It has already been pointed out on several blog posts that the use of data at the business level should be managed by business metrics and by those in charge of business. The higher this is managed in the organization, the more support, visibility, and priority the data your company will receive. It is also often emphasized that one of the key challenges for senior management is adequate knowledge of data matters and this is one reason why terminology is not properly understood and often the decision is passed on to the organization’s IT department and decision makers there.
It is therefore vital that every manager has a good understanding of the business opportunities that digitalisation brings in general, but also a basic understanding of the data-related entities. This of our “100 days of data economy” gives a good picture from many angles but we have also accumulated a good understanding of a few key things that every business decision maker should understand at least at the concept level.
The first to highlight are business models that are good to learn about:
Consumption-based economy. That is, when services are produced and consumed in real time. Data is collected and the service is modified as the customer's consumption changes or the need changes.
Platform Economy (and Platform2Platform). Many companies are currently developing platforms and bringing them together to develop a Platform2Platform business model that combines the best of different platforms into a unique business entity and generates value for multiple directions and parties simultaneously. Everyone is hardly worth developing their own or their own platforms themselves.
Cloud Services. While cloud services are already bulk or “de-facto” in many places, we still miraculously come across the fact that the management team has scalable digital business needs even though the company’s own services run in an unscalable local iron environment.
Data Economics. "All" consultants talk about data as a new oil or something similar and there are numerous highly successful examples of how data has a huge value for a company. No company can own all the data, nor can it collect all the data. So data must also be bought, exchanged and sold in the future. The data economy makes all of this possible, and believe me, you want to be among the first to be involved.
Next, a little more technological entities but with which modern business is made possible:
API Economy. Interfaces are often understood as the key to happiness. APIs enable functions and transactions between companies, businesses and different systems such as data exchange, process automation, event-triggered actions and much more. APIs are also a "gateway" to data. Many companies price interfaces and create a business for themselves. With the development of the data economy, there are also many parties who price but the data that is used through the interface but the API is free.
Data -> information -> understanding -> impact. When talking about data, it is important to look at how the use of data affects your business or return on value. Data is practically ones and zeros, and discussing it is often completely useless to businesses. One should understand how data is constructed into information that becomes understanding and this understanding affects something.
Low-code / no-code. One of the most promising trends in application development is low-code and no-code services, where all development is no longer done by writing hundreds or thousands of lines of code. Finally, the maturity of application development is starting to be at the point where drag 'n' drop interfaces can be used to make interface changes, new views or even new interfaces in minutes or hours instead of the development projects of previous months.
Serverless. You don't have to buy a server or an entire cloud environment for everything. In many cases, the needs are very limited, well defined, and implemented as a single element, and then you do not need a server or data center solution to run them, but a "serverless" implementation is sufficient, running the application without a complete server platform.
Microservice. One of the most important things to understand is the micro service environment. One possible model for building an agile and modular business model, as well as its various components, is the environment if functional services (micro-services) are interconnected, enabling value creation. That is, not complete, massive, and largely overlapping systems customized for you, but individual functions that are connected in a modern way into a whole that looks like you.
In addition to the above, of course, data-based business models, data management, artificial intelligence, machine learning and, for example, dynamic pricing, as well as the opportunities offered by modern business models (such as ecosystem, employee-centered and social business), should be kept close enough in innovation and strategy.