How Supply Chain Executives are Spending Money on Modern Technology - SLMT
How Supply Chain Executives are Spending Money on Modern Technology
October 27th, 2022 by

On their path to digitalization, everyone is at a different stage. The majority of businesses have already begun using digital techniques for one or more operational activities. However, the vast majority of businesses still track shipments using manual documentation.

 

For their shipment tracking procedures, about 70% of fleet management and supply chain leaders still use paper driver logs, workbooks, and spreadsheets. But manual procedures are outmoded and tiresome, as we all know. They can obstruct an operation’s visibility and future growth because they are prone to human error. Pursuing any one of the best Shipping Management Courses in Kochi can help to acquire more knowledge about the industry.

 

The biggest issues in the sector are prompt service, costs, staffing challenges, and workflow automation. A more intelligent supply chain and improved visibility can help with many of these problems.

For many businesses, transitioning to a data-driven culture has been a long process for a variety of reasons. Enabling data-driven decision-making and collecting all the disparate sources that data is dispersed throughout, such as various systems and businesses, are two of the major problems.

Analytics adds critical context once the data is available so that it can be applicable to the decision-making process. However, it is acknowledged that the biggest area for improvement in supply chain visibility is predictive analytics. Joining for Logistics and Supply Chain Management Courses in Logistics Colleges in Ernakulam, like SLMT can help to progress in this industry.

 

Creating a supply chain that is more prognostic

 

There are many stepping stones that can boost the efficiency, accuracy, and cost savings of your business even though it may seem like a long way between purely manual procedures and prediction. Predictive supply chains seemed unattainable a few years ago because the data wasn’t readily available. Supply chain leaders are better positioned to begin creating more predicative supply chains now that we have a wealth of easily accessible information at our disposal. What therefore prevents the general adoption of technology?

Finding the correct partners or suppliers and knowing where to start are the main obstacles to technology implementation. To put it another way, there is a lot of hesitation and confusion over digitalization. Here are five crucial aspects to take into account as you embark on your digitalization journey to assist close this knowledge gap.

  1. Use a strategy and approach that are data-driven.

You must begin developing a data-driven strategy and approach before you can truly embrace a predictive supply chain. A truthful talent evaluation is also necessary. Do you have the data scientists and analysts with the necessary skills to evaluate particular data sets?

  1. Identify the gaps and silos in your data.

Be careful to be informed of everything. Understanding your processes and the data you have or do not have access to is crucial when it comes to data. By integrating and then normalising these data sets from all the various stakeholders, you can connect your assets. Anywhere is there a lack of transparency? Do you have usable data and are there any data gaps?

  1. Examine the larger tech stack:

There are software programmes and off-the-shelf solutions that fit seamlessly into your bigger IT stack. There are ready-made solutions that can provide the plug-and-play solutions you’re searching for, regardless of the problem areas, which may include visibility, ETA accuracy, driver onboarding and safety, warehouse optimization, and middle and last-mile efficiency.

  1. Implementing tests

The part of the business you’re seeking to enhance will have a big impact on how you test a new solution. The testing phase might resemble this if you oversee first-, middle-, or last-mile deliveries for your business:

To identify areas for optimization, model concepts (tours, spending, etc.) against the actual completed tours using sample data.

Converting job data from an order management system should be tested to ensure that all pertinent information is properly included.

  1. Application

Following testing, the implementation procedure for the identical fleet scenario would be as follows:

Step No.1. Define the locations of the fleet and the depot.

Step No. 2. Registering drivers and dispatchers for user-friendly tools is the second step (eg, app, navigation)

Step No.3. Import job information

Step No.4. Optimize and send out tours

Step No.5. Complete tours using the driver app’s advice and delivery confirmation.

Step No.6. Review completed tours using the analytics dashboard in step six.


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