Beyond the Arc
Simplifying Data Science for Enhanced Customer Experiences

Today, businesses large and small are aiming to adopt innovative ways to unlock the value hidden within their data to attract and retain more customers. To that end, many are interested in incorporating emerging technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) into their existing customer-facing solutions and services. Fueled by the data boom, IBM is leading AI innovation with its state-of-the-art tools and platforms. That said, some companies may be challenged with how to capture ROI because of their lack of internal expertise in building customized data science solutions. They need assistance in developing the right data science strategy and architecture, as well as implementing the solutions efficiently. Beyond the Arc, a data science agency hailing from San Francisco, can help. The company has tremendous expertise and experience in helping its clients create and deploy machine learning solutions. They address a range of use cases, from delivering personalized customer experiences to reducing costs by optimizing operational processes.

In an interview with CIO Applications, Steven J. Ramirez, CEO of Beyond the Arc, discusses the company’s inception, growth, and future in helping clients excel with data science.

Give us an overview of Beyond the Arc.

Beyond the Arc assists organizations in creating the right data science strategies and architecture and then implement next-gen data science programs. Our focus is on helping clients gain insights from their data so that they meet their business goals. As a certified IBM business partner, we simplify the selection, software

licensing, implementation, and utilization of IBM’s machine learning and AI solutions. As a key part of our work, we also develop natural language processing (NLP) solutions capable of analyzing unstructured data for insights.

Our clientele includes companies in technology, utility, financial services, and other industries. We enable clients to understand the needs of their customers better and deliver personalization and predictive solutions.

We also help clients use predictive analytics to improve operations and back-office functions.

How do your services help businesses in reaping the benefits of IBM solutions?

As a data science partner of IBM, we resell IBM’s industry-leading products to our clients. We begin every client engagement with our defined process that we call ‘Roadmap to AI.’ It starts with a thorough assessment of the client-specific requirements. With this understanding, we often develop proof of concept projects (POC) to mitigate their challenges. After viable POCs are created, we help scale these efforts. We create tailored and scalable solutions on top of the IBM Data Science Platform that includes IBM SPSS and IBM Watson. Our team offers the necessary training and support services based on the size and maturity of the client business. We also help transition the organizational culture of our clients and facilitate the effective utilization of the upcoming technology implementation.

We recognize the hype surrounding all the possibilities of ML. We eliminate the complexities of machine learning to emphasize its practical and applied uses. Additionally, our 18-year experience in developing solutions capable of solving real business challenges gives us a competitive edge over our contemporaries. At the same time, we educate our clients to help them see the many ways they can gain an advantage with machine learning.

Could you elaborate on a client success story?

In one instance, we assisted a large bank in maximizing their customer satisfaction and retention. We collaborated with the bank’s call centers and email support teams and built an NLP-based technology solution that leverages IBM’s SPSS modeler data mining platform. With the NLP and text analysis capabilities of the developed system, the client was able to analyze over a million customer feedback inputs a month from emails and telephone conversations. As a result, the bank could create a prioritized list of customer experience issues that they needed to address to boost their customer satisfaction. In a win for another customer, we used IBM SPSS Modeler’s powerful data integration capabilities to curate legacy datasets and create data assets that can be used for predictive modeling. With the ease of Modeler’s drag-and-drop interface, their team is now analyzing historical data and building models to improve maintenance and safety.

What does the future look like for Beyond the Arc in the next 12-18 months?

Looking ahead, we plan to simplify the adoption of data science of machine learning for businesses of all sizes. Furthermore, with Beyond the Arc’s ‘Roadmap to AI’ approach, we plan to provide the tools and training required to help business analysts conduct effective data science processes. We want to enable robust data analytics in organizations that do not have highly trained data scientists on their staff. Our mission is to drive the democratization of data science and simplify its utilization.