A wise man once told a cheeky arachnid, “With great power comes great responsibility!”
This is a particularly relevant quote in the context of the evolving data economy. CDO’s may think of themselves as caped crusaders saving mankind, and the truth is they are indeed playing an increasingly critical role to help ensure that organizations can successfully transition to their rightful place in the new data economy.
Consider the following:
- Overwhelmingly, CEOs believe leveraging data as an asset will be more than a game-changer, and will soon become a critical differentiator to remain successful and relevant – and not all companies will make it;
- Available data – both volume and variety – continues to grow at an impressive rate;
- Data science and tools are moving in lock-step with the data growth, finding new ways to derive value from data, creating transformative and disruptive opportunities;
- Data events – intrusions, breaches and exposures – are also growing at an alarming rate; in 2018 alone, hundreds of millions of people-related records have been targeted, exposed or breached (and that’s just the ones detected); and
- Regulators – notably the EU and the State of California – are responding with complicated requirements, that will impact a great majority of organizations, and more jurisdictions will follow.
What is the role of the CDO?
The CDO’s primary responsibility is to establish the vision and execute a strategy to leverage data in a responsible way. This ranges from monetizing data directly, through sale or licensing data, to creating new or enhancing existing products and services with data, to optimizing operations by augmenting decision-making with data. This is a tall order, and needs to combine insights into available opportunities, maturity of the organization to embrace change, and expectations of organizational Leadership with the support they provide. After all, if leadership isn’t on-board, a data program is not likely to be successful.
The other responsibility addresses meeting the obligations tied to the data, which starts with data ethics. Just because we can do certain things with data, should we? Consider some inputs to that decision:
- Harm– As with medicine, and as the business person overseeing data initiatives, the CDO should start from the commitment to “do no harm”. The CDO should have a methodology for analyzing and socializing potential data solutions to understand the potential consequential impacts.
- Legality– The CDO should collaborate with counsel to develop a clear understanding of where legal boundaries lie. As with “do no harm”, organizations should not break the law. The CDO has an important role, because sometimes there is legal risk (heightened probability that a law will be – or perceived to be – broken), and analysis presented to decision-makers should be clear. As with other cutting edge sciences, senior leadership may not be as data-literate as the CDO or the data scientists.
- Expectations– An initiative may be “legal” – technically – and even cause no actual harm, but the organization should be comfortable that stakeholders or clients would not be so disappointed with an outcome that the organization’s brand is impacted or clients go elsewhere. A consumer-client has a different tolerance level than client-companies; consumers take reactionary queues from society, media and social-networks, often with unpredictable results. Client companies have their own stakeholders, regulators and clients to look out for, which drive their reaction. Moreover, an un-harmful but “creepy” initiative may draw unwanted scrutiny from a regulator, resulting in the organization expending resources to address.
- Profit – will the initiative make money, even if risks are mitigated and obligations are met, and expectations are intact? A CDO will be presented (pitched?) with dozens of cool ideas, and has to know how to analyze them for fit within the organization. This is trickier than it seems, because data science presents data-oriented opportunities in organizations not used to the data economy. The decision-making process around investing in a new plant or product in, say, a manufacturing company may be very different than deciding to invest in a data-driven feature or capability. And simply “willing it to happen” isn’t enough.
- Consequences– Suppose the organization bets wrong. What if the initiative fails to deliver on the planned profit, or simply doesn’t work? This is manageable through various pathways – insurance, hedges, accounting treatment, etc. But what if the organization creates a proverbial monster? Recent debate around AI comes to mind, with AI appearing to evolving in lab settings. What if, in hindsight, the organization realizes they did something deeply wrong or harmful – should they have been expected to anticipate and alter course? Recently, companies have ceased to exist because they pursued what seemed like sanctioned or low-risk data-driven initiatives, failing to anticipate social and political outrage.
The data economy presents opportunities never before available to business. Some organizations will choose to gamble risk against profit. Others will take a step back and forego immediate opportunities, adopting a wait-and-see attitude. Some from each group will succeed while others fail.
Like any new science that affects humanity, data science should adopt a canon of ethics that balances achieving benefit against the risk of harm.
No doubt the CDO plays a central role in making or orchestrating decisions and administering data. As the steward of the data vision and strategy, the CDO must be able to think through the upsides and downsides with balance and objectivity and be willing to stand behind the ethics of decisions, after the fact.
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