One of our main competitors is a notebook

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sadiksojib35
Posts: 41
Joined: Thu Jan 02, 2025 7:13 am

One of our main competitors is a notebook

Post by sadiksojib35 »

Another area for automation is bidding with a contractor-carrier. To do this, you need to be constantly aware of the situation on the logistics market, promptly offering the contractor to revise tariffs and reasonably bargaining for a fair price. This is our field of activity - we help track the current price dynamics. Our program processes data on real transactions from our own and partner sites (this is more than 150 thousand transactions monthly) and calculates prices for a total of 15 million directions. The algorithm can also provide a price forecast for a period of up to 12 months, taking into account seasonality, inflation, fuel price dynamics and other factors.

And finally, another way to use resources efficiently and increase profits is to load up the company's own fleet of vehicles, which is idle during off-peak periods, at the expense of third-party clients. As a rule, companies singapore telegram organize this process with the help of logisticians on staff, who manually monitor potential clients' sites, search for flights and simultaneously select suitable transport for themselves. It is logical to assume that technological services that are on the market can do this cheaper and more efficiently than people.

The operating principle is as follows: based on the specified parameters (time and place of loading and unloading, type of vehicle, price range), the algorithm automatically selects suitable lots on partner trading platforms, buys them and transfers them to the client’s ERP system.



Risks of incorrect logistics budget planning
As mentioned earlier, logistics accounts for a significant share of the cost structure of most companies, so an error in forecasting shipping prices can lead to an imbalance in the entire budget.

A case in point: retail during the peak pre-New Year period. For some companies, the volume of shipments during this season can increase 3-4 times, and the need for transport is at its maximum.

Over the past holidays, we have repeatedly encountered such cases in the market: companies budgeted for a seasonal increase in logistics rates by 20%, based on the simplest linear model. Companies reasoned like this: last year and the year before it was on average about 20%, so it will be the same this year. In practice, due to the fact that the market changed and became more volatile, the jump in rates was much greater: 40-60% for various carriers. The result was an excess of budget and disruption of logistics chains, especially critical for seasonal goods. Business was forced to take urgent, non-systemic measures to reduce costs - to the detriment of quality.

Large companies use not only spot (i.e. one-time) biddings, but also tenders as a tool for finding a contractor. Here, the cost of an error can be even greater. Calculating a tender is a labor-intensive procedure, which in most cases is done manually. At this stage, significant time costs and calculation errors are possible, which result in losses as a result of the tender.

The impact of an error can be not only direct - on costs, but also in the long term - meaning damage to the business associated with the outflow of the customer base. Changing the budget, revising prices for goods, finding new suppliers - all this takes time, during which the client can leave. As a result, an attempt to save on logistics can cost the company even more.

In conclusion, I would like to note that in today's situation, the ability to predict tariffs even a month in advance is becoming a key competency of companies engaged in transportation. This requires constant analysis and competent forecasting of tariffs: either within the company or with the involvement of third-party contractors and special services. And the key to forecast accuracy is big data and algorithms.

The more information and the more accurate it is, the more relevant factors are taken into account and incorporated into the model, the more reliable the forecast will be - and the more effective the optimization of logistics chains in the company.
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