By: Ryan Ayers
Today, nearly every action taken by a consumer generates data, and the price point of data analytics technology is now within the budget range of most small-to-mid-sized firms.
Your competition’s rigorously analyzing consumer behavior, and if you’re not – your organization will get left behind. Before you can level up your data analysis capabilities, however, you need to figure out what business intelligence tools to use as well as how your organization works with information.
Customizing Business Intelligence for Your Team
Start assessing your enterprise’s data analysis needs by thinking about the end-users. For example, consider the type of dashboards and reports employees will need as well as the analytical functions that users have the skill to perform.
By providing employees with the tools that they need for self-service analysis, you can empower them to find answers without the help of your IT department. As a result, the new tools will make employees more self-sufficient, and IT personnel will have more time to work on strategic initiatives that will move your organization closer to its objectives.
You should assess how you will integrate data analysis tools into workflows and how they will bolster business intelligence. By developing end-user personas, you can figure out how to match available big data resources with employees’ skill sets. You’ll also need to think about the compatibility of your existing business intelligence tools, as well as how employees need to review structured reports – for instance, as a dashboard or data visualization.
Moreover, you must consider how staff members will work with the technology. Will employees need to customize their dashboards, or should you provide them with static information? Also, you’ll need to think about whether employees need to access more detailed data – for instance, by clicking on objects in the dashboard. Finally, you must think about whether employees will need to create personalized queries, visualizations and reports that they can share with organizational peers.
Planning for Data Success
While your new data analysis solution needs to work with your existing business intelligence system, you want to invest in a system that you can scale up as your organization evolves and grows. For instance, make sure that your new BI tools work with the primary data sources supported by your current information management solutions. Also, make sure that programmers can access, or develop, and implement plug-ins or application programming interfaces (APIs) as needed.
Furthermore, you’ll need to assess your real-time reporting and data caching needs as well as whether employees need to query information directly. You’ll also need to assess whether personnel will need the ability to manipulate data to complete various tasks.
In addition, you must think about advanced project management features. For instance, it’s helpful to choose solutions that support DevOps tools and practices for the continuous and iterative rollout of business intelligence system upgrades.
Accordingly, you want to look for a data solution with ample native development resources. Your big data tools should enable rapid development as well as the deployment of minor changes – as well as significant changes that may affect your entire legacy system.
You should also ensure that your new BI system is capable of rapid deployment and scalability within your current technology architecture. It’s also a good idea to consider what barriers your organization has faced before in adopting analytics and make plans to avoid those bottlenecks during the new deployment.
Pulling It All Together With Embedded Analytics
Some final points to consider when shopping for an updated business intelligence system are embeddability and personalization. Think about whether it’s more beneficial for your BI tools to exist within the current workflows of employees.
If your organization isn’t already using embedded analytics, you should assess how the feature can benefit your enterprise. By embedding BI into the right existing technology architecture, you can help employees make phenomenal advances in productivity.
Embedded analytics is a better way to empower employees to make use of real-time data. It can help you to promote information-driven decision-making. As an example, imagine that your sales department relies heavily on a CRM tool such as Salesforce.com. In a fast-paced sales environment, your employees may not have time to divert their attention from Salesforce to work with a separate BI tool.
An embedded BI resource can live within a current application, such as Salesforce – negating the need for employees to divide their focus between programs while at the same time giving them access to vital information. If you embed business intelligence into common resources, you will compel staff members to make use of valuable, up-to-the-minute information.
If you’re not familiar with business intelligence, now is the time to learn. You can upskill your executive toolkit by taking an online business analytics degree course to get you up to speed quickly.
Overall, it’s essential to look beyond how you will deploy a new business intelligence system. What’s more important is making sure that the tool you choose is versatile and adaptable for a range of projects.
It may take more work to find both a flexible solution and one that will work with your existing legacy system. However, the extra time that you spend on planning now will pay off handsomely in the future.
About the author
Ryan Ayers has consulted a number of companies within multiple industries including information technology and big data. After earning his MBA in 2010, Ayers also began working with start-up companies and aspiring entrepreneurs, with a keen focus on data collection and analysis.