Watch the recording, read the webinar slides and discover the Q&A resources below.
Q&A session summary
1. The value for chartering teams was discussed in the webinar, but could you explain what the value is for other departments such as operations or finance?
There is a downstream value for the other parties because, in chartering, if you estimate more accurately, it will mean that your budgets are also more accurate. Cash flow predictions are going to be much more precise as CFOs can see how much is coming under demurrage and what the delay is on that compared to freight. For operators, the value starts from the terms and estimates – the better terms and laytime chartering teams can get, the more room this gives for operations to optimise port calls.
2. If we're not using IMOS, what are the implications? Can we apply changes back to non-IMOS VMS?
We are in the process of integrating with Softmar. We have the integration ready on our side so we can expose, in theory, to any voyage management system. It’s really a matter of customers coming to us, and then we’ll look at doing it.
3. What does onboarding typically look like?
Overall, it takes less than a week to complete the onboarding process. It usually takes about a day for us to do the entire set-up based on the parameters the customer provides. The IMOS integration takes another day which involves data-mapping. We then run a short introduction and training session for all users and follow up with them once they’ve had experience using the platform.
4. What can you tell us about the accuracy rate on predictions? Is there any testing or research that you can share?
We make sure that our predictions are as accurate as possible by constantly back testing. We have access to a huge data pool from our customers which enables us to benchmark our estimates against the actuals. Every month we run iterations on tens and thousands of calculations where we are comparing.
When we compare our accuracy on estimating unpaid time, we are typically at least a day closer to getting it right. But we need to consider that these are averages so when we look at the data, we tend to see a bell curve spread to see how much is in the middle of the curve and where the balance is on that curve. We tend to see that our curve is much more symmetrical, whereas our customers tend to underestimate up to 80% of their calculations.
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