From Okay to Awesome: A Buyer’s Guide to Processing Automation
The market for processing automation tools is heating up – growing volumes, pressure to support new use cases, importance of data quality to analytics, and the hyper-tight labor market all make automation an essential and high return investments.
Rampiva has been supporting clients in this space for 5 years. Our clients collectively process over 500TB each year, and we know that because we stay with them through the years to make sure we’re delivering day in and day out.
Based on this experience, we wanted to share our thoughts on how to evaluate your different options. Let’s assume that every tool delivers the basics: workflow templates, a job scheduling queue, and centralized reporting. What makes the difference between okay and awesome?
- User Interface has to be really easy to use. It’s one thing for expert systems to be a bit complex, because you get flexibility, but for processing automation it’s different – teams are prioritizing productivity, so every interaction has to be both streamlined and accessible. An extra 5 minutes setting up a job has real implications to the scalability of your team.
For example, we have a client that started the automation journey in 2018. They were loading about 5 TB into the tool and exported 3 TB for review. They had a blended team with 2 primary users and 6 total users. They executed roughly 3 processing sessions per week. By 2021, that same team is loading 22 TB, exporting 12 TB,and running 88 session per week. Admittedly, they hired more project managers – because they have a lot more projects! But the same processing team has increased productivity by 14X because the User Interface lets them schedule a job in under 5 minutes.
- Workflow Design has to support exceptions and edge cases. Automating data processing is not “one size fits all” – the workflow that fits 60% of your projects isn’t going to fit the other 40%. Realistically, that other 40% probably needs increasingly customized Workflows to deliver. There’s also a “last mile” effect, where teams are more likely to adopt automation if it’s flexible. If it actually gets them all the way home.
Advanced clients will also continually improve their workflows, which is a big investment of expert time and also requires rigorous stress testing before putting that Workflow into production.
To make this process easy, Rampiva users have access to a Library built by our team of exports, a user-friendly Workflow Wizard, and conditional Parameters that allow users to adapt advanced workflows in real time while setting up the job.
Learn more about Rampiva Parameters.
- Connectivity. Data processing is usually part of a larger workstream, so it’s really helpful to consider how your automation tool will interact with Legal Hold systems, Collection tools, Matter Management platforms, data staging tools, eBilling systems, cloud hardware environments, and review tools.
Increasing productivity is great, but it’s really great if you can take full advantage of that new capacity by accelerating how quickly data gets to your processing environment.
Accelerating results is great, but it’s really great if you can push data directly into the review environment of choice.
Handling 14X as many jobs is awesome, but you’d better have a plan for tracking that activity as part of the larger matter, generating invoices, or attributing spend to the requesting department. And if that plan is to “enter it manually” then you’d better budget for that role. Or, invest in an Automation platform that makes all of this easy to administer.
- Comprehensive, real-time operational reporting. Automating data processing is going to make your department more productive. Strong Dashboards will help you measure it, show the impact, leverage it to do more, and turn that increase in activity into budget, authority and trust. It will also help you diagnose friction and bottlenecks in your operations, training opportunities and standout team members, and message performance and productivity.
Stay tuned for next week’s deep dive into Advanced Features and how they help.
We hope this has been helpful perspective!