Part 3: How to Implement Your IDP Solution and Measure Success

Imagine you’ve already done the research, interviewed potential vendors, and selected an IDP solution. Congratulations! Now what? Once deployed, how can you tell if your new solution is working?

Rely on your vendor’s implementation team for a strategic roll-out

Change is a challenge, and it takes time to fully integrate new tech. That’s why it’s important to implement your IDP solution in stages and not expect a complete change or full strength all at once.

But that doesn’t mean there won’t be wins along the way. A top-notch IDP solution will deliver high rates of accuracy and automation out-of-the-box, but it will also continue to get better over time.

Your implementation manager should identify mechanisms that ensure a highly accurate system at the start – one that becomes even more accurate over time due to advanced machine learning models.

And if you’ve chosen your solution wisely, you can rely on your vendor’s implementation manager for a dependable, proven framework and coordinated strategy customized to your infrastructure and business needs.

A good implementation framework should start out with a plan that itemizes the necessary hardware and software required to get started. Next, it should determine step-by-step the resources and processes needed to successfully deploy the solution. The framework should also determine all internal stakeholders whose full support and buy-in will be required at different stages of roll-out, including executive sponsorship. Finally, it will need to identify how to govern future investment above and beyond initial deployment.

Measure success by three criteria: accuracy, efficiency, and productivity

Before you deploy your new IDP solution, map out what success really looks like for your company, including benchmarking metrics to compare with future results. Map your metrics along three criteria: accuracy, efficiency, and productivity.

Ideally you’ve chosen to automate using an IDP solution that can read diverse document types. That means you can count on a large jump in the speed of your document processing and the accuracy of the extracted data. Improvements in these areas are a key sign that your solution is working.

Have you chosen an IDP solution with technology that will flag data known as exceptions? Hyperscience, for example, knows when its transcription is likely to be right; it also knows when its transcription is likely to be wrong (in other words, it has low confidence in its extraction results) and sends these exception cases to your company’s data entry team for review and resolution. This is known as “human-in-the-loop.” The best solutions are not only smarter about when to involve humans, minimizing manual work and oversight, but continuously learn from these cases to improve accuracy and automation.

Fewer manual processes and better data means smarter, better, and more efficient workflows. When organizations have access to more data with fewer errors, employees can turn their attention to a wider range of different tasks that will drive the business forward. Plus, customers will get better and faster service and answers. Make sure you’re seeing a rise in your efficiency metrics at quarterly junctures.

Hyperscience enables the automated processing of low resolution images, scanned documents, PDFs and more with handwritten, cursive, and machine-printed text, and automating the extraction of this data can unlock incredible productivity, not to mention revenue.

When you decrease wasted manual effort, you’ll start to increase output and productivity. Are processing rates up? Do employees have more time to focus on long-delayed initiatives with greater impact on company success? Does being freed from dull and repetitive tasks give people more time and energy to devote to other mission-critical actions? Keep track of these changes to determine the success of your automation initiatives.


Design: Chen Nergal

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