Data visibility in IT operations is like having a clear map of your complex IT landscape. It's the ability to readily access, understand, and analyze the vast amount of information your systems generate, painting a comprehensive picture of your infrastructure, applications, and user behavior. This clarity is the lifeblood of effective IT management. Think of it as the difference between navigating a treacherous mountain range with a detailed map and a compass, versus stumbling through blindfolded, relying on intuition and guesswork.
Imagine a critical security patch for a widely used software sitting unapplied, simply because the data showing its vulnerability got buried in a sea of irrelevant logs. Or picture an employee missing from a crucial Okta group due to an invisible gap in user provisioning. This oversight can lead to access issues, hindering employee productivity and potentially leading to critical security lapses. These are just two examples of how data blind spots can turn into gaping security holes and operational nightmares.
What is data visibility?
Data visibility is the measure of how easily data can be accessed, understood, and used by those who need it. It's not merely about having data; it's about making that data actionable and insightful.
Why should IT teams care?
Proactive Operations: High data visibility allows IT teams to anticipate and tackle issues early, supporting strategic planning and resource allocation. This proactive approach prevents problems from escalating and ensures smoother IT operations.
Enhanced Productivity: Efficient access to and management of data lead to significant time savings and streamlined operations. This not only boosts the productivity of IT teams but also empowers other departments by reducing their reliance on IT for data-related inquiries.
Compliance Assurance: In an environment of stringent data regulations, clear data visibility is crucial for compliance. It enables IT teams to effectively track, manage, and protect data, ensuring readiness for audits and reducing risks related to data breaches and privacy violations.
Now that we’ve established data visibility is something IT teams should care about, how do you know if your team has a data visibility problem? Here are 7 signs to watch out for.
1. Data is inconsistent across various sources
An IT team uses Azure AD for user identity management and Slack for team communication. An employee recently promoted to a new department is updated in Azure AD, but this change isn't reflected in Slack. As a result, they continue to receive irrelevant messages from their old department and miss critical updates from the new one.
This indicates a lack of data sync between different systems (Azure AD and Slack). Such data inconsistencies can lead to confusion and inefficiency, impacting productivity for both employees and the IT team.
2. Data retrieval is a pain and takes forever
An IT manager needs to generate a report on software licenses used across the organization. However, this information is scattered across various SaaS applications, and compiling it manually is time-consuming.
When data retrieval is a slow and arduous process, it hampers the IT team's ability to make timely decisions and respond quickly to evolving needs.
3. Data is siloed across different teams & systems
During the onboarding of a new developer at a tech company, the IT team faces challenges due to siloed data. While Azure AD is updated with the developer's personal and role information, their access to project tools and Slack communication channels, managed through separate systems, lags behind. This results in the developer having network access but not the necessary project or team communication permissions, delaying their effective integration into the team.
The lack of a unified approach in handling new employee access rights leads to operational delays and extra workload for the IT team, impacting overall productivity and onboarding smoothness.
4. IT is reactive and not proactive
An organization only updates its device management protocols in response to incidents like device malfunctions or security breaches, rather than proactively based on data trends and alerts from these tools.
A reactive approach, as opposed to a proactive one, means the IT team is always a step behind, dealing with issues after they've occurred rather than preventing them.
5. IT is dealing with a lot of data requests
Department heads in a software company often need data about their team but the data is spread across various systems. Since they cannot (or don’t want to) access this data themselves, they frequently request IT teams to compile this information. IT ends up dealing with such requests distracting them from their core tasks.
This highlights the inefficiency of over-relying on IT for routine data queries, impacting both leadership's decision-making speed and IT's productivity. It underscores the need for direct data access for key decision-makers.
6. Adding a new data source is difficult
An IT team adds a new project management tool to their stack to improve task tracking and collaboration. However, integrating the data from this new tool with the existing time-tracking and billing systems is difficult. The lack of integration across tools means data must be manually transferred or reconciled, leading to errors and inefficiencies.
When new tools are not easily compatible with existing systems, it results in additional workload and potential inaccuracies, highlighting the need for a more adaptable and integrated data infrastructure.
7. IT team relies on spreadsheets
An IT team uses spreadsheets to compile and manage data from various tools and systems, such as device information from device management software, user accounts from Azure AD, and software licensing details. Over time, these spreadsheets become increasingly complex and difficult to maintain, often resulting in outdated or conflicting information.
The dependency on spreadsheets for IT data management means there's no access to centralized, real-time information, leading to delayed decision-making and a heightened risk of errors due to manual data handling and difficulties in reconciling disparate data sources.
The problem with data visibility is not very (no pun intended) visible, but its effects certainly are. It's unfortunate that even with all the right data in hand, many IT teams still struggle to put it all together in a way that's easy to use and understand. It's like having all the pieces of a puzzle but not being able to see the big picture.
It's time to think about bringing in tools that can help. There are systems out there designed to make data more accessible and manageable. Adopting these tools can make a huge difference. They can simplify the way data is handled, making it easier for IT teams to get their jobs done and for the whole organization to benefit from the wealth of information they already have.
