– Improve cooperative working exploiting complementary knowledge
CDTs can be considered as active knowledge repositories: the keypoint is “active”. They can establish relations with other CDTs and explore the cyberspace to become aware of new knowledge and how that knowledge complement / obsolete their own knowledge.
Within a firm there can be a number of CDTs (even a big number!) such as:
- a CDT mirroring the firm knowledge
This is the CDT that clusters all the knowledge making the company “unique”. It interacts with all company’s CDTs and with the company ecosystem plus with any party that is interested in establishing relation with the company, like prospective clients, suppliers…
- one CDT for each of the firm’s projects;
These CDTs are accumulating knowledge needed and generated by a projects, starting with the design phase up to the product testing and interact with the processes (supply chain, manufacturing, delivery, operation monitoring, customer care…);
- one CDT for each of the firm’s processes
These CDTs are mirroring the operation of the firm and in turns can be structured in a hierarchy as one process may be composed of several sub-processes. They mirror the “how”, the status of a process and can be used as controllers (usually via external applications). They can also be used to simulate a process and the impact of changes on the process. These CDTs are particularly important in a firm business since a company effectiveness depend on their processes.
- one CDT for a product line
This CDT is mirroring a business aspect, the cost/revenue sheet of a product line and can be used both for business monitoring and for marketing monitoring. It is usually related to a business division within a company;
- CDTs instances for each produced product
These CDTs are created at the time a new product is assembled, accruing data on its manufacturing (thus initiating the digital thread for that product instance) and on through the delivery, customisation, operation, maintenance till the point of recycling/decommissioning.
It is a very important CDT since it is the one that contains the insight on the product use and can govern the relationship with the client/user. Additionally, it can provide feedback into the design of new product releases, upgrade offers, service offer and in the design of new product lines;
- one CDT for each supplier and one for each reseller
These CDTs mirror the knowledge of the parties interacting with the firm over the value chain, from the point of view of the company contractual links. Each CDT in principle could interact with the external company CDT and represents a subset of that company CDT that becomes more and more aligned with that over time. Actually, a company may decide to release (part of) its CDT to a supplier/reseller to facilitate interaction in the cyberspace. Smart contracts can be used to support and regulate the interactions;
- one CDT for each employee
The knowledge of each employee can be mirrored by a CDT “owned” by the firm (usually the owner would be the HR department). This CDT accumulate data mirroring the knowledge of an employee experience and may be created at the hiring interviews. It is not the employee personal CDT. That remains (if it exists) in the person’s ownership. As discussed later the two of them may interact and clearly the company’s employee CDT becomes more and more alike to the person’s CDT. This is a grey area that will require regulation, as is the case for the ownership and exploitation of patents.
The firm can decrease cost and increase efficiency through the adoption of a CDT based operation model. Today most companies are already relying on data for their operation and this reliance will become greater and greater in the coming years. The whole concept of Industry 4.0 is heavily based on data. The shift towards a CDT based operations requires the shift from a data base model where data are stored to a agent based model, with data encapsulated in agents and made available through APIs. This offer more flexibility in the control of access and use of data since in principle data are not released but information over data are provided based on the context. This ensures control and the same request to access a data may generate different responses depending on who, when and why the query is made. Notice that this is already a standard practice in modern search engines. When the same query is submitted to Google by two different parties (sometimes even by different terminals/locations) the answers will differ. Answer will also differ based on the time and on the repetition of the query. In other words the search is context dependent. The same happens with CDT (not with simple Digital Twin: it is the cognitive part that makes the difference).
Being an agent it can be used to generate revenues through paid interactions. As mentioned smart contracts and blockchain are important to create a revenue stream since they provide security and accountability.