Is PMML Useful for Model Deployment?
At LatentView, we develop a variety of predictive analytics solutions for our clients. Our deliverables typically include a power point that highlights key findings and the consequences, excel sheets to validate business hypotheses and model equations in some form for ongoing scoring. The last one is the topic of this post.
There are a variety of approaches to deliver models. For simple techniques such as Logistic Regression, we typically deliver it in Excel, or in the form of a VBA-based decision simulator. For more complex techniques, we deliver a set of SAS codes that can then be used by the client to score models on an ongoing basis. These SAS codes consist of logic for data preparation, model scoring and validation.
This is where PMML plays a key role. LatentView is standardizing on a PMML-based approach for delivering predictive models. PMML promotes model portability across different platforms, model maintenance, and better lifecycle management. It's faster and easier to score and validate with PMML models. PMML also makes it easy to develop a visualization tool.
However, from the looks of it, PMML is not so widely used.
Some of the drawbacks of PMML include potential loss of accuracy, alleged lack of support for a variety of models, lack of support for complex transformations and lack of availability of third party scoring engines that read PMML and score models. However, tools like Zementis have helped overcome some of these drawbacks, and I believe there are more such offerings in the pipeline. There's also a need for open source scoring engines that use PMML.
Today we use R to generate the PMML files. However, we understand that there's a need for an easier way to create PMML files from SAS, SPSS or other standard packages (rather than buying their most expensive licenses).
What do you think of PMML? Do you deploy models in PMML? Does it meet your model deployment needs? Why / Why not? Please post your comments here.
Are Pharma Sales Reps going to be obsolete soon?
Given the economic downturn, the entire corporate sector is in cost cutting mode. Pharma companies certainly aren’t going to be left behind. They are digging deep into their expenses and evaluating the returns from every investment that has been made.
While studying effectiveness of various methods of promotion, Pharma companies are beginning to wonder whether they are spending too much money on reps, especially for not much return. One of the clear indicators is the way leading Pharma companies are cutting down on their sales force – In the US, there were around 94,000 reps in 2007 compared to 92,000 in 2008.
The question that marketers are asking is that ‘If samples are the most effective medium of influencing prescriptions, are Sales reps reduced to being well-dressed delivery boys?’ Are their salaries justified? With the increased number of doctors who have been ordering samples online, one begins to wonder why Reps are required at all! Physicians say they prefer the online medium anyways because they can do it at their own convenience and don’t have to answer questions regarding their prescription habits every time they ask for a sample.
Given that there are few new products launches, owing to drying pipelines, do companies still need detailers who drop off samples and make hardly any connection with the doctor? Do reps really make any difference to the prescribing behavior of physicians?