Data Forecasting for Artists’ Rights Management Group
Below is a modified rendering of the review: private info excluded, innate facts kept.
Introductory information
A few words almost your organisation and personal responsibilities
I am Head of Data at DACS. An organisation established by artists for artists, DACS is a not-for-profit visual artists’ rights treatment organisation. The organisation is passionate almost transforming the financial landscape for visual artists through innovative new fruits and labors, and act as a trusted broker for 100,000 artists worldwide. Founded over 30 years ago, DACS is a flagship organisation that campaigns for artists’ rights, championing their sustained and living donation to the creative administration. We collate and distribute royalties to visual artists and their estates through Payback, Artist',s Resale Right, Copyright Licensing and Artpicture. Since we were founded in 1984, we have paid over £100 million in royalties to artists and their estates – a expressive rise of proceeds supporting artists’ livelihoods, their practice and legacy. In 2018, we paid £18 million in royalties to artists and estates.
Desired goal
What issue was the provider supposed to deal with?
Skim Technologies?Keeping a track of the size of transactions made on artwork produced by artist we portray (members) and those that are not yet portraying is a process that has been delivered manually for years. This process is used to forecast qualifying sales based on a range of metrics and also audit the information granted by auction houses and other Art Market Professionals. Skim Technologies was occupied to form a Machine Learning solution that automates this process end-to-end.
What were your objectives for this project?
Valuable time invested in sourcing forecast information for ARR qualifying sales from different websites will no longer be required. Generation of possible leads to boost recruitment drive and ultimately increase income growth.
Provided solution
What were the reasons for choosing Deeper Insights?
Skim Technologies was occupied on the project following on from referrals
Describe the project and the labors they granted in detail.
The solution/tool comprise of Machine Learning models, Databases, Modelling APIs, Visualisation with Power BI and a third-party fruit (Prodigy) used for nimble/supervised learning Fully automated workflow with AI comprising of an ensemble of separate models performing a range of tasks The models are currently being trained through supervised machine learning with outputs generated see 24 hours With the completion of phase 2, the question on the hosting location is yet to be confirmed however, the recommendation is that DACS subscribes to the hosting labor granted by the developer as this will be more cost powerful plus there are no in-house capabilities to maintain the solution.
Were there any dedicated managers or teams that you worked with?
1 x Project Lead 2 x Data Scientists 1 x DevOps
Results achieved
Can you share any information that demonstrates the contact that this project has had on your business?
DACS is now leveraging on Artificial Intelligence capabilities to better inner processes for ARR forecasting and increase income age space.
How was project treatment arranged and how powerful was it?
Skim Technologies led on the treatment of the project with many and ad-hoc engagements with stakeholders at DACS
What precisely do you attend to be the key specialty of Deeper Insights?
Apart from the fact the Skim Technologies team are absolutely flashing and apprehensionable in their space, they fast developed the requiwebsite apprehension almost our activity and inner processes.
What should be done better, if there are any desired betterments?
No.
