Business Intelligence plays a BIG role in your startup!
Business Intelligence (BI) is growing in complexity and power, but it’s still only in its infancy. Until very recently data analysis was left to a very select group of analysts, IT and R&D professionals. As an employee, anything you wanted to do with corporate data would have to go through these all-knowing gatekeepers within the organization. But now things are changing. The same Shadow IT trend that is transforming the role of IT within organizations is happening to BI. The everyday business user is suddenly being empowered with tools that are restructuring the way analytics is done in organizations.
IT in the Shadows
Shadow IT is a broad term that describes IT systems and solutions that are used or built inside the organization without explicit organizational approval. Basically any program or software used within a business that was not sanctioned by IT falls into this category. They did not develop it, or were not aware of it, and the department generally does not support its use. For example, when the marketing department doesn’t want to wait for IT to approve their new social media tool, they just download it and start using with getting definitive permission. In startups and small businesses this happens tenfold, as there’s often not clearly defined guidelines or “person in charge.”
So what does this have to do with BI? Well the same thing is happening with business intelligence software across many organizations. Business users across markets and companies are bypassing the “responsible adult” when it comes to analytics tools and going at it on their own. The use of strategic analytics is accelerating across businesses and among business users with readily available self-service software and programs. With the huge range of these, it’s no surprise employees are taking advantage of the single-click download or sign-up.
Most of us recognize, and probably use, any one of these common analysis tools: from the basic Excel and Google Spreadsheets, to Adwords and of course Analytics, to Splunk or CRM software like Salesforce. Sure, they are all useful and contribute to each company or department’s competitive edge. But having four platforms open, and trying to gain insights from each one on its own is not the ideal way to do analytics. While many users can get a basic report done with the tools they have, when it comes to complex questions that require a lot of data or data that comes from a variety of source they are still stuck with going to IT.
Often this problem is exacerbated by the lack of an overarching data strategy within organizations. When there is no official BI tool to service employees, the whole company is being held back from gaining insights because it is doing fragmented analysis: different departments and users with different data, multiple platforms that all create disconnected data, and little possibility for collaboration. In the startup world, there tends to be a smaller staff usually of a more technical problem. This means a lot of the time that there is less strategic business planning, and decisions are made more on the fly. Particularly in these environments, there’s less set roles, and everyone dips their hands into all kinds of work – on the one hand increasing the creative approaches to finding insights, on the other sometimes neglecting a centralized plan. Many modern businesses, of all sizes, are engaging in business intelligence, but it’s only a pale version of what they could be doing.
Self-Service, Agile BI
With Shadow IT come a lot of risks: security risks, wasted time for inexperienced users, inconsistent approach, inefficiencies, wasted investment, etc. But when it comes to Shadow BI this is not the case – rather organizations should be wholeheartedly embracing the trend by enveloping all unofficial business intelligence into an overall data strategy.
Enter the concept of self-service BI. Gartner defines self-service BI as “end users designing and deploying their own reports and analyses within an approved and supported architecture.” Basically it is an approach to data analytics that empowers business users with access to corporate information without involving the IT department.
Providing self-service BI falls under engaging in a concept you may have heard of, agile BI. This is the idea of addressing the need to enable flexibility in business intelligence by working to accelerate the time it takes to gain value from analytics projects. It can mean technology deployment such as cloud-based BI, or data discovery dashboards that can allow users to work with data more rapidly and adjust to quickly changing needs.
People are doing Business Intelligence today, even if it is in a very simple form, and this speaks to the employees’ desire to have access to the tools they need. They want to get stuff done efficiently, and they’re probably more tech-savvy than they are given credit for. The self-service approach is the answer to this problem because it allows users to create this dashboards, visualizations, and reports on their own. Ideally it does so on a complex level behind the scenes, collecting and merging the data from various sources, while looking and feeling simple to use.
Self-service BI tools encourage users to base business decisions on data instead of intuition, and reduce the risk of contradictory reporting within organizations. Because the concept focuses around usability, it also encourages fast adoption of BI software. For startups, these are huge advantages: get your company going on a data strategy earlier and you can avoid many a wasted resource, and start a company-wide habit early on.
We all know it’s a good thing to use data, but most of us are still not so sure how we can use it effectively. And using it effectively nowadays means giving access to anyone, because creativity and insights are best done collaboratively. Companies should be encouraging their employees to do analytics on their own terms, but to do it using a strong business intelligence software that is both simple enough for anyone to use, but robust enough to handle all of a business’ data.