Within the Big Data and Internet of Thing (IoT) phenomena there is a concept that is gaining its own identity: Industry 4.0. This concept refers to the implementation in industrial processes of technology based on Data analytics and artificial intelligence, in conjunction with the interconnection of the different units of the industrial process for the purpose of facilitating its progressive automation.
Take for instance a hypothetical IoT-related technology that may allow a company in the fashion industry to implement an expert system that informs its logistic warehouse when any of the company’s stores around the world is running out of products. The expert system will immediately transmit the order to start the packaging and the loading of spare units in the means of transportation. In addition, the expert system may also inform the factory of the need to manufacture new units of the product. All these data interchange can take place instantaneously, with minimum human intervention, and regardless of the geographic location of each of the establishments of the company. Finally, it can be the case that the manufacturing, on one side; and the packaging and loading of the product sin the means of transportation, on the other, are carried out totally or partially by robots.
The technologies associated to Industry 4.0 are all based on the collection, treatment and analysis of huge amounts of data. The more data a company has, the better its position to compete in the market. This is so for two reasons: the data can provide information that is vital to optimize industrial processes; new opportunities are opened to develop innovative products and services based on the analysis of that data. Because of these, ownership and access to huge amounts of data has become a necessity in the framework of Industry 4.0. This is why the media talks about the new lifeblood of capitalism.
When data is generated, processed and analyzed with technology (being sensors, devices or software applications) that belongs to the company, their managers shall decide on two questions in relation to the management of that data: how to ensure its ownership; how to commercially exploit it to extract its maximum value. In this respect, it should be bear in mind that the technology can be protected by patents, utility models and copyright in the case of software. However, data is more difficult to protect. As we have analysed in a previous post, the protection as a trade secret seems to be the most appropriate. This implies the need for the Company to adopt the necessary legal and technological measures to ensure the confidentiality of data. Furthermore, the attribution to third parties of access to this data requires the adoption of the necessary contractual measures to keep the data secret and to restrict its use.
Data management gets more complex in situations where the company needs to acquire technology from third parties for the collection, treatment and analysis of data. In these cases, an adequate negotiation of the license agreement for the exploitation of that technology is essential to ensure that the company retains ownership or access to data. This has two implications. On the one side, the contract should state that ownership of the data collected and analyzed belongs to the company. This cannot be given for granted: contrary to what happens with intellectual property rights, in the absence of a regulation within the contract, there is not a default regime that determines who owns data. On the other side, data collected and analysed should remain under the control of the company, i. e. it should be stored in its cloud, or at least, in a cloud the company has permanent and unconditional access to during the duration of the contract and once it has expired.
Returning to our previous example, let’s assume that the fashion company hires the service of an external technology provider to develop the intelligent system that connect all the company’s units. If data remains under the ownership of this external provider, it will be in an excellent position to use that data to develop services to other companies in that sector in relation to times of manufacturing and transportation of each category of products, mostly-used sizes in different parts of the world, the kind of clothes that are preferred in each part of the world, etc… The fact that such data is not under the control of the company, means other companies in the same sector may benefit from it.
Certainly, there are alternatives to this scenario. Having in mind the development of Industry 4.0 is at its initial stage, the most interesting scenario is one where the company looks for partnerships with technology providers in the form collaborative agreements or the creation of start-ups for the joint exploitation of data with the purpose of developing innovative IoT-related products or services that might be interesting for other companies in the same sector. This brings us once again to highlight the need to pay much attention to the negotiation of the terms of the agreement related to ownership and access to data.
Unfortunately, it would usually be the case that the technology a company aims to implement in its industrial process belongs to different providers. In our example, the technology to interconnect the stores with the warehouse may belong to one provider while the intelligent system that governs robots in the factory is offered by another. In these cases, the company would need to negotiate agreements with each of the providers. For doing so, it is essential to clearly define in advance a uniform strategy where the company’s objectives in this new sector of activities must be identified. The success of company in the nascent Industry 4.0 sector depends on it up to an important extent.