Independent study finds IBM Watson Discovery customers can accrue $6.13M in benefits

The impact of natural language processing

March 2021 saw the release of a commissioned study conducted by Forrester Consulting on behalf of IBM. The Forrester Total Economic Impact study aims to examine the potential return on investment (ROI) an enterprise may realize when deploying the IBM Watson natural language processing (NLP) portfolio of solutions. The purpose of the study is to provide readers with a framework to evaluate the potential financial impact of implementing these solutions.

Enterprise businesses are overflowing with data that must be hunted down and sorted through by knowledge workers. This data contains valuable information and insights that employees need. It also offers a window into predictable trends and customer behavior. However, in many businesses, this information is housed in disparate repositories and composed of structured and unstructured data types.

Legacy enterprise search systems aren’t sophisticated enough to find specific answers, making knowledge work frustrating and tedious. Modern knowledge work is non-routine, reactive, and heavily dependent on workers who can quickly find information and synthesize it into informed business decisions.

Read the Forrester Total Economic Impact study

Why NLP

Intelligent search solutions like IBM Watson Discovery leverage natural language solutions, including intelligent search (also referred to as enterprise search or cognitive search), text analytics and machine learning capabilities, to augment knowledge workers’ strengths. Text analysis solutions such as IBM Natural Language Understanding (NLU) extract metadata from passages, images, tables, and other enterprise documents — like contracts and technical manuals — and transform them into actionable insights.

“If we had not moved to an NLU platform like Watson, we wouldn’t have been able to achieve any growth,” says the chief of product at an online media company. “Journalists don’t want to click a button and sit there and wait 10 minutes for the system to come back with the result. So one of the most important things was that Watson was able to return a result very quickly and accurately.”

Learn more about intelligent search

See results with NLP

To compile a thorough report, the Forrester team took the aggregated experiences of four IBM clients who are using IBM Watson Discovery and Watson Natural Language Understanding. Forrester’s analysts discovered the following benefits that an enterprise can expect to see over three years:

• Knowledge workers who previously spent 20% of their time on text analysis/search reduced task time by 50%
• Replacing costly legacy systems saves $150,000 a year
• The efficiency and accuracy of the solutions deliver a 5% increase in growth per year
• Increased worker productivity improves quality of work and customer satisfaction
• Workers start seeing the benefit of the solution after 2 hours of training
• It takes just 13 months to recover the cost of adoption and implementation
• An organization can experience a net present value of $4.86M and an ROI of 383%

“We were able to reduce the time that lawyers spend on answering the questions,” says the cofounder and CEO of a legal services business. “A question comes in to the lawyer, and in the background Watson is already giving some proposals of possible snippets of good answers which could be useful for answering the question.”

What’s next?

To further explore the report results and learn more about IBM Watson Discovery’s award-winning NLU capabilities, IBM is hosting an exclusive analyst overview webinar. Hear Forrester Principal Analyst Mike Gualtieri in conversation with report author and TEI consultant Sarah Musto as they discuss the implications of Forrester’s comprehensive economic impact study.

IBM digital event:

Expert overview of cost savings and business benefits improved by employing IBM Watson Discovery and Natural Language Understanding

Date:

Wednesday, March 31, 2021

Time:

1:00 PM Eastern Daylight Time

Duration:

1 hour