Data as a Business
The value and the risk of data are context dependent. It depends on how it is used. The comparison with oil is not sufficient. Data has an infinite usage, not consumable and simultaneously usable. Data owners have a particular context, but they cannot know all the ways in which their data could be used. On the one hand, unlocking the full value of data requires opening it up to all potential users firmwide and beyond. On the other hand, this exposure is very risky. New governance practices must open data access, to get the most value from data, without increasing the risk. The investment in information technology should be also progressive and justified by an actual return. Collaboration is key to unlocking the data value. It is not just about the data itself. To maximize the return, a composable architecture that allows the resources' reusage and combination with an ecosystem of component providers, is key.
Frequently, local domain data asset owners used to have full responsibility for risk and determining access. However, the risk and the return on data use are ultimately an enterprise concern that is better addressed by a consensus of a broader group of users. To clarify the roles and responsibilities of data owners, data users, and data governance body, it is necessary to reframe data ownership as data usufruct. This clarifies the roles and responsibilities and aligns the risk-reward incentives toward business goals.
[Usufruct is a legal concept that means the right to use an asset. A usufruct is a right conferred to a person or group, usufructuary, to use and derive income or benefit from someone else’s property. The usufructuary has the right to use the asset, but cannot significantly alter, damage, destroy or dispose of the property because it belongs to the proprietor.
The new governance gives data “owners” full rights to control all aspects of a data asset, especially risk determination, but not the access decisions. It is the data governance body that gives access to users and grants the right to use the asset as long as they do not “damage the data”; that is, use the dataset to violate existing data ethics, compliance or use-case agreed rules.
Use-case rules are especially important because data assets have many potentials uses that siloed data creators and users cannot foresee. These use cases representhuge potential benefits for the enterprise. Meanwhile, the data governance body reserves the rights of the data asset “proprietor”, the rights to assess value and risk, determine potential damage to the asset, and decide the right to access, only when there is a real business need. The data governance body is responsible, considering the assessment, to agree with users on the right and rules of usufruct in each use-case. The idea is to maximize the return, controlling the risk.
It is mandatory to prioritize the potential value of data assets and products from the perspective of data users. The investment in information technology should be progressive, aligned with the business strategy of monetization, and supported by an actual return. The ROI concept is the ultimate reason for investing in data preparation and sharing. It relies on the identification of the potential value of data assets and products from the perspective of the stakeholders who oversee the business units or initiatives that require the usufruct of data.
In the current scenario, companies that manage to organize and extract intelligence from the ocean of data acquire a decisive competitive advantage.
The potential value can be measurable or estimated, therefore leading to quantitative KPIs and metrics. It informs the business that the right to usufruct over a data asset has a business reason that balances the expected return on information with the appropriate levels of investment and risk. The concept of ROI is tied to the idea of data usufruct.
It is prime to understand the customer's (internal or external) needs. Sometimes, if it is a B2B, you may need to follow the chain until a B2C to understand the need. I like to think that this ultimate beneficial owner is the only one that feeds the chain with money. We need to understand what will make him pay for a product or service. This mindset will maximise the chances of business success. Collaboration with some key customers is very successful in this search for efficient investments. Break the deliverables and fail fast. Only after proving the value with a few customers, the escalation should be done. Those are, in the end, part of the ROI best practices.
More than your own Data
The race for data in recent digital years has transformed businesses and boosted a new market that has been essential to assisting in decision-making, optimizing costs and processes, and promoting increased revenue. In an increasingly digital world, the "footprints" we leave on the internet reveal a lot about our habits, interests, and consumption profile. In the current scenario, companies that manage to organize and extract intelligence from the ocean of data acquire a decisive competitive advantage, on the other hand, we have a great chance of being left behind. This new era in the market seems irreversible and should intensify in the coming years. As the world becomes more digital, data production, capture, and analysis are growing exponentially and require, not only a more advanced data analytics strategy but fired a hunt for external data to complement the decisions.
This scenario, naturally, triggered a race for people and technologies capable of transforming data into value. All large companies have robust infrastructures and a team of engineers and data scientists prepared for the challenge. But not everything is rosy, as it is a highly complex challenge. Some organizations understood that the data they had access to was limited and revealed a fragmented scenario. Others realized that there was a big learning curve ahead of them to be able to monetize data over time-based only on their expertise. Finally, we have no capacity to focus on all initiatives at the same time. Those who did not restrict themselves to looking inside their facilities discovered that working together with an ecosystem can accelerate and enhance their experience with data analytics. Imagine that databases, areas of expertise, and technology infrastructure are Lego pieces that can be articulated to give rise to infinite shapes. If you have parts of a single model, you can assemble them in different ways, but there is a limitation. If someone gives you assorted blocks, however, your possibilities grow exponentially.
Statements for Reflection
Monolithic governance will block your entering in digital era. Adaptation to risk is needed.
Access controlled by the data owner leads to siloes and is risky. Developing the enterprise controls and migrating to new governance are prime.
Centralised areas are overflowed and show frequently a gap in capacity and business expertise. We need to collaborate.
Make all your investments aligned with a business return and transform them into KPIs.
Connect with an ecosystem of data, applications, and services. Compose your offer with partners to anticipate the results.
Be sure that the customer will pay!