Get started: 5 NLP tips for co-innovation

1. Identify processes that have repetitive, manual steps.

As mentioned in the first innovative blog series, document-based processes containing large volumes of high-value data are often good places to start. Examples include invoices, contracts, claims, medical records, statements, forms, call center logs, archives, transcripts, tax records, financial information, and utility bills. These documents are usually unstructured; therefore, the data is trapped and unsearchable and needs NLP to assist the transformation process.

2. Select one process that can make a high impact with minimal effort.

While this may be the case for many of the processes you identify, take it a step further and see what departments could benefit the most. Maybe they have a small team with a backlog of work. Or maybe most of the steps to complete a task could be automated, driving quick efficiency gains to save time and money. Or it could be an area in which the partnering company has deep expertise in a specific technology, which can complement your existing skills and resources. We have often seen invoice processing as a safe, easy proof of concept. Once you kickstart your project, it will create a baseline for the next set of automation initiatives. For ideas and use cases, you can learn what we’ve already done with some of our customers in the second innovative blog series.

3. Align your co-innovation initiative with company values and goals.

Will your initiative support the company mission? Testing out rogue projects usually doesn’t sit right with management teams and budgets. For example, if your company’s goal is to improve customer satisfaction ratings by over 90%, make sure your project will reinforce that by automating a task that will result in faster (or improved) service.

4. Build a cross-functional tiger team with executive sponsorship to drive operational excellence.

Co-innovation teams should typically involve multiple departments to provide insights, not just IT. For example, product development needs input from engineering, product management, marketing, sales, finance, and potentially other departments. A variety of perspectives and experiences are beneficial to co-innovation projects.

5. Continue improving processes by tracking milestones and results.

Innovation is a continuous cycle that needs refinements and the ability to incorporate new technologies as they emerge. Track failures and successes. And, of course, share these with your team. Transparency is beneficial and will only help in future hyperautomation endeavors.

Let’s invent the future

Now that you’ve read these NLP tips and selected your co-innovation partner and use case(s), it’s time to invent the future of your business and transform valuable information into actionable data.

Perhaps you have heard the phrase “data is the new currency?” It is about much more than simply being digital. When you have structured data available, it can expose hidden insights, meaning, and context. And with NLP and other AI technologies, adding meaning and context to your data is the next step in obtaining ground-breaking information. Then, you can truly differentiate yourself — using technology to deliver exceptional customer experience and flatten the competition.

Are you ready to co-innovate? Contact us today >