I recently attended the Digital Government Summit. As expected, there were plenty of keynotes and sessions centered around these core trends: Mobile, Social, the Cloud, Analytics and Internet of Things. Perhaps somewhat surprising was the focus on the impact of the digital revolution on business transformation, both in the private as well as the public sector. As Alan Cox stated in his keynote, “There is no project any longer that is a technology project; only business projects.”
We finish this series on the top 10 trends with perhaps the most important trend of them all: Adaptive Digital Enterprises. Digitization and business transformation trends are not just about technology— they are about delighting the customers, optimizing the customer experience, and promoting the culture of a modernized enterprise that is constantly adapting to changing and evolving strategies.
Digitization is one of those mega-trends affecting every aspect of our personal lives and our business lives. Authors Andrew McAfee and Erik Brynjolfsson (in The Second Machine Age) articulate the big historic picture of digitization very well:
“The late eighteenth century corresponds to a development we’ve heard a lot about : the Industrial Revolution, which was the sum of several nearly simultaneous developments in mechanical engineering, chemistry, metallurgy, and other disciplines. … Now comes the second machine age. Computers and other digital advances are doing for mental power- the ability to use our brains to understand and shape our environments— what the steam engine and its descendants did for muscle power… The Second Machine Age will have greater impact than even the first industrial revolution.”
With that top of mind, here is a summary of the previous nine trends I’ve blogged about as of late:
- Trend #1 Innovation for Digital Enterprises: We started the series with the four dimensions of Innovation. Digitization is causing resurgence in startups in all the digitization technologies. Innovation for new product and services need to be balanced through a partnership between innovation in execution (Process Innovation) as well as customer service and IT innovation through digital technologies. Digital innovation needs to be holistic but also continuous and embedded in the very DNA of the Digital Enterprise.
- Trend #2 Business Transformation Roles in Digital Enterprises: For innovation to yield concrete results, the adaptive enterprise needs to empower its human capital to innovate by revising existing organizational roles and creating new roles and cultures. There are emerging transformational roles including Chief Digital/Digitization Officer that are increasingly becoming more pervasive in digital enterprises. The priorities and focus of these roles (CDO, CPO, CCO, etc.) can also be assumed by existing more traditional roles such as CIO, CMO and COO – or might co-exist especially in large organizations. The roles span innovation and transformation roles to the more technical roles focusing on core digitization enablers (SMAC’T!). For Adaptive Digital Enterprises, two roles – or the focus and empowerment of these roles – are essential for success: the Chief Customer Officer and the Chief Process Officer, for end-to-end process simplification, ownership and simplification. In fact, it makes sense to coalesce these two.
- Trend #3 Modernization for Digital Enterprises: Think Big, Think Digital…but Start Small: Innovation and transformational roles are often weighed down by unwieldy enterprise applications and environments - the incumbent “legacies.” Rationalizing application portfolios, then simplifying with fewer data centers, platforms, and applications that improve IT efficiency need model-driven agility layer digitizing processes, business rules, decisions and integration. Such an approach with complete visibility of digital enterprise assets provides the perfect balance between home grown and point solutions. Often business is frustrated and procures solutions especially on the Cloud, creating “shadow IT” practices. For business and IT to collaborate effectively, the change through an adaptive digitization platform needs to happen. Digital enterprises can then embark upon a rationalization, simplification and digital modernization as a journey – with incremental innovative solutions.
- Trend #4 The Rise of “Things:” According to the Gartner 2014 Technology Hype Cycle, Internet of Things is at the peak of its hype - and will achieve plateau of productivity within five years. This is just about right, given the prediction of more than twenty billion connected objects by 2020. The Internet of Things has many names: Internet of Everything, Industrial Internet, Machine-to-Machine, and Connected Devices to name a few. One of the more creative and elegant characterization of IoT was captured in David Rose’s book Enchanted Objects and is as follows,
“I believe that enchanted objects … will transform the way people use, enjoy, and benefit from the next wave of the Internet— through embedding small amounts of computation, connectivity, and interaction into hundreds of everyday things that surround us.”
There are nuances to these terms and creators or proponents will definitely accentuate specific attributes of IoT. For instance, IoE emphasizes People-Process-Things-Data. According to Cisco, Process is an essential component of IoE – in addition to Things, People, and Data. A key requirement for the success of IoT is the end-to-end digitization of processes, connecting the objects to people, applications, and processes within the enterprise.
- Trend #5 Data, Analytics and Real-Time Decisioning: Called by different names such as “information explosion” or “Big Data revolution,” we are generating more data than any other time in human history. One of the main sources of this Big Data is Internet of Things. Through statistical and analytical techniques there is now the opportunity to leverage the hidden intelligence within the vast amounts of data, operationalize it, and create increasing real-time and responsive solutions. Organizations that are leveraging analytics in decisioning for customer experience transformation are exhibiting distinct advantages over the competition. Data can be mined using analytics to discover predictive models. Predictive models are useful, but they are always based on historical data, which means that decisions are made by looking in the rear-view mirror. A complementary continuous self-learning technique, adaptive analytics, elevates intelligence another (large) step further. It provides “self-learning” that can dynamically incorporate new information and insights in real time and automatically apply this current knowledge to the next applicable situation.
Part II will continue the recap of this year’s trends and conclude the series.