Digital transformation is a methodology in which organizations change and create new business models and culture with digital technologies. Digital transformation has contributed greatly to a major business upheaval: since 2000, 52% of companies in the Fortune 500 have either gone bankrupt, been acquired or merged, gone bankrupt, or ceased to exist. These organizations failed to respond quickly to the pace of change. In fact, the lack of business agility led to their demise.
While most organizations face massive technical debt from legacy infrastructure and applications, market leaders and fast followers realize that the future requires making proactive and strategic use of digital technologies to support the future strategy of their organizations. They see the shift from analog to digital systems as a continued march to delivering business agility.
Modern systems start with an anticipatory approach aimed at solving the issue of massive individual scale and enabling connected experiences. These systems simplify the business environment by abstracting information from the older systems to create new paradigms. As business requirements evolve, these systems deliver platforms that enable organizations to continuously match an organization’s evolution. Consequently, new next-generation platforms and apps must deliver business agility at today’s and tomorrow’s pace of change. The progression to digital follows a progression from systems of engagement to digital systems that deliver mass personalization at scale (see Figure 1).
Figure 1. From Analog to Mass Personalized Systems
Systems of engagement provide standalone and embedded social media and collaboration capabilities, which introduced new verbs to computing, including like, share, publish, collaborate, and subscribe. These systems started with a design point of “sense and respond,” with a goal of solving problems of massive social scale. These systems support interactive experiences, from touch-screens to gestures. Communication styles focus on conversations that happened in real time. The impact and reach shifts from departmental to more widely interconnected. Information moves from highly structured data to loosely structured knowledge. Intelligence builds on hard-coded or deterministic business rules, which provide a greater sense of smartness.
The next level of business agility is systems of experience. It starts with an agile and flexible design point. Experiential systems deliver massive contextual scale. Bionic, human APIs connect users to systems, with a communication style of role-tailored interactions. The speed of real-time, coupled with contextual relevancy, creates right-time interactions, where delivery of information and insight happen as needed. Right-time interactions improve the signal-to-noise ratio. Experiential systems move beyond the four walls of the corporate environment and push out to customer-, employee-, partner-, and supplier-driven segmented value chains. Knowledge flows into systems as immersive streams filtered by context. As these systems get smarter, intelligence gains a probabilistic, pattern-based, self-learning approach. To date, these systems do not exist out of the box, and market leaders must design, assemble, integrate, and build these systems from scratch. Early examples include ad networks, gamification models, and demand-sensing supply chain and commerce systems.
Leading technology providers are building for the future of digital with mass personalized systems. The shift to mass personalized systems delivers a customer segment of one and drives the goals of building a digital architecture. Leading technology providers assemble the components to deliver on an intention-driven design point for massive individual scale. These systems craft user experiences personalized from self-learning and designed by use case. The communication style reflects an appreciation for sentience, the ability to feel. Mass personalized systems move in a space-time continuum, as these systems not only anticipate personalized requests, but also build prediction models of what is most likely to occur. The impact and reach are tailored to people-to-people networks that move beyond corporations, but balance personal and business connections. Information management builds on context and then applies knowledge bases to deliver situational awareness. Intelligence is predictive. Early examples include decision-support systems, personal clouds, identity, and vendor relationship management systems.
As organizations have emerged more efficient from technical debt- and cost-reduction efforts over the past decade, leaders are poised to address the next set of business challenges, which require more than incremental innovation. In fact, incremental innovation is no longer enough. Organizations must manage the constant tension and expectation to create new business models or disrupt existing models with new technologies and the need to invest for the future without harming short-term profits. These market forces create a high priority for investing in business agility and will provide the catalysts to build the next generation of systems that meet the pace of change required to succeed in the digital world.