste. However, running too lean can create as many problems as having too much inventory. Data can be used to monitor warehouses, responses from logistics partners, and customer requests for information or solutions.


How data integration improves business intelligence

Business intelligence defines a number of practices within an organization and how data is utilized and applied. First, it is the process employed to retrieve valuable information from raw aggregated data. Business intelligence also defines how that information is used in business decisions, predictive analysis, trend and pattern identification, and overall business management. Additionally, business intelligence fosters better collaboration with all partners throughout the supply chain.

An excellent example of business intelligence is benchmarking. Data can be used to provide benchmarks for both in-house performances and that of the competition, providing milestones for measuring improvements to efficiency. Alternatively, a market and sales analysis could forecast a potential surge in demand, allowing a company to communicate with manufacturing, warehousing, and logistics partners to better anticipate the increased demand.


How to add data integration into your operations

It’s one thing to know that data is a powerful tool, and it’s another thing entirely to know how to go about collecting it and, more challenging still, interpreting it. There are various ways to go about bringing data integration into your operations. You could work with a third-party logistics (3PL) service provider who can handle data collection, processing, and analysis. While the downside is that added features typically incur additional costs, the hands-off approach is appealing to some organizations.

Alternatively, you can bring the process in-house using a software platform with data collection capabilities. Because the supply chain has become so incredibly complicated, most software has been developed to optimize supply chain performance. These products can typically cover many features, from monitoring sales to providing near real-time data about the supply chain and freight movements.

However, it is important to note that not all software is created equally. Optimally, the software will mesh with current ERP and legacy systems rather than replace them. The ideal solution would be a seamless integration that overlays current systems and allows for data sharing across all platforms.