What are the most valuable assets of a large-scale business? Skilled professionals, funding, technology, you may say. Though these factors heavily lie behind every successful enterprise, there is another asset without which even the brightest minds and biggest investments won’t get you far.
Data! It’s what makes all the difference. However, dealing with huge datasets is pretty complicated on its own, especially for industries like healthcare or fintech, which should strictly adhere to regulations in data handling.
Key Highlights
- By recognizing existing governance and turning employees into data stewards, non-invasive data governance sets a solid foundation for intelligent data management.
- NIDG formalizes employees’ responsibilities rather than replacing them, thus elevating their motivation and accountability.
- NIDG focuses on the most critical data first, then scales gradually across the entire data infrastructure, leading to a seamless governance rollout.
- Traditional governance can cost enterprises up to several million dollars annually, while NIDG cuts these costs by leveraging existing resources and workflows.
Many enterprises believe that creating a secure environment for sensitive data processing is enough. But intelligent data management requires more than just security.
It’s critical to clarify who owns and maintains data, as well as who carries the weight in case of issues such as data duplication or inconsistencies. Yet, defining responsibilities within an organization is rarely straightforward. Typically, this process is associated with massive structural changes.
There is a method that sorts things out with minimal disruption and maximum impact — non-invasive data governance (NIDG). Let’s jump right in and explore why it is considered one of the best data governance strategies for enterprises.
What Is Non-Invasive Data Governance, and Why Traditional Approaches Fall Behind?
Before going any further into our topic, let’s first compare traditional and NIDG approaches to see what makes the non-invasive method the better choice.
Traditional models manage data ownership and accountability through a centralized, top-down approach. Typically, it’s not about hiring people with deep expertise in data management, but rather creating high-stakes positions that duplicate the work already done by existing staff. Besides, this method considers rebuilding the existing governance structure or creating one from scratch.
This may lead to more overlap than clarity. Meanwhile, an NIDG framework simplifies things by turning current employees into formal data stewards and embedding governance into existing data infrastructure. As a result, businesses gain a team with clear accountability for data ownership, quality, and security.
“The emphasis is on formalizing people’s behaviors, not the behavior of data. Data behaves the way people behave.”
— Robert S. Seiner Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success
At some point, you may, of course, require some changes and new hires. But a non-invasive framework offers gradual changes. This makes data management less stressful and more flexible.
Learn about critical Enterprise Data Management Strategies
Enterprise data governance is a model that companies use to effectively manage large-scale datasets. Its main goal is to maintain data accuracy, security, and compliance.
Enterprise data governance becomes non-invasive when companies assign data-related responsibilities to their staff and integrate them into current processes, rather than hiring for new roles or overhauling existing structures.
Core Principles Making Non-Invasive Data Governance Click
Given that you don’t have to dig into deeper infrastructure changes to achieve advanced data governance, NIDG may seem like a pretty simple method. But in practice, getting it right takes deep planning. Non-invasive data governance is built around a set of core principles that make it all work. Let’s break them down:
- Govern existing processes: If your business handles data, some form of governance is already in place; it’s just not recognized as such. NIDG offers formalizing existing practices instead of building new ones. Let’s say you need data validation before finalizing reports. It turned out that your analytics team reviews variables at that stage. So, you already have a governance process and just need to make it official.
- Leverage existing roles: As we’ve mentioned, NIDG assigns data ownership to your current team rather than hiring new staff. The key here is defining them as data stewards. This means you have the same team, same work, just with clear ownership. Taking our earlier example, if your analytics team is already reviewing data before reports, it means the right people are already in place. NIDG simply gives them clear accountability.
- Expand gradually: Simultaneously governing a huge dataset would be extremely challenging. That’s why NIDG suggests focusing first on the most critical data, then scaling gradually. For example, if you process hundreds of variables through your enterprise healthcare solution, you can first apply NIDG practices to variables that directly impact compliance and revenue. Then, expand governance across your entire data infrastructure.
- Catch issues early: Duplicates in reports, inaccuracies in dashboards, compliance gaps… These are the most common issues that arise from a lack of timely intervention. NIDG provides peace of mind here as well. It builds proactive checks into your data engineering pipelines, such as validation rules that catch errors early on and automatically notify your teams about possible issues.
- Encourage communication: The last principle of NIDG is making data governance a shared effort. When no single person is carrying the entire burden of data responsibility, it fosters a culture of collaboration and communication across teams. Each department knows its role and works together to maintain data quality and consistency across the organization.
A data steward is a person responsible for data management and protection within their specific domain. By defining data standards, checking its quality, and ensuring consistency across departments, data stewards help prevent silos and improve overall analytics accuracy.
Why Non-Invasive Data Governance Pays Off?
It’s probably clear by now why NIDG is a perfect fit for enterprises looking to achieve effective data governance without turning everything upside down. You’ve likely already picked up on some of its core advantages, but let’s lay them out clearly.
Cut Costs, Not Corners
Traditional methods require utilizing governance platforms, data quality tools, and metadata management software, which can be pretty costly. NIDG, on the other hand, leverages existing resources. It mostly applies governance practices to the tools and workflows your company already uses. There’s no need to invest heavily in license fees, provide additional training for your staff to get familiar with new tools, or hire new roles.
But let’s get it right. NIDG doesn’t make technology irrelevant at all. It just removes the need to break the bank on new tools for tasks your existing tech infrastructure can already handle.
For example, if your organization already has data pipelines, data warehouses, or ETL tools, you can simply apply NIDG. If not, you need to integrate some critical techs prior to NIDG employment. With this in mind, we recommend assessing your infrastructure readiness before implementing data governance practices.
Higher Adoption, Less Resistance
After all, let’s admit that hiring top-down roles to handle the same work your staff already does can leave employees feeling undervalued. Why put in the effort when someone else gets the title? Which, frankly speaking, promises nothing good for your business.
Non-invasive data governance values the efforts of your staff, thus boosting their motivation and accountability.
Foundation for AI & Analytics
On top of that, accurately managed data speeds up the entire analytics process. There’s no need to allocate extra resources for variable cleanup or hire specialists to prepare data for analysis.
Discover how to Prepare Data for Powerful Analytics
The benefits of clean, well-structured data don’t end solely at streamlining analytics. It also elevates the input accuracy and trustworthiness of your ML models and AI algorithms.
To build a solid NIDG framework, start by auditing your existing governance. Then document the key responsibilities of your staff. Go on with the tools your team already uses or integrate user-friendly ones to make the adoption stress-free. Eventually, encourage employees to share feedback about processes and challenges. This will lead to continuous improvement of your governance practices.
What Could Go Wrong with NIDG, and How to Nip It in the Bud?
If you’re set on building a truly effective enterprise data governance framework, it’s worth knowing the pitfalls that could stand in your way. Let’s zoom in on the core considerations you may face when building an advanced NIDG, along with the most effective solutions to overcome them.
Lack of understanding:
Employees may think NIDG is a new system that will add additional requirements to their workloadPrioritize education over enforcement: Explain the nature and benefits of NIDG. Clarify that it recognizes their roles and responsibilities rather than adding extra workload
Balancing flexibility and control: Since their tasks feel the same as before, employees may take governance as optional and ignore some predefined standards on data management
Set clear policies and guidelines: Document how data should be handled at each stage, conduct regular audits, and provide ongoing feedback to ensure standards are strictly followed
Technology integration: If existing tools don't support governance requirements, you'll need to employ new ones, which can add complexity for your staff
Choose compatible tools: Opt for user-friendly tools that are also in line with your existing systems
Success measurement: As NIDG delivers long-term benefits, it can be challenging to measure its impact in the early stages
Define KPIs from the start: Set measurable goals like data quality scores, issue resolution time, and compliance audit results at an early stage. This will simplify the assessment of your NIDG framework
Taking the First Step Toward NIDG
How you govern your data is equally important as the data quality itself. We’ve explored why non-invasive data governance is a go-to approach among enterprises looking to achieve effective data management without disruption.
To get the most out of NIDG, it’s first worth having a clear picture of your current data and technology landscape. After all, without the right tech infrastructure in place, even the best governance models may fall short. We advise you to start with an enterprise architecture audit. It will give a solid picture of your current tech infrastructure and highlight where governance practices can deliver tangible results.
If you’re looking for a strategic partner to guide you through the entire process from tech audit to setting up a governance framework, get in touch.
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