In a webinar I gave last week, “Over Outlook? Simplify your PV mailbox with NLP technology,” I introduced a scale that I call “Case Processing Evolution.” These five steps cover what we’ve found repeatedly at pharmaceutical companies—where they’ve come from and where they’re going on the road to automation.
In case you missed it, here are the five steps to automation.
1. Any Means Necessary
When companies are just starting out, they may find themselves in the “Any Means Necessary” Phase. You may be in this phase if:
Your company has no standardized way to accept reports—you’re just trying to manage them wherever they come in.
Your team is manually processing these reports— data validation is near impossible and your process takes a lot of manual work and direct monitoring.
You often feel that you’re just too busy to compile metrics or optimize the process
If this sounds like you, then it’s time to take a step back and start working toward the next phase.
2. Low Hanging Fruit
It’s not perfect, but it’s a lot better! These companies may not be using the newest technology, but they’re finding ways to make their process more effective:
- Your company has started automating a few of their intake methods by adding electronic data entry from your vendors
- Manual Processes are still there, but they’re getting smarter—e.g. personalized email folder on your shared inbox, color-coding incoming cases and other quick fixes
3. Process Automation and Fine-Tuning
This is where it starts getting good. Not only is your AE Intake Process fully digital, its also fully validated!
- You have standardized processing with robust integrations with other data sources
- Your process works on its own without a lot of clerical effort
- Your centralized and digital process is easy to query for reports—or better yet, reports are fully automated as well.
4. Incorporating AI
In the evolution of technology, AI (Artificial Intelligence) pops up towards the end of our timeline—but that doesn’t mean that it can’t support your processes in other stages of evolution. A well thought-out Natural Language Processing application can help you triage new cases for language, seriousness, and completeness without painful infrastructural changes.
5. Total Automation
In an ideal world, anything that could be done by a machine would be—from intake, translation through verification—the software would handle processing and only require human intervention when they’re needed most.
As we all know, today’s technology hasn’t gotten there – and neither have our regulations. That won’t stop us from dreaming though!