Enterprise-level organizations are often multi-layered, complex, and spread out over several departments and locations. Teams operating in different departments may be almost completely unrelated and have their own unique needs and objectives. As such, creating analytics and business intelligence tools for them usually becomes a piecemeal process of addition based on need.
The result is a BI system made up of mismatched parts and disparate tools that don’t often fit together neatly. Even worse, this makes it harder to derive insights and can bog down the process of enterprise analytics. The next time you look for a BI suite, consider these factors to ensure your next purchase is the last, and only, one you’ll need to make.
1. Take a Census of Your Full Organization’s Needs
The biggest reason why enterprise business intelligence becomes fragmented in large organizations is because specialized departments exhibit unique needs. As a result, purchasing and implementation decisions are not made at a company level, but rather by individual departments and IT teams. This is problematic for larger organizations that must constantly share data and communicate, but also navigate complicated tech infrastructure to do so.
Instead, the first step towards uncovering the right BI tool boils down to understanding what each team and stakeholder needs from their BI tools. As an alternative to making purchasing decisions in piecemeal form, take the time to understand your organization’s data needs and search for a solution that meets as many, if not all, of your stakeholders’ requirements.
2. Understand Your Organization’s Use Cases
Once you understand what organizations and teams need from their business intelligence tools, the next step is to identify specific use cases. While each department has unique needs for their data, they also reveal different requirements for what their BI must accomplish. Some teams may demand high-level visualizations and weekly reports, while others may want more day-to-day reporting tools and degrees of complexity.
The key is to identify a BI tool that is flexible, and powerful enough, to manage all these unique tasks simultaneously. Some BI platforms specialize in some but not all of these tasks, so finding one that checks every box requires research and a deep understanding of your organizational use cases.
3. Establish Your Data Streams and Requirements
Because each department displays different informational needs, they must each depend on different data streams. Some require real-time data—such as warehousing and logistics teams—while others may be amenable with historic data that is less time-critical. Most organizations will consider each team’s needs as unique, and find BI tools that fit one specific need but ignore the rest.
Concentrate on locating an enterprise analytics tool that forgoes specific data capabilities in favor of a BI system that can handle multiple data streams without being forced into a tight peg. Business intelligence tools that can process data flexibly and deal with a variety of connectors and channels are ideal, as they provide information and warehousing solutions for every stakeholder.
4. Ensure that Your BI Solution is Accessible By Every Stakeholder
Another reason why BI implementation tends to be scattershot is due to the accessibility of a system. Many applications that are highly specialized are not always user-friendly and can limit an application’s usability across an organization. These specialized systems also require teams to have specific employees to handle analytics needs, further segmenting their use.
It’s vital to discover a BI tool that is not just multi-faceted, but easily accessible. Organization-wide adoption requires usage, and stakeholders are more likely to adopt a system that is easy to operate and available when they need it. Therefore, it’s a strategic imperative to explore BI tools that are easy to learn and implement across different departments, without sacrificing power.
5. Make Sure it Can Always Do What You Need
Finally, many BI tools quickly become obsolete when organizations max out what they’re capable of handling. These limitations also result in organizations needing to purchase new tools to solve specific problems, adding applications as necessary. This creates a patchwork system that is capable of realizing certain objectives. However, the downside may be the creation of bottlenecks and complications elsewhere.
When you make your next purchase, focus not only on your immediate needs exclusively but on your organization’s growth and future requirements. BI tools can adapt and scale, but they require time and the proper implementation. More importantly, they must be flexible enough to match an organizations’ ever-changing needs.
The right BI tool will enhance your organization’s operations and simplify your data processing and collection needs. Before you make your next purchase, ensure you understand your organizational data needs to guarantee the next BI tool you buy is the very last.