Predictive Dashboarding

Everyone can make a dashboard these days. In fact, most business systems, whether LIMS, ERP, MES, QMS, SDMS, POS, or CDS (and the list goes on) come with an analytics and/or dashboard module out of the box. Additionally, organizations have reporting tools such as Power BI and Qlik in-house for use. While it’s tempting to utilize existing resources who are “good at that sort of thing,” to utilize these tools, think of the time saved by bringing in someone who specializes in Life Sciences data and who already has expertise in not only reporting and visualizing information but with modeling to optimize and predict in an automated manner.  Presenting models in a dashboard view steps up your dashboard game.   Things like training predictive models, adjusting those models’ hyperparameters, gauging performance, navigating heteroscedastic data, introducing cleaning approaches to dirty data, etc., can all get very complicated.

Often, the dashboards that come out of the box don’t yield the most fruitful visualizations or analysis. They’re typically simple sums or slicing and dicing (descriptive/diagnostic analytics). These can be useful as a first step but when you are ready to predict what will happen next or even catch problems before they occur to sidestep massive costs a deeper dive is typically needed (predictive/prescriptive analytics).

Custom modules, or even help with complexly configured descriptive/diagnostic analytics, can be just the thing. CSols data & analytics experts are trained to quickly assess your data, identify the required data sources to view the right data sets, and extract the most valuable insights. With hundreds of different system implementations, they know where to start and what to look for, with the goal of a smooth hand off to the in-house team.