How supply chain leaders are investing in new technology

When it comes to digitization, everyone is at a different stage of their journey. Most companies have already started using digital methods for one or more tasks within their operations. However, most organizations still rely on manual documentation when tracking shipments.

In fact, new research commissioned by HERE Technologies and conducted by ABI Research found that nearly 70% of fleet and supply chain management leaders still rely on paper spreadsheets, worksheets, and driver logs as part of their operations. of your shipment tracking processes. But as we all know, manual processes are outdated and tedious. They are prone to human error and can hamper an operation’s visibility and potential growth.

Respondents cited speedy service (55%), costs (54%), staffing complexities (49%), and workflow automation (47%) as their top concerns. Many of these challenges can be addressed with better visibility and a smarter, more predictive supply chain.

“Shifting to a data-driven culture has been a slow process for many companies for a number of reasons. A couple of the biggest challenges are enabling data-driven decision making and aggregating all the separate sources that data is scattered across, like different systems. and companies,” said Bart Coppelmans, global director of industry solutions at HERE.

Once the data is available, the analysis provides crucial context so that it can be relevant to the decision-making process. However, the majority of respondents (61%) said that predictive analytics is the biggest gap they have in improving supply chain visibility.

“This is where HERE can help connect different stakeholders and data sets. Our core capabilities allow you to combine and aggregate disparate data sets and put them into context with value-added insights for your customers,” said Coppelmans. “Location data analytics puts your logistics operation data in context. We add real-world events, alert notifications, analytics, and machine learning models to make logistics and supply chain software more predictive.”

See also  VGI Health Technology Limited Receives Ethical Approval for US Clinical Study

Building a more predictive supply chain

While the distance between fully manual processes and being fully predictive may seem great, there are many steps along the way that can increase the efficiency, accuracy, and cost savings of your operation. Just a few years ago, predictive supply chains seemed out of reach because the data was not available. Now, with a lot of accessible information at their fingertips, supply chain leaders are better positioned to start building more predictive supply chains. So what stands in the way of widespread technology implementation?

According to HERE research, 31% of respondents said their biggest barrier to technology implementation was knowing where to start, and 39% said their biggest challenge was identifying the right partners or vendors. In other words, there is a lot of hesitation and confusion when it comes to digitization. To help fill this knowledge gap, here are five important factors to consider throughout your digitization journey.

1. Adopt a data-driven strategy and approach

Before you can fully embrace a predictive supply chain, you need to start implementing a data-driven strategy and approach. On top of that, an honest assessment of talent is required. Do you have the qualified data scientists and analysts to analyze specific data sets?

2. Identify your data gaps and silos

Make sure you have the complete image. When it comes to data, it’s important to understand what’s happening within your operations and what you do and don’t have access to. Connecting your assets integrates and then normalizes these data sets from all the different stakeholders. Is there a lack of transparency somewhere? Are there data gaps and is your data usable?

See also  Flow partners with SRC to power the Science and Technology Conference

3. Consider the largest technology stack:

There are out-of-the-box solutions and software that can be easily integrated into your larger technology stack. Whether your problem areas include visibility, ETA accuracy, driver onboarding and safety, warehouse optimization, and last mile and a half mile efficiency, there are out-of-the-box solutions that can be just the thing. out-of-the-box answers you are looking for.

4. Test Implementation

The testing process for a new solution will largely depend on the area of ​​the business you are trying to improve. If you or your company manage first, middle or last mile deliveries, the testing stage could look like this:

  • Use sample data to model concepts (drives, expenses, etc.) against actual drives completed to see potential for optimization
  • Test job data conversion from an order management system to ensure all necessary data is included correctly

5. Implementation

Using the same fleet scenario, after testing is complete, this is what the deployment process would look like:

  1. Step one: Define depot and fleet locations
  2. Second step: Register drivers and dispatchers for easy-to-use tools (eg, app, navigation)
  3. Step three: Import job data
  4. Step four: Optimize and dispatch routes
  5. Step five: Complete tours via guidance and delivery confirmation in the driver app
  6. Step Six: Review completed rides through the analytics dashboard

To see how logistics leaders are using location technology to build better software and predictive supply chains, visit

Leave a Comment