We recently caught up with John Broderick, who has held the title of Chief Executive Officer of Cicero Inc., for the last fifteen years. Cicero is a noted contact center and back-office enterprise software provider, and a welcome new member of Frost & Sullivan’s Customer Engagement Leadership Council. John fielded a few key questions about Cicero’s origins, products and services, and discussed how big data, artificial intelligence and machine learning are currently shaping product development and the customer experience.

    1. You have been with Cicero for a long time now. What attracted you to the company initially?

      The original use case for Cicero was to create access to a 360 degree view of a wealth manager’s customer’s accounts. Every application was opened in context of the interaction. There was no searching and logging into applications. This was game-changer integration as no code is required to integrate disparate applications. Our integrations were literally man-days rather than months of rewriting code or replacing applications altogether. Our first focus was on contact centers, where nearly everything is measured including time on task. Later, we realized that we have a unique ability to capture data that others cannot; specifically how work happens at the desktop; all in terms of people, processes they use and technologies deployed. That clearly redefined our thinking about data driven decisions allowing the customer to make operational and systematic corrections to their existing processes and technologies.

        2. Specifically, what Cicero product or service are you most proud of helping to develop or steward?

          A few years ago, we were at a company retreat (imagine a “retreat” for a company of about 15 people as we were and still are small). It was there that we “whiteboarded” the beginnings of what has now morphed into our Intelligent Analytics Platform. That product was originally called “Discovery” -of course, what else would it be! We were convinced of the need for a systematic or scientific approach to automation – using data to identify process bottlenecks. Discovery perfectly complimented our automation product by identifying which processes worked and which did not- where there were bottlenecks and excessive manual actions. Over time, we have added a visual tool bar, machine learning and artificial intelligence where we can predict the next best action for an agent.

            3. Cicero recently hosted a Webinar and Customer Engagement Leadership Council Roundtable, “Why Shoot from the Hip? Use Data to Restart and Reimagine Your Business Instead?” What key insights were shared?

              We are in the midst of significant and accelerated change. We see it in our businesses and we see it in our daily lives. We see an influx of people working from home. Is that a tactical change or a strategic change? Data is necessary to understand how to best meet both the tactical and strategic challenges in front of us. Most companies reply on interactive metrics like CSAT, NPS and Voice of the Customer, but they don’t leverage observational metrics. These metrics shed light on things like production delays, defect rates, agent effectiveness, capacity management and the like. We need to be dynamic in these changing times and leverage both interactive and observational metrics.

                4. What’s the most important thing B2B companies need to understand about Big Data today? What strategies do you recommend to best leverage data?

                  The single most important thing about Big Data is the speed by which it produces usable analysis for making business critical decisions. The ability to consume all enterprise data, across systems, data types, structured, unstructured and produce a meaningful result is more critical than ever, but also more accessible than ever to achieve. We recommend leveraging readily available tools that include data lake technology, machine learning, in addition to investing in your people to cultivate in house data science expertise.

                    5. Why are analytics so important to the enterprise today? Your views on the efficiency and/or pros and cons of AI and ML? How do they help to enhance the customer experience?  Pitfalls to beware of?

                      We are strong proponents of AI, ML and Deep Learning. That said, this is nuanced and tricky territory and it is very easy to be seduced by an .ai domain only to find out they are selling snake oil or vaporware. That is the biggest con in our opinion, but the pros far outweigh these challenges. As an example, ML can be used to identify clusters of agents by behavior in a particular process at scale. Think millions of small activities. It simply isn’t possible to analyze this manually and produce the same results reliably. These clusters of behavior can then be sequenced to identify the various ways agents interact with the customer while handling the same type of claim as an example. This sequencing can shed real detail on why one is more effective than another, using real data not produced by a survey that is inherently flawed.

                      Take this a step further and we can apply Deep Learning to the sequences and then begin to predict next action during a live sequence. This has applications to produce an enhanced customer experience due to speed and consistency, and can also affect fraud and compliance in real time.

                        6. Where do you see the customer contact industry heading in the near future, i.e. as the pandemic crisis continues? Further out?

                          The current pandemic has certainly redefined the business world.  Many industries have been decimated — retail is a great example — as consumers are moving more to the digital world to shop. Work from home has exploded, and companies are struggling with capacity challenges as well as production challenges. This new normal may be with us for a while.

                          At the same time, consumers are more reliant on agents that offer a personal interaction – the customers want to be known, they want the agents to “know their stuff” whether it be product related, transaction related, or policy-related, they want the agent to keep them informed. Most importantly, they want the interaction to be effortless. Looking into our crystal ball, we do not see a near term reversal; we see the contact center front and center delivering that customer experience as an integral part of the enterprise.