Digital transformation is the application of technology to modernize business processes, activities, models and strategies with the intent of making the company more competitive and/or more profitable.
Originally published by G2 Crowd
There are at least five major business areas that can be modernized using the combination of technology and data: two related directly to strategy, and three that are more process- and activity-based.
Those areas are:
- Business models
- Business strategy
- Customer interactions
- Business operations
Each of the three activity areas are unique, but they are all interdependent, so modernizing one often requires efforts in the other two. Business models and strategies drive modernization in the three activities directly. The modernization process can start at the business model and move to strategy, or can be a change/modification of the strategy that then drives the three activity areas. It’s also important to note that technology changes should be accompanied by process change to optimize the impact of the changes.
Business-model innovation is arguably the most impactful change that the growth of the internet has enabled: There are any number of examples from Amazon to Uber. While the most obvious examples are from companies that were started and grew up as “digital native” companies, there are also good examples from “pre-internet” companies that have used business-model innovations as a means to drive the overall change in the business. There are also some high-profile examples of pre-internet companies that did not adjust to the disruptions and make the shift to a modern, digital business model or strategy.
Digital transformation is driving business change and technology innovation.
A simplified example of a company that is modernizing a business unit might help understand the concepts better. General Electric (GE), a company that is nearly 140 years old, has been on a digital transformation or business modernization path for several years now. That path has touched all business units and changed GE’s workforce, the way it engages and interacts with customers, and its business operations.
Take its aviation division, which manufactures jet engines as one product line. The legacy business model was based on selling jet engines to airlines. To modernize this model, GE has shifted to what it calls “executing critical outcomes” for its customers. What this actually means is that instead of selling a jet engine, it sells guaranteed up time. That shift drove massive changes in the aviation division.
For example, GE is now one of the largest companies in digital platforms, software development, artificial intelligence (AI) and internet of things (IoT). To accomplish the shift, it retooled its workforce by adding software developers and technology experts across a range of skills. It also built and launched a digital platform, Predix, as the underpinning of the new strategy. To sell outcomes rather than engines, the company had to find new ways to ensure asset reliability through increased monitoring using IoT, analysis by leveraging AI, and predictive actions. The change also came with business operations changes to support a subscription financial model over the old transaction-based model, as well as a long list of system changes to manage customer interactions, workforce activities, etc.
Digital transformation, then, is driving business change and technology innovation. Over the past few years, several technology trends have emerged or accelerated as a result of the modernization needs of businesses. For 2018, G2 Crowd research is tracking a list of these tech trends, and we’ve identified four broad technology areas that serve as the anchors or framework for ongoing analysis of technology trends, and their impact on modernizing businesses.
These technology anchors are:
There are a lot of other technologies, of course, but they are taking a supporting role for these four anchors in many use cases.
which includes machine learning, deep learning, neural networks, image recognition and natural language processing is having an impact across all of the software stack and leading quickly to “intelligent systems.” The rapid increase in the use cases and the need for more complex algorithms have created a skills shortage which will be a short-term limiting factor, but will generate a lot of opportunity as well.
AI is quickly moving past simple automation, predictions and decision support to prescriptive systems and autonomous action. There will be many issues to resolve around that shift, as autonomous vehicles become common and self-programming systems evolve, including the necessary ability for the AI system to document and explain its own code and actions. All of the evolution of AI, though, is dependent on the accuracy and availability of data. AI enables and relies on moving from “big data” to smart and small data to properly execute its models.
is an enabler of all sorts of innovations that involve the need for data from remote physical entities. Edge computing is evolving around the growth of IoT sensors to move much of the processing nearer to the sensors themselves to increase efficiency. The GE example relies on IoT as the source of much of the data needed by the Predix platform to manage risks and provide the desired business outcome.
In the midst of all the high-profile security breaches and issues in 2017, cybersecurity is, more than ever, a business topic of great interest. 2018 will see cybersecurity broadly incorporating AI to attempt to level the playing field created by an exploding number of bad actors, including those that are state-sponsored. Intelligent security has potential to, at a minimum, keep businesses on some par with the growing number of black hats.
The rapid evolution of digital platforms and the broadening of what they include is a big factor in the modernization efforts. Many functions are moving into the foundation as the technology landscape is increasingly cloud-based and composed of smaller building blocks called microservices. The modular platform provides services for the other technologies and is the underpinning to a new flexible and adaptable business system architecture. The platform can provide utility services and can provide access to transactional frameworks such as blockchain, AI and other analytics, as well as system management. With the concept of “serverless,” there is a move to reduce or eliminate the IT management overhead by moving it out to the cloud platform vendor, freeing up business resources to concentrate on adding business value.
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