August 29, 2022
Data Analytics for Logward Users
Data Analytics is a method or a way to understand information and derive actionable insights. Yet there is more to it than that because Data Analytics comes in different types and is adopted in different fields, with each presenting its own challenges and opportunities. This blog post explores what Data Analytics is in logistics and at Logward.
As far as supply chain goes, the process of shipping a container across the globe has barely changed over the last few decades. But what has evolved is the industry’s potential to capture all the data associated to it, in a “not so digital” way. Logistics data volume is significantly high because a multitude of stakeholders take part in moving cargo across the globe, with different players having different perspectives to various supply chain processes. Bringing it all together on a single dashboard is as much fun as much as it is a challenge, and this is one key element that drives Logward’s unique value proposition.
Below, we will cover different types of analytics that go into building such supply chain dashboards.
Different Types of Analytics for Logward Users
Descriptive Analytics gives customers a quick summarized look of what has been happening in day-to-day operations. The more data available, the more in-depth summarization can be done. For Logward customers, this means having an overview of their business to efficiently manage their dynamic and complex supply chains.
Some examples of insights that descriptive analytics can provide:
- Changes in shipment volumes based on the total shipments done by customers over a given time period
- Tracking accuracy from the location of in-progress shipments
- Operational movements at certain ports exposed by detention and demurrage charges incurred by customers
Along with being able to tell what happened, it is even more important to figure out why it happened. Diagnostic Analysis uncovers the “why”. To answer that, Logward diagnoses events that occurred and figures out the cause. Talking shipment tracking as an example:
- Where do most of shipments get stuck?
- What often disrupts customers’ supply chain?
- Were there delays in picking up empty containers?
- Were there delays in containers being loaded on to the vessels?
- Were shipments stuck on the inland container depots for too long?
Understanding which of these milestones impacts OTIF delivery is a crucial insight for consistent shipping, and this can be called a diagnosis of the situation.
Once the “what” and “why” are known, the following question is, “What will happen next?” Predictive Analysis answers that.
First, one must understand what can happen next. All data sets help to find patterns, correlations, and eventually statistical evidence that would lead to possible, probable, and/or definitive outcomes.
For example, Allocation Management is used to monitor how tenders are managed (the “what”). Poorly planned tenders and bookings (the “why”) can disrupt the supply chain, and thereby, force stakeholders to incur higher costs associated with freight forwarding (what will happen next). Such methodologies of analysing data empower shippers to prevent potential disruptions and extra costs.
Companies shipping large volumes often have complex supply chains with many logistical partners involved, and they must constantly check the volume of containers they plan during the year. Vessel capacity, carrier commitments, schedules, rates - all these factors play a significant role in helping customers with annual operations plans, thereby improving execution. Through Allocation Management and the Procurement Cloud, Logward enables customers to turn past performance and data into future success and improvements.
With predictive analytics, Logward customers plan and prepare container shipments in a timely manner knowing:
- How soon will they reach carrier capacity?
- Will there be a need to book containers on a vessel at spot quotes?
- Are they on track to meet the carrier commitment for the week/month/year?
- Are they going to incur a penalty for not consuming the agreed allocations?
And so on.
After having described, diagnosed, and predicted what can happen, actions, and solutions can be proposed. The predictions made in the previous section may or may not present a favorable outcome, but with that, shippers will be empowered further to choose what actions can/should be taken when it comes to continuing or changing the way their supply chain is behaving. For example:
- Should they plan their tenders better?
- Can they plan their bookings better?
- Can they get better rates?
- Which vessel/service shall be opted to reduce the lead times?
Analytics is a powerful medium for data to communicate with humankind. It is a by-product of shippers’ overall business. However, it can be utilised to a much higher potential when combined with the simplest of methodologies and/or processes. The next Blog post will go through the processes Logward has implemented to adhere to one or more of the methodologies of data analysis based on either the requirements from customers or additional insights from the team.