Company: IBM, Armonk, NY
Company Description: IBM is the hybrid cloud and AI technology and services company, focused on providing client value through a combination of technology and business expertise. IBM solutions draw from an industry-leading portfolio of capabilities in software, consulting services and a deep incumbency in mission-critical systems, all bolstered by one of the world’s leading research organizations.
Nomination Category: New Product & Service Awards Categories
Nomination Sub Category: Sales Automation Solution – New
 Nomination Title: COPRA Hub - Deciphering AI Recommendations
- Which will you submit for your nomination in this category, a video of up to five (5) minutes, explaining the features, functions, benefits, and results to date of the nominated product or service, OR written answers to the questions? (Choose one):
Written answers to the questions
- If you are submitting a video of up to five (5) minutes in length, provide the URL of the video here, OR attach it to your entry via the "Add Attachments, Videos, or Links to This Entry" link above, through which you may also upload a copy of your video. If you are submitting written answers to the questions for this category, provide them in the spaces below.
- Describe the features, functions, and benefits of the nominated product or service (up to 350 words):
Total 348 words used.
IBM sellers and pricers have been using COPRA (COgnitive PRicing Analytics) derrived Optimal Price (OP) to support negotiations and to automate pricing processes for over 5 years. Despite its growing popularity, users have expressed a desire for more flexibility from this AI solution.
The primary user requirements had been around two points: 1) the need for greater transparency into Machine Learning / Artificial intelligence (ML/AI) methods and the output details to boost confidence and increase OP adoption; 2) the need for a quick (if not immediate) simulation of OP generation under different deal scenarios, a common occurrence during negotiations with clients.
To address this challenge, Chief Analytics Office (CAO) developed a companion tool – COPRA Hub – a one-stop-shop solution that seamlessly integrates ML/AI methods, API (Application Programming Interface) technologies, traditional data analytics, and visualization techniques. Along with monitoring and other operations-focused functions, COPRA Hub implemented two user-centric capabilities: OP Explanation and OP Simulation.
OP Explanation: By consolidating all request and response information from COPRA API with full set of model logic, historical data, and business rules, a robust search engine was developed. It empowers users to explore the context for their pricing quotes (client history, product performance, etc) as well as to understand key drivers of the OP in a straightforward numerical fashion (Figure 1). This capability improves users’ understanding of the OP computation, leading to more confidence and, therefore, greater adoption of COPRA AI. At the same time, users no longer need to depend on the operations team responding through traditional channels such as Slack, email, or web-conferences, which, in turn, eliminates delays and reliability concerns characteristic of human-mediated transactions, reduces repetitive workloads on both parties ultimately helping IBM achieve greater productivity.
OP Simulation: By establishing a connection to COPRA API and replicating the production database, COPRA Hub has effectively put the entirety of the quote research onto a single screen. With OP Simulation, sellers and pricers can easily explore multiple variations of the quote through What-If analysis (Figure 2), helping users to generate multiple options for their clients, while building understanding of what impacts the OP.
- Reference any attachments of supporting materials throughout this nomination and how they provide evidence of the claims you have made in this nomination (up to 250 words):
Total 32 words used.
Please see the following resources as referenced in the sections 4 and 5 above:
- If you are nominating a brand-new product or service, state the date on which it was released. If you are nominating a new version of an existing product or service, state the date on which the update was released:
COPRA Hub is a brand-new solution which was released in September 2023.
- Outline the market performance, critical reception, and customer satisfaction with the product or service to date. State monetary or unit sales figures to date, if possible, and how they compare to expectations or past performance. Provide links to laudatory product or service reviews. Include some customer testimonials, if applicable (up to 350 words):
Total 246 words used.
Since its roll out, COPRA Hub has reduced communication overhead by about 80% – 4 out of 5 times users can solve their inquiry entirely on their own, eliminating the need to engage the operations team and associated pitfalls, such as potential misunderstandings, unavailability, and delays due to time zone differences. This alone saves 17K hours for users to be faster in closing deals with more efficiencies and confidence, an equivalent to $0.7M in productivity gains per year.
Most importantly, COPRA Hub contributes significantly to enhancing COPRA OP adoption. Multiple research studies indicate that ‘AI explainability’ (Figure 3) or ‘Fear of the unknown’ is a primary barrier to ML/AI adoption. COPRA Hub addresses this challenge driving estimated 10% growth in COPRA OP adoption which corresponds to about $4M of incremental revenue per year.
Comments from users:
- “This looks fantastic!” – C.B., IBM WW Pricing
- “I’m sure this is informational for my team! It helps us self-service for sellers to understand how COPRA price is built in the individual cases.” – M.S., IBM WW Pricing
- “I loved the concept when I first saw it back in Feb. I am pretty sure I was not alone in that. Glad the team could make it a reality now.” – K.A., Pricing Operations
- “The tool is incredibly useful for understanding/explaining quote prices and troubleshooting. It has greatly decreased the time/people involved in investigating quote errors or unexpected results” - M.G., Pricing Operations
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