A large part of any IT or data leadership job is to create a coherent strategy, fostering ongoing relationships and alliances with leaders and specialists in other fields. But if technical challenges are not clearly understood across those different fields, and often  dismissed, the best conceived strategies will fail to be executed. In 2022, I wrote these articles for Forbes Technology Council, and now I realise my audience had to reach beyond the technology community if the goal is to lower the barriers between disciplines in an organisation.

Becoming a fellow of the BCS and a chartered IT professional have given me a platform to speak at industry events, as a trusted voice for the IT (and data) disciplines. In my commitment to continuous learning, I have joined many opportunities to exchange ideas with peers in recent years – from business agility and sustainability to ongoing career and skills development.

Where were they before AI?

The moral compass of the organisation and its compliance with the law have always co-existed with the purpose of organisations. We may know this compass as company’s values, leadership tone, employees’ conduct, and brand perception. So why is ethical and responsible use of data become such a prominent concern now? Wasn’t it there before? Availability of data, cloud computing, and accessibility of AI have brought to light that the pursuit of profit is too tempting. Data leaders now need to "show" through data how ethical, compliant, and sustainable the organisation really is. To do that, data leaders may need a more candid partnership with the board, i.e. an open conversation about the limitations of data - data is not undisputed fact and may not even be a good representation of reality.

Data Governance, Privacy, and Quality

How can data leaders effectively drive compliance with regulation – and stay compliant – with a growing number of regulations on data, including the EU AI Act? I’m looking back at the recent history of data regulation and offering a friendly provocation to the data leaders’ community. Think like a public health professional: would you go around checking how every restaurant is preparing every meal every day? Or would you focus on giving professionals sufficient knowledge (contagions, pathogen transmission), access to training (hygiene habits, apprenticeship, certification), clear and simple rules of the road (standards), and checks and balances (surprise inspections)? We cannot make data conform with all expectations from all stakeholders by redesigning the system every time; i.e. this is not sustainable. But we can improve the complex adaptive system by shifting our focus to people and their interactions in our businesses.

The key to sustainable data practices

Data leaders can get the most out of their efforts by embracing the fact that large organisations are complex adaptive systems. To influence the outcome of the system, we must understand the agents (people) and their interactions (processes, systems, policies, and other unspoken norms). Implementing new technologies and systems of work often produce underwhelming results - despite some successes (we always shout about those!), the experience from the trenches is somewhat painful. The data leader has other options that don't look like either a "test lab" or a "multi year transformation".