Business leaders want to make informed decisions quickly, learn from insight, become more efficient, and stay profitable in today’s world. But extracting insight from data that will lead to more informed decisions is often a long process involving cross-organizational teams from various business areas, bottlenecking the organizations’ ability to make quick decisions and act on them. Decision management platforms like Lithium AI can speed up and automate the insight and decision-making process in many cases. Here is how:
Normally a cumbersome process, ingesting and normalizing data from multiple sources becomes easy when using data normalization techniques that come bundled with Lithium’s Studio, taking pressure off data scientists and engineers to do menial “clean up” work.
Decision models can then be built using that data. Whether the question is where to deploy resources due to geographic demand shifts or identifying what service shortcomings cause the most customer churn – Lithium can present data-driven evidence of cause and effect. Making any decisions that need to be made by management much more straightforward.
Lithium AI in and of itself is a powerful business tool that can give business leaders an edge, but the same principles can be tied to RPA (Robotic Process Automation). For example, Lithium can convert insight into triggers that link directly into an RPA platform.
The process is relatively straightforward, with the figure below showing how Decision automation (blue) plugs into RPA (orange).
Decision Automation to RPA
Using the churn example from above, Lithium AI can identify that a customer will churn with varying degrees of confidence. Then, plugging this data into an RPA or marketing automation platform lets the company automatically execute remediation tactics and decreasing churn.
While this is only a single relatively rudimentary example – Lithium applications can be deployed for numerous use cases across industries as different as healthcare, retail, and financial services. It’s accessible machine learning and artificial intelligence.