TechBytes with Barry Pellas, Chief Technology Officer, PointSource
Chief Technology Officer, PointSource
A recent study by PointSource, called The Executing Digital Transformation, probed 300 decision makers in marketing, IT and operations about the challenges businesses face when trying to make improvements with the end-users in mind. Challenges include framing a digital strategy, ensuring departments work in synergy and knowing what the consumer wants. We spoke to Chief Technology Officer at PointSource Barry Pellas about how to navigate this digital transformation.
MTS: “Complacency is the Achilles heel of today’s digital organizations.” What complacency is the report referring to?
Barry Pellas: Organizations need to continually evolve if they want to succeed, and that requires actively listening and adapting to meet user needs. When an organization begins to subscribe to a legacy mindset or legacy processes – either by failing to recognize that the customer needs are evolving or choosing not to respond to those changes – that’s when complacency sets in. The organizations that become complacent in today’s competitive landscape will quickly fall behind to those that maintain an iterative, user-focused approach. It’s vital that organizations maintain a clear direction for achieving long and short term goals in order to avoid the sting of this Achilles heel. Investing in internal resources, like technology and trainings, is key so that skills remain relevant to support those ever-changing customer needs. Developing clear, measurable KPIs that are frequently reported against can help drive improvements to the customer experience, thereby preventing complacency and, ultimately, irrelevance in the market. With regards to technology, organizations need to evaluate and determine relevance quickly to see if there is possible enablement of a better user experience. For example, intelligent systems are upon us and now is the time to consider this technology to help achieve business outcomes. Finding that trusted advisor to help navigate the technology will be key as new technologies arise which will in turn fight complacency.
MTS: Marketing technology budgets are growing at a phenomenal pace. How does this reflect on a company’s digital transformation framework?
Barry: It’s no secret that the fight for resources is fierce within companies. While in a perfect world, additional resources being allocated for marketing tech programs would mean some gets spread evenly across all departments, that’s often not the case. In fact, three-fourths of department leaders indicate that they compete with other departments within their organization for resources and/or budget. But for companies undergoing a digital transformation, an increased budget requires collaboration, rather than competition. Applying an incubator team that can be used to support or discredit ideas quickly can be a great way to start building a collaborative culture and provide a universal resource for different departments to go to with ideas. This team can work to formulate UX research which can help an organization determine what users actually need from a system before they fully invest, saving time and money. The user experience is something all members of an organization impact, regardless of department. If the marketing department wants to use some of their newfound budget for a user-focused digital initiative, they’ll need the support of everyone from UX designers to backend developers to sales managers. In order to create a solid foundation for digital transformation a culture of collaboration is required.
MTS: “Digital transformation is not a single destination.” How do you see the journey evolving with AI/ML technologies in the next five years?
Barry: Gartner estimates that the world’s information will grow by 800 percent in the next five years, and that 80 percent of that data will be unstructured. With this influx of information, cognitive computing and AI technologies will be increasingly used to harness data in order to transform business intelligence and digital experiences alongside human capabilities. As artificial intelligence and machine learning become further ingrained within the everyday user experience, we’ll see increased pressure on organizations to employ this technology to stay competitive and achieve better business outcomes.
However, many organizations are still in the early stages of their digital transformation and don’t have the appropriate systems in place to integrate with these advanced technologies. While organizations might not be ready to dive deeply into more mature technology, there is little reason not to start preparing for them by implementing practical applications of AI and machine learning where it makes sense in small chunks. Often, organizations get caught up in the flashy, cool technology without giving thought to the scalable architecture that’s necessary to support these initiatives. As this technology becomes more essential, organizations will need to look for ways to build the necessary foundation to support advanced technology. UX teams should challenge themselves based on assumptions of smarter systems and developers should prepare to create those smart systems by exploring simple ways to inject intelligence. Over the next few years, we can expect to see more organizations start to gradually adopt digital solutions that will equip them with the tools to employ AI and machine learning when they are ready. By gaining familiarity with this technology, organizations can get ahead of the curve with minor investment or change in their process.
MTS: Achieving unified, seamless and intuitive customer experience remains an elusive proposition. How should organizations build the right engagements for the right audiences?
Barry: In order to build the right engagements for the right audiences, organizations need to prioritize understanding their users and adapting to their needs and preferences. Right now, about 12 percent of decision makers indicate that their organization doesn’t know when, where and how its users interact with the company across digital and physical channels and devices. In order to achieve a unified, seamless, and intuitive user experience, organizations have to spend time collecting qualitative, cross-channel user data. This type of data collection can be done through focus groups, one-to-one interviews and live observations. Data is an organization’s best friend. Given the advanced tech that is available today, timely and accurate reporting is incredibly easy to achieve. But it’s only by analyzing this information that it’s possible for organizations to quickly act on trends and user behaviors.
Users crave personalization. And because of this, organizations’ demographics are important as they work to engage users across all channels, online and offline. In this process, organizations need to consider the individual users’ unique needs to create more and more brand loyalty through tailored offerings. If businesses can tap into the power of cognitive systems and AI, it’s possible to personalize experiences like never before. Organizations will be able to personalize the user experience and the data that the user interacts with, and then also change the way that data is produced through smarter systems. Ultimately, individual engagement will be key to the seamless experience and deep learning technology will help gather the necessary data to make each interaction a unique one.
MTS: With newer regulations for data privacy in place, how should digital companies prepare their enterprise technology stack to manage and analyze audience data more judiciously?
Barry: In order to prepare to securely manage analytics data, technologists & architects need to design systems with both event management and scalability in mind. The systems need to do much more than just monitor. They need to, in real-time, map different events to correctly react within the system to take the appropriate action. These systems need to have intelligence to make decisions involving both confidence in the data they receive and how to handle partial or supplemental data. With more and more variations in the system, organizations must consider Big Data security analytics solutions to help them manage the volume and coordination of data in the most secure way. In addition to the implementation considerations, organizations also need to consider tools for viewing the new influx of analytics data and reporting on that data. Having the right partners and team members to make sense of the vast amount of data as well as creating a roadmap to collect the right data to be analyzed.
MTS: Thanks for chatting with us, Barry.
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