EARL London – speaker interview, Johannes Tang Kristensen

August 21, 2019
By

[This article was first published on RBlog – Mango Solutions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

We sent Johannes Tang Kristensen from Arla Foods a few questions about his upcoming talk at EARL London – ‘How much milk do our cows produce? Lessons learned from putting our first R model into production’.

How did the need for your project come about?

The project started out as part of a larger initiative in Arla with the goal of proving the need for and value of advanced analytics. In this particular case, our global planning team asked us whether we could have a look at their current forecasting approach and see if we could improve it. An interesting aspect of the challenge was that the performance of their current approach was very high so they did not necessarily expect us to come up with a model that could beat their forecasts, although they of course wouldn’t mind it if we did. Instead what they wanted was a model that could help them develop a more systematic approach towards creating their forecasts where it would be clearer what the underlying assumptions of the forecast were, where they would be less dependent on the knowledge of individuals in their team, and where they wouldn’t have to spend days creating a forecast in Excel.

Where did you start with your project?

The project started by conducting a proof-of-concept where we were given a data set compiled by our global planning department containing the variables they believed could be relevant. Using the data set we were able to build a model that in the end outperformed their current forecasting approach. In order to present the results in an interactive way we supplemented the model with a Shiny dashboard where our stakeholders could visualise the forecasting performance of the model in different cases and at different points in time. Based on this the project was approved and upgraded from proof-of-concept to an actual IT development project which meant we had to figure out how we actually put such a model into production.

How did you communicate the value of your work to the rest of the business?

The communication was mostly driven by our business stakeholders as they were the ones that best understood the actual value of the forecast improvements and time-savings provided by the model. However, we have of course also used it to showcase what we can deliver whenever possible.

Thank you to Johannes for answering our questions. Please take a look at the other brilliant speakers we have at EARL, we are now counting down the days! There is still time to get a ticket to EARL – our workshop spaces are filling up quickly, so don’t miss out. 

To leave a comment for the author, please follow the link and comment on their blog: RBlog – Mango Solutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)