Digital Strategy, Operating Models & Technology Implementation Insight
Boost business success via insights on emerging trends in digital transformation and IT strategy; practical frameworks you can apply; and guidance from the world’s experts in leadership, IaaS, investment prioritization, operational excellence, sustainable innovation, change management, enterprise agility, and applying emerging technologies.
In Part III of this Executive Update series on design thinking and digital transformation, we examine the top challenges that arise from pursuing a digital transformation strategy and how design thinking tools and the design thinking process can help address these challenges.
In this article, Sagar Gole and Vidyasagar Uddagiri help you understand which fundamental concepts — specifically, the six elements of an enterprise-wide data architecture — you should address today in order to “overcome challenges and leverage the opportunities and benefits of digital transformation.” They describe the “secret sauce” that prepares your organization to thrive during a digital transformation journey.
So how do you put context-setting information at the center of your data architecture? Adrian Jones illustrates how to do this by putting Cutter Consortium Senior Consultant Barry Devlin’s architecture into practice. He stresses the importance of context-setting information by pointing out the increased vulnerability to which we are exposing ourselves. We produce and use more and more data. In the backs of our minds, we know that data governance is of growing importance, but we don’t act in the right way on this knowledge. The problem with data governance is that it is never part of a data architecture but rather addressed as a separate process. If our data architectures are not aware of the vulnerability being introduced, accidents are just waiting to happen. Jones hands you the recipe for avoiding these accidents.
This issue of CBTJ will help you understand that a data architecture should be much more than merely a technology roadmap. To be of any value to people in an organization, the architecture should guide the people in an organization to an understanding of how to organize for ever-changing information requirements.
Christian Kaul and Lars Rönnbäck explore what it means to adopt a data-centric paradigm. It certainly isn’t enough to have a data-centric data architecture; the implications are much more fundamental. The ultimate consequence is that you need to create a model-driven organization. By doing so, data architecture determines the shape of the organization, not the other way around. It’s a thought-provoking article, and best appreciated when keeping the context of the two previous articles in mind.
Barry Devlin takes us on a journey to help us understand how context plays a big role in using data. Known for creating the first data warehouse architecture, he proposed a new standard for data architecture for today’s world in 2013. Devlin puts context-setting information at the heart of all data architectures, and for good reason. In the drive to digitize more business processes, the intricacies of how all stakeholders interact with data have been underexposed. Though it is understandable that getting a grip on technology and reorganizing your business is hard enough, it is precisely this interaction that will determine your success. If you turn your perspective around, as he argues, your data architecture will be of more value.
In this Advisor, we consider the four types of blockchain and explore some financial services where blockchain can be used effectively to enhance customer experience and increase the efficiency of those services.
Working with blockchain over the past few years has made me realize the broad possibilities of distributed networks. Certainly, one could say that blockchain is “just” a distributed database; however, emerging adoption reinforces the potential underneath. There are myriad ways to adopt this technology, including in transferring funds, managing supply chains, handling tax evasion, and performing targeted analyses of data already recorded on the blockchain.