Engineering the Switch to Digital: Are you prepared for 2020?
5 skills to master digital transformation
In the industrial age of the ʼ80s, the concept of business engineering emerged as computers and software evolved. It was guided by the principle of transactional, stable processes executed in large corporations. Information technology (IT), often introduced as enterprise resource planning (or ERP), was viewed as an essential resource to support traditional operations by huge IT departments.
Let’s face it: The world has changed since then.
Today, information technology is purely a commodity. It is available everywhere, with almost no limits and an increasingly affordable price tag. Everyone — both individuals and corporations — has it. You can switch it on and off. Everywhere, every time. The internet has even lost its fun — an evidence that it has become a basic commodity.
Today, the vital resource is data, not capital. Processes are no longer stable; they need to be customized at an exponential rate of change. IT systems built during the past three decades inevitably (and understandably) fail to manage the rapid change required by business. Today, robots — available 24/7 and with seemingly infinite scalability — can process work activities faster and more accurately than humans can. And artificial intelligence can think faster and smarter than we can imagine.
Managing the switch to digital is not possible using outdated concepts from the ʼ80s.
Today’s approach can be described as “Digineering,” an adaptation of classical engineering concepts for use in the digital world.
Digineering — A revised approach to business re-engineering?
Let me try to put it this way: “As we near the 2020s, digital opportunities are transforming organizations to the same degree as information technology once did during the 90s. These changes include process-digitization technologies that allow for near-zero-cost operations, robots that use a variety of digital services to streamline processes while managing human input, and artificial intelligence (AI) that automatically adjusts robot and human actions to execute work in a dynamic context. Additionally, data will replace capital as the vital element within this digital transformation. All of these, working together in a digital operating model, can create a new way to reengineer your business by changing the skills necessary as well as the way you do business.”
1. Process Digitization
Break down your process activities into simple steps that can be automated using electronic microservices running on a serverless infrastructure that is fully scalable to volume, allowing you to perform digital processes at near-zero cost per transaction. Develop semi-informational processes that include automating previous manual activities using robotic processes.
Knowing your processes is a vital to digitizing your business.
Robots are the modern interface between humans and digitized microservices and have the ability to change human interactions and communication into digital processing. Using queries, they can accurately coordinate the data and information flow between services at unseen speeds while operating 24/7.
Robots are vital for managing digital services and ensuring communication between artificial intelligence and humans.
3. Artificial Intelligence
Prebuild logical big-data analysis routines that can identify exceptions and prevent system failures. AI mechanisms can predict the future based on the past and make decisions based on prior data. AI ensures that robots and services operate in a dynamic, ever-changing environment by continuously monitoring the data flow and automatically adapting processes and robots to prevent failures from occurring.
AI is the future brain that combines robots and digital processes to keep your business structure going under changing conditions and environments.
It’s not about money and earnings anymore: capitalism fades away and data has become the new asset. Business models will be valued for their data instead of physical assets. The way we control, steer, and operate businesses must move away from shareholder value models based on earnings toward customer value models based on data.
To generate revenue streams, business models must be based on how they produce, maintain, and add value to data.
5. Digital Operating Model
The digital enterprise architecture puts this all together in a digital operating model that creates digital processes, operates robots 24/7, and adapts automatically based on AI findings. This kind of operating model generates revenue streams by creating data-centric customer value.
The digital operating model, formerly known as an enterprise architecture framework, is based on the interaction of process and IT management. You can’t manage processes without IT, and you can’t manage IT without processes. These two traditionally separated disciplines need to be blended into a new management discipline: digital management.
The management layers of a digital operating model are customer value, processes, IT, and data.