This editorial considers how three new technologies and innovative processes may impact enterprise transformation projects such as outsourcing and back office innovation. These are:
- Cloud Architecture and Data Privacy
- Artificial Intelligence, Data and IP Ownership
- Agile Project Management and Relationship Management
Digital Transformation Opportunities and Legal Issues
1. Cloud Architecture and Data Privacy
Exploiting advancements in cloud-based tools and delivery models may benefit the enterprise. Cloud-based storage and the opportunity to buy storage as a service from a cloud-based platform may reduce the need to make capital investments in storage equipment.
Questions to Consider: Does the physical location of the cloud infrastructure matter with respect to storage-on-demand services? Similarly, does the footprint of the network used to deliver services raise legal issues?
Issues to Address: The location of cloud infrastructure may make a difference and the footprint of the network underlying this solution may raise legal questions. Compliance with applicable data privacy laws may be one key concern. For instance, your enterprise may have a footprint in jurisdictions where data related to individuals is subject to data privacy laws or data residency laws. These laws may require that your enterprise knows where this data is processed and stored and may require that your enterprise puts in place minimum protections for the privacy and security of this data. In addition, depending on how the network is designed, locating network assets or storage devices in particular geographic areas may provide local authorities and courts with jurisdiction over access to the information transported or stored on or through those assets. Therefore, understanding the footprint of the various solutions is critical and an important factor to consider in evaluating proposed solutions.
2. Artificial Intelligence, Data and IP Ownership
Collecting data about how services are used and generating analytics regarding such usage can drive transformational improvements in order to optimize service delivery and reduce costs.
Questions to Consider: Who owns the data that may be collected or generated by the service provider regarding your enterprise and its employees', visitors' and customers' use of services?
Issues to Address: It may seem that service related information should be owned by your enterprise, since your enterprise is paying for the services, the information is generated from the services being provided for your enterprise. On the other hand, data analytics solutions that make sense of such data are generally delivered by service providers through tools operated by the service provider, using algorithms developed by such service providers. In addition, usage data is processed and stored by the service providers in cloud infrastructures licensed to such service providers by third parties.
As a result, it may not be clear, as a matter of law, who owns the data that may be collected or generated by the service provider or, for that matter, what ownership means in this context. The data, particularly in an unstructured format, is not protected by copyright and, even in a structured format, may not qualify for much copyright protection because it is factual information. Data and the data analytics derived from such usage may also not qualify for trade secret protection. Although the parties could maintain the secrecy aspect of trade secret by contract (i.e., agree that data and data derived from the analytics is your enterprise’s confidential information), the data may not derive independent economic value by providing any competitive advantage to your enterprise.
Your enterprise may want to negotiate upfront with the service provider any allocation of usage rights and restrictions on such data and the analytics that may be derived from such usage data that your enterprise expects to have. If the contractual agreement is silent or vague around such rights, your enterprise's expectations may not be met. By identifying this issue during the solutioning phase and having the allocation of usage rights be part of the initial discussion, the parties could avoid potentially substantial conflict later in the relationship regarding the allocation of usage rights and restrictions and intellectual property ownership.
3. Agile Project Management and Relationship Management
Questions to Consider: What are the implications between choosing a traditional project development methodology (i.e., where the process is codified in the contract with a project kick-off, planning, detailed design, development, and testing stages) versus a more agile project methodology (i.e., the parties would manage projects using an iterative process intended to deliver minimum viable products in a more compressed timeline)?
Issues to Address: Under an agreement based on a traditional project development methodology, the project deliverable warranties would provide that the project deliverables will function in accordance with their specifications. The agile methodology may not provide as much detail around product specifications as more traditional models. However, the process should still provide some meaningful criteria that the project deliverables should satisfy. These criteria may be used as the standard to measure the quality of deliverables and to form the basis for the deliverables warranty. That said, the project management process set out in the current outsourcing agreement should be revised to reflect the agile processes preferred by your enterprise.
Digital technologies are changing many of the key business drivers behind transformational projects. Such projects are significant catalysts enabling enterprises to take advantage of digital transformations. These new opportunities raise interesting legal questions. Having legal counsel engaged early in the process helps to identify the issues raised by these new technologies in digital transformation projects.