We have already disclosed a few insights about what’s being used at Lokad. Yet, a frequent support request remains what’s your model, precisely?
We‘re looking through various forecasting statistical packages with the intent on selecting one at some point in the near future. One thing I find lacking in Lokad is to see which statistical model was used. I understand that the selection of which model is used is a trade secret, but I would like to verify the final selection, in the trial that is, with our in-house mathematician before we trust you with our actual forecasts. Most software vendors operating in this space provide the model selected. Is it possible to get that result with Lokad?
Well, unfortunately, the correct answer is that Lokad isn’t a statistical package. In particular, we don’t deliver models, we deliver forecasts.
The whole architecture of Lokad has been designed around this very assumption, which unfortunately is very ill-suited to deliver any information about our models.
Our forecast flow, which grabs input data and outputs forecasts, is:
- vastly more complex compared to models shipped with statistical packages. Forecasts cannot be associated with well-known models.
- tailored for distributed computing in the clouds, thus, the design feels very alien when compared to classic toolkits.
- subject to ongoing changes, as we are carrying experiments on a daily basis with agile deployment strategies.
But this design has very specific benefits too:
- no need to tune complex forecasting parameters.
- no need to constantly watch your parameters, we monitor the results.
- scales up as much as you need to, up to millions of forecasts.
- handles complex patterns that are way beyond classical toolkits.
Then, we don’t ask anyone to take our results for granted. Just go and see for yourself, our trial is free for 30 days.
Reader Comments (2)
Hi John, yes indeed that’s a very good question! Give me a bit of time, and I will directly address this question in the next post.
9 years ago | Joannes Vermorel
Perhaps a better question is “on what basis do you measure forecast performance?” - i.e. how do you demonstrate that your forecast is “better” - what’s the measure. Is it possible to answer this within the “secret” constraint?
9 years ago | John Dawson