Making any organization fully crisis-proof is impossible. However, it is possible to make an organization extremely agile, thereby increasing its flexibility and resilience so much that it can weather the crises of an uncertain world. We believe agility is enabled by data-driven decision-making, and that such decision-making becomes possible when an organization has effectively governed data. In fact, because any company operating nowadays needs data, every company also needs data governance.
What is data governance?
Organizations have long been implementing data governance, even if they didn’t call it that. And yet, the concept has gained currency – and urgency – as companies today do more and more with data. Data governance simply means having rules and guidelines on how an organization structures and manages its data. Some may consider the topic boring, complicated, or overly time-consuming. But it’s simply a necessary component of digital hygiene and any business strategy. In that sense, calling data governance boring is comparable to calling a smoke detector boring. We might say that what fire safety devices are to a home, data governance is to a modern-day organization. Both systems ensure processes are in place to protect precious assets and enable quick decisions for staying alive and being able to thrive.
Data governance requires having clear, consensually decided-upon answers to fundamental questions. For example: who are the owners of the data within the company? And specifically, who is accountable for which data streams? Asking these questions is often something a CIO or a data consultant might do. As an IT partner, we can implement tooling to support the existing processes. As we see it, any IT solution should facilitate effective data governance. It should also cement what needs to be in place to make the data available and usable to the right people at the right time and place.
Save money and time
So why is data governance so important? It sets the stage for producing what we could call more “truthful” data. Getting absolute truth and proof may be impossible, but effective data governance supports processes that increase a collective’s confidence that numbers are correct and accurate. Good governance leads to good management, which leads to clean, checked, and verified data. What logically follows are better data analysis, data-driven decisions, and fruitful data-driven actions.
Incorrect or poor-quality data can lead to decisions that have ineffective or negative consequences. For example, a retailer might incorrectly forecast its budget because it has used the wrong data to make projections. Or a pension company might decide to invest in a certain market based on knowledge that is informed by bad data. Both hypothetical scenarios can result in major losses, hitting companies’ own profit and loss statements but also incurring expenses, should fines be issued by regulatory bodies.
Preserve trust and reputation
The potential devastation caused by bad data is more than financial. It can deliver a blow to an organization’s reputation and thus viability, especially if customer assets have been threatened or harmed. Bad data that leads to bad decisions doesn’t only affect a company’s end users. It also erodes trust of the staff who work within the organization and the boards and other stakeholders who make decisions for the organization. If different departments within a single company have incongruent data or disparate sources of data, colleagues are likelier to do more ad hoc manual work (think: Excel sheets). In “going rogue,” they may take up data projects on their own and use software or tooling that they prefer but which may not be sufficiently secure or compliant. In other words, the data has been gathered but not governed.
Such inconsistency can lead to divergent and/or conflicting data, and create multiple versions of the truth. The incertitude may result in staff relying more on their own feelings or intuition about a project rather than facts and figures. This can be problematic if people make less data-driven decisions and/or spend more time gathering their own data and creating their own truth. It is crucial, therefore, to come to an agreed-upon truth by coming to agreed-upon processes to verify that truth in the end. This tenet holds even when organizations don’t have data disagreements, discrepancies, or roguish tendencies. For an organization to adopt data governance, management must instill a data culture and train people to participate in it.
No more firefighting
Establishing data governance policy and management is part of basic data hygiene. What’s more, it causes less technical debt and incurs fewer monetary costs when it is built into a digital transformation, such as moving to or getting set up in the cloud or a new platform. This way, rather than having to refactor an environment after the fact, the data rules and regulations simply come with the territory. Finally, having effective data governance policy frees an organization from constantly being in firefighting mode. With no more fires to put out, the resources that were used to extinguish flames can instead be devoted to optimizing daily operations and doing more creative, innovative, and value-generating activities.
If firefighting is a thing of the past, a company can treat and appreciate data for what it is: an asset. In doing so, daily work becomes more enjoyable and the business starts to benefit. It creates opportunities for shorter time to market and greater, faster innovation because people can spend more time on activities that are exciting and financially promising. With effective governance in place, basic data hygiene also gets kept in check and data-driven decision-making becomes second nature. In that sense, data governance helps keep an organization – even in a world of much uncertainty – most certainly agile.
By Jochem van Leeuwen and Frank Buters